Artificial intelligence (AI)
Dojo by BullGuard, globally renowned IoT security platform for Communication Service Providers (CSPs), has announced the addition of DIP EDGE to the Dojo Intelligent IoT Security Platform (DIP). DIP EDGE is a software-based, IoT security gateway, a 5G and Multi-Access Edge Computing (MEC)-compatible Virtualised Network Function (VNF). DIP EDGE is a highly distributed, CSP-grade IoT security gateway with a comprehensive set of IoT-related threat detection and mitigation features. Dojo Intelligent IoT Security Platform The Dojo Intelligent IoT Security Platform is the first IoT security platform that enables CSPs to offer seamless IoT security services The Dojo Intelligent IoT Security Platform is the first IoT security platform that enables CSPs to offer seamless IoT security services across fixed and mobile broadband networks. DIP EDGE VNF can be deployed in any computing platform ranging from bare metal to a fully virtualised NFV (Networks Function Visualisation) platform, providing CSPs with flexible deployment options across their network infrastructure. DIP EDGE is designed to serve both fixed and mobile (4G and 5G) IoT security use cases and enables CSPs to offer their customers a seamless and continuous IoT security service regardless of the network to which they are connected. Dojo by BullGuard will showcase its 5G-enabled IoT security edge computing capabilities for CSPs at Mobile World Congress Barcelona, February 25 – 28 at the Fira Gran Via, Hall 5 – 5E41 in the Israel Pavilion. 5G and IoT integration “The intersection of 5G and IoT presents huge business potential and service innovations for CSPs and consumers, but also introduces a new set of cybersecurity threats to the existing threat landscape – one that requires an entirely new approach to securing the massive amount of vulnerable IoT devices,” said Yossi Atias, General Manager, IoT Security at BullGuard. “As the world’s first company to deliver a network-based IoT security platform, designed for the modern mobile network architecture, we’re proud to offer CSPs and their customers an integrated IoT security service. DIP EDGE provides an experience that is seamless and extremely consumer-friendly. Consumers simply register on the service, and any device that utilises the home or mobile network is automatically secured.” Built for CSP-scale, Dojo’s intelligent IoT Security Platform (DIP) is architected from the ground up to deliver the most advanced IoT security and parental control services. IoT cyberthreats mitigation DIP is designed to intelligently detect and mitigate IoT-related cyber threats, content filtering, and can be easily integrated into the CSP's existing network via open APIs DIP is designed to intelligently detect and mitigate a wide range of IoT-related cyber threats, content filtering, and can be easily integrated into the CSP's existing network via open APIs. The Dojo Intelligent IoT Platform’s container-based highly distributed architecture provides CSPs with the flexibility to provide network-based services running on any virtualisation platform. DIP makes it easier to load-balance, scale up and down, and move its functions across distributed hardware resources in a fully automated manner. Additionally, DIP enables continuous security and content filter updates, without interruption to the CSP’s customers. Multi-layered tech and IoT security The Dojo Intelligent IoT Security Platform uses a sophisticated multi-layered technology that covers multiple IoT security and parental control use cases for fixed and mobile networks. Cybersecurity features include: Automatic Device Discovery, Smart Vulnerability Scanner, Smart Managed Firewall, Smart Managed IDPS, Secure Web Proxy, Machine Learning (ML) and AI-based Behavioral Analysis, and DDoS prevention. Parental control features include: User and Device-based URL Filtering, Bedtime (internet time) Control and Usage Control for Headless Devices. According to a recent Accenture report, Ready, Set, Smart: CSPs and the Race to the Smart Home, the IoT market represents a $100 billion profit opportunity to the CSP industry. Survey data in the report gleaned from 26,000 consumers noted they are short on time, keen on convenience and eager for a single trusted provider that can offer support, security and the convenience of an ‘out of the box’ experience. 80 percent of survey respondents said they prefer a provider to manage their digital needs and 71 percent would choose a CSP for a connected home.
Video solutions maximise work safety, prevent the loss of insurance cover and physical damage to health, and help companies to comply with statutory protective measures. Geutebrück, international software and hardware specialist for video solutions, will be presenting a practical application at Logimat in Hall 6 / Stand D23. The system recognises the complete protective clothing and only then allows access to an area in which the corresponding protection is mandatory The algorithm-based optical recognition identifies, for example, the person wearing a safety vest together with a helmet. The system recognises the complete protective clothing and only then allows access to an area in which the corresponding protection is mandatory. If one of the two components is missing, access is not granted. This visualisation ensures that legal and operational protection regulations are complied with and significantly improves work safety. Detects All Types Of Objects In addition to wearing vests and helmets, the Geutebrück AI detects all types of objects. This is made possible by the individual training of an image-based neural network. Each solution is individually customised. The exact requirements often develop only in a face-to-face conversation. "Our solutions can be used in any situation where objects need to be detected, moved, repackaged, delivered, protected, weighed or counted. Also repairs can be carried out faster, lost items can be localised quicker and the cause of damage can be traced completely - even after months," says CEO Katharina Geutebrück. Protection Against Intruders Video solutions from Geutebrück are often installed to protect against intruders, vandalism or theftVideo solutions from Geutebrück are often installed to protect against intruders, vandalism or theft. But there is much more to the company's own high-performance software, which combines data and video images in an intelligent way. The privacy of employees or passers-by is protected at all times. In over 70 countries, Geutebrück is one of the most sought-after providers of video solutions. Geutebrück is a medium-sized family-owned enterprise in its second generation and is completely independent of public authorities, institutions, shareholders and banks. For nearly 50 years, Geutebrück has been offering made in Germany quality, innovation, reliability, flexibility, loyalty, experience and excellent service.
DigiCert, Inc., global provider of TLS/SSL, IoT and PKI solutions; Utimaco, one of the world’s top three Hardware Security Module providers; and Microsoft Research, a provider of quantum-safe cryptography, announced a successful test implementation of the “Picnic” algorithm, with digital certificates used to encrypt, authenticate and provide integrity for connected devices commonly referred to as the Internet of Things (IoT). This proof of concept provides a path toward a full solution, currently in development, that will protect IoT devices from future threats that quantum computing could pose to today’s widely used cryptographic algorithms. IoT devices with RSA and ECC cryptography Currently, most IoT devices use RSA and ECC to protect confidentiality, integrity and authenticity for device identities and communication Currently, most IoT devices use RSA and ECC to protect confidentiality, integrity and authenticity for device identities and communication. Experts from the security community, including Dr. Brian LaMacchia from Microsoft Research, predict that large-scale quantum computers capable of breaking RSA and ECC public key cryptography will exist within the next 10 to 15 years. Although this might seem like a long time away, many devices such as connected cars, smart homes, connected cities, connected medical devices and other critical infrastructures will either live longer than this or will take longer to update. “DigiCert, Microsoft Research and Utimaco are collaborating today to solve tomorrow’s problem of defending connected devices and their networks against the new security threats that the implementation of quantum computers will unleash,” said Avesta Hojjati, Head of DigiCert Labs, the company’s R&D unit. “Together, we are leading the market with development of hybrid certificates that inject quantum-resistant algorithms alongside RSA and ECC to ensure long-term protection.” DigiCert uses Utimaco Hardware Security Module The certificates are issued by DigiCert using the Picnic quantum-safe digital signature algorithm developed by Microsoft Research. To implement this algorithm and issue certificates, DigiCert has used an Utimaco Hardware Security Module. The full solution, in development, would provide quantum-safe digital certificate issuance and secure key management, helping companies future-proof their IoT deployments. The cooperation between DigiCert, Microsoft Research and Utimaco will help organisations implement secure and future-proof IoT products" “The cooperation between DigiCert, Microsoft Research and Utimaco will help organisations implement secure and future-proof IoT products that are protected against the potential security threats of quantum computing,” said DigiCert CTO. Dan Timpson. Enterprises will be able to cost-effectively deploy these solutions at any scale. Further, these companies will provide solutions and tools to manufacturers of IoT devices to remain prepared for quantum threats. The goal is to keep the sensitive information and high-value assets safe. Implementation of quantum-safe solutions “DigiCert, Utimaco and Microsoft’s successful test implementation provides a fundamental building block for the implementation of quantum-safe solutions,” said Dr. Thorsten Grötker, CTO at Utimaco. “Using these solutions, IoT manufacturers and other large organisations can innovate and develop products that are well prepared against coming quantum threats.” Brian LaMacchia, Distinguished Engineer and Head of the Security and Cryptography Group at Microsoft Research, said, “The work that Microsoft Research is doing with DigiCert and Utimaco is important to develop quantum-secure cryptographic algorithms, protocols and solutions today so that in the near future enterprises will be able to transition to and deploy quantum-safe cryptography. Working to ensure that their solutions are cryptographically agile will help companies avoid expensive and unscalable security practices to protect their IoT devices against future security threats.”
HID Global, a provider of trusted identity solutions, and Mist Systems, a pioneer in self-learning wireless networks powered by artificial intelligence (AI), announces that the two companies are working together to converge Bluetooth Low Energy (BLE)-based location services with Wireless LAN (WLAN) infrastructure for better deployment, management, and operations of IoT devices. With HID Location Services that is enabled by Bluvision, HID Global is an innovation in the IoT space as market pioneer in sensor beacons for workflow and event management. IoT asset tracking The Mist Learning WLAN is a single, converged cloud-based microservices platform for Wi-Fi and BLE indoor location services, eliminating the need for expensive overlay platforms and battery powered gateways for asset location and user engagement. The typical hospital today has over 20 different use cases for IoT tracking and management that can increase profitability" The combined solution provides a simple architecture for scalable IoT asset tracking and management that reduces costs, eliminates complexity, and fosters rapid adoption across organisational functions and use cases. “The typical hospital today has over 20 different use cases for IoT tracking and management that can increase profitability, patient care and overall patient experiences,” said Rom Eizenberg, Vice President of Sales at Bluvision, part of HID Global. Create seamless solutions “The introduction of AI-driven indoor location capabilities using standards-based BLE makes the deployment of these services scalable and cost effective, and reduces barriers to entry for many clinical scenarios previously locked out of benefiting from these state-of-the-art capabilities.” “By deploying Mist and HID Location Services together, enterprises have a proven solution to electronically touch and validate anything that moves, playing a strategic role in IoT environments,” said Bob Friday, Founder & CTO at Mist. “As we enter a new era of ubiquitous indoor location services, it is imperative that leading vendors come together to create seamless solutions for seamless and reliable BLE deployments.”
The past decade has seen unprecedented growth in data creation and management. The products and services that consumers use every day – and the systems businesses, large and small, rely on – all revolve around data. The increasing frequency of high-profile data breaches and hacks should be alarming to anyone, and there’s a danger data security could worsen in the coming years. According to DataAge 2025, a report by IDC and Seagate, by 2025, almost 90% of all data created in the global datasphere will require some level of security, but less than half of it will actually be secured. Nuanced approach to data security Security is a circle, not a line. Every actor involved in the handling and processing of data has responsibility for ensuring its securityThe rapid proliferation of embedded systems, IoT, real-time data and AI-powered cognitive systems – as well as new legislation like the European Union’s GDPR – means that data security has to be a priority for businesses like never before. With data used, stored and analysed at both the hardware and software level, we need a new and more nuanced approach to data security. Security is a circle, not a line. Every actor involved in the handling and processing of data has responsibility for ensuring its security. What this means in practice is renewed focus on areas of hardware and software protection that have previously not been top of mind or received large amounts of investment from businesses, with security at the drive level being a prime example. The importance of data-at-rest encryption In a world where data is everywhere, businesses need always-on protection. Data-at-rest encryption helps to ensure that data is secure right down to the storage medium in which it is held in a number of ways. Hardware-level encryption, firmware protection for the hard drive, and instant, secure erasing technology allow devices to be retired with minimal risk of data misuse. Data-at-rest encryption helps to ensure that data is secure right down to the storage medium in which it is held in a number of ways A recent report from Thales Data Threat found that data-at-rest security tools can be a great way to help protect your data. However, it’s important to note that this must be used in conjunction with other security measures to ensure that those that fraudulently gain access to your key management system can’t access your data. Ensuring drives to be Common Criteria compliant One straightforward test any business can do to ensure its storage is as secure as possible is to check whether the drives are Common Criteria compliantDespite the clear benefits, this kind of encryption lags behind other areas, such as network and endpoint security, in terms of the investment it currently receives. The same Thales Data Threat report found that data-at-rest security was receiving some of the lowest levels of spending increases in 2016 (44%), versus a 62% increase for network and a 56% increase for endpoint security. One straightforward test any business can do to ensure its storage is as secure as possible is to check whether the drives are Common Criteria compliant. Common Criteria is an international standard for computer security certification, and drives that meet this standard have a foundational level of protection which users can build on. Providing an additional layer of security The retail industry has seen a spate of security breaches recently, with several major US brands suffering attacks over the busy Easter weekend this year. As frequent handlers of consumer card information, retailers are particularly vulnerable to attack. Data-at-rest encryption could enhance security in these instances, providing an additional layer of security between customer records and the attacker The advanced threats retailers face can often evade security defences without detection. Such a breach could grant attackers unrestricted access to sensitive information for possibly months – some breaches are known to have been detected only after consumer payment details appeared on the dark web. These types of undetected attacks are highly dangerous for retailers, which are relatively helpless to protect consumer information once their defences have been compromised. Data-at-rest encryption could significantly enhance security in these instances, providing an additional layer of security between customer records and the attacker which has the potential to make the stolen data valueless to cyber criminals. Industries in need of data-at-rest encryption Healthcare organisations, which hold highly sensitive customer and patient information, have a strong use case for data-at-rest encryption. With the widespread adoption of electronic patient health records, that data is increasingly more vulnerable to attack. Recent research from the American Medical Association and Accenture revealed that 74% of physicians are concerned over future attacks that may compromise patient records. With the widespread adoption of electronic patient health records, that data is increasingly more vulnerable to attack The financial sector would also benefit from further investment in data-at-rest encryption, given 78% of financial services firms globally are planning on increasing their spending on critical data, according to Thales’ Data Threat Report. It’s helpful to view security as a circle in which every piece of hardware and software handling the data plays its part SMEs and enterprises are not immune to security threats either – with growing numbers of people traveling for work or working remotely, the risk of sensitive business data becoming exposed via device theft is heightened. Usernames and passwords have little use if thieves can simply remove unencrypted hard drives and copy data across. Securing every hardware and software Technology vendors often focus on aspects of hardware and application security that are within their control. This is understandable, but it risks proliferating a siloed approach to data security. There is no single line for data security -- rather, it’s helpful to view it as a circle in which every piece of hardware and software handling the data plays its part. There’s a clear need for more industry dialogue and collaboration to ensure data security is effectively deployed and connected throughout the security circle and across the value chain.
According to the reports of not-for-profit organisation Gun Violence Archive, the year 2018 has seen 323 mass shooting incidents as of November 28 in the United States. This number is 346 for the year 2017 and 382 for 2016 (more statistics are available here), with “mass shooting” defined as cases where four or more people are shot or killed in the same time period and location. While definitions of mass shooting vary with organisations in the US, the count of over 300 incidents per year, or about once per day on average, is simply alarming. It raises public safety concerns, ignites debates and protests, which in turn lead to public unrest and potentially more violence, and increases costs for governments from the regional to federal level. Most importantly, the loss of lives demands not only improvement in post-incident handling and investigation, but also new prevention technologies. Gunshot detection solutions AI weapon detection offers a more efficient alternative to prevent active shooting There are several gunshot detection solutions in the security market, commonly used by law enforcement agencies to detect and locate gun fires. These systems function based on acoustic recordings and analyses and often in combination with signals detected by sensors of the optical flash and shockwave when a gun is fired. However, gunshot detection by nature dictates that the law enforcement can only react to a shooting incident that has occurred. With fast action, law enforcement can prevent the incident from escalating, but lives that are lost cannot be recovered. With the development of artificial intelligence in object recognition, AI weapon detection offers a more efficient alternative to prevent active shooting: AI can visually detect guns based on their shapes before they are fired. The AI is trained to recognise firearms in different shapes, sizes, colours, and at different angles in videos, so that the AI weapon detector can be deployed with existing cameras systems, analyse the video feeds, and instantly notify security staff when a gun is spotted. Comparison of the advantages for law enforcement and public security agencies Legacy gunshot detection using sensors AI weapon detection Reactive measure: detect after guns have been fired Proactive measure: detect before guns are fired Time to action: within 1 second Time to action: within 1 second Unable to provide visual data about shooter(s) Can provide data about shooter(s) based on the camera recording: clothing, luggage (backpack, handbag, etc.), facial features, vehicle Unable to track the location of the shooter(s) before and after shooting because of the lack of sound Can track the shooter(s) using AI Person & Vehicle Tracking, AI Face Recognition, and AI License Plate Recognition False detection caused by similar sound such as fireworks and cars backfiring Minimal to no false detection, as AI can distinguish different types of handguns and rifles from normal objects (umbrella, cellphone, etc.) Require physical deployment of gunshot detection sensors Can be used with existing camera systems, do not require special hardware Complicated to deploy, require highly trained professional Easy to deploy as an add-on to existing video surveillance system - Can integrate with gun-shot detection to create a “double knock” audio and video active shooter alert system Gun-shot detection advantages In addition to advantages for law enforcement and public security agencies, this type of visual-based pre-incident detector has three-fold advantages for the public: Save lives by spotting the shooter before the shooting event. Minimise the chaos entailing an incident: panic and chaos caused by a shooting incident often adds to injury, as people run, fall, trample on others… With an AI weapon detector, when a gun is spotted, the system sends an alert to security staff, who can quickly control the situation in an organised manner and apprehend the intending shooter. Can be added as a SaaS (Security as a Service) component to small business and home surveillance systems, e.g., intrusion detection alerts (home invasion incidents with firearms number over 2500 per year nationwide). For a complete active shooter detection system, video-based AI detector can operate in conjunction with gunshot detectors for enhanced security. Traditional X-ray based weapon detection or metal detection entrance systems are complicated and expensive; with AI video technology, active shooter detection system can be cost-effective, and after all, what price tag can one put on a life? Written by Paul Sun and Mai Truong, IronYun
In my coverage of China Tariffs impacting the security industry over four recent articles, products on the tariff schedules routinely integrated into security solutions included burglar and fire alarm control and transmission panels, video surveillance lenses, HDTV cameras used for broadcast use cases and fiber optic media converters. The general ‘callout’ of ADP (Automatic Data Processing) devices and peripherals technically includes servers, workstations and microcomputers, all of which are commonly used to support security solutions. The underperformance, from June 15 to August 24, of U.S. stocks with high revenue-exposure to China, and that of Chinese stocks with high revenue-exposure to the United States was significant and almost identical at 3.2%, significant losses to some investors already involved in security industry M&A activity. Significant public safety Facial Recognition (FR) vendors leveraging AI expanded their market focus to retail and public safety While it was not apparent that practitioners’ security program budgets kept pace with the growth of the more popular solution providers like video surveillance and cyber security, the ICT industries supporting the security economy continued to expand, especially in wireless and wired infrastructure, including preparations for 5G wireless rollouts. These omnipresent technologies drove significant public safety, smart city and public venue projects in 2018. Facial Recognition (FR) vendors leveraging AI expanded their market focus to retail and public safety. In 2018, virtually every public presentation, webinar and published Q&A on social media monitoring and facial recognition technologies I worked on, involved significant pushback from privacy advocates, almost to the point of alarmism. Massive risk reduction Several solution providers in these areas have made significant strides on data protection, accuracy, powered by AI and documented crime reduction cases; however, this real news is quickly shadowed by privacy advocates, seemingly ignoring massive risk reduction, especially in the case of active assailants and gang-related crime. Will FR become mainstream? The cautious security industry may take a cue from the maverick retail industry, sports venue and VIP verification solution providers that grew in 2018. 2019 trends: presupposition or repudiation; winners and losers. Chinese tariffs have had a huge impact on the security industry, which can be seen from changes to U.S and Chinese stocks Although technology adoption forecasting is inexact, there are definitive opportunities in the security industry born on necessity. With the widespread problem of false alarm transmission and inability for first responders to ‘be everywhere,’ developers of solutions that provide automated verification and alternative security incident detection are expected to become mainstream. Promising detection systems The use of AI, NLP, LiDAR, UAS (Unmanned Aerial Vehicles aka drones) with surveillance and thermal imaging will grow, mostly due to higher acceptance in other industries like autonomous vehicles, rail safety, terrain and post devastation mapping/rescue. However, legacy ‘listing’ or certification organisations will be forced to make an important decision for their own survival: work toward integrating these promising detection systems into acceptance by insurance, licensing and standards development organisations. 2019’s ‘true’ Industrial Philanthropists will be needed to fund early warning tech for firefighters and the presence of active assailants 2019’s ‘true’ industrial philanthropists will be needed to fund early warning tech for firefighters and the presence of active assailants. For these use cases, 5G infrastructure rollouts, FR acceptance, lower cost perimeter detection and long range object and fire recognition by LiDAR and Thermal imaging will all be watched closely by investors. Should public agencies and philanthropical solution providers in the security industry cross paths, we may just yet see a successful, lifesaving impact. Cyber risk profile The ‘Digital twin’ refers to a digital replica of physical assets (physical twin), processes, people, places, systems and devices that can be used for various purposes. Your ‘Security Digital Twin’ has a similar physical and cyber risk profile, either through common threats, similar assets or both. Good news: managing your risk, protecting assets and securing your facilities in 2019 will get easier as security digital twin profiles will grow in maturity, while keeping their data sources private. This will be accelerated by the maturity of AI-based, auto-generated visualisations and image recognition, that happens to also drive the FR solutions. The 5G wireless infrastructure market is emerging as far more of a quantum leap in connectivity, like ‘wireless fiber optics’ performance, than an upgrade to 4G LTE. The 5G infrastructure market will be worth $2.86 billion by 2020 and $33.72 billion by 2026, growing at a compound annual growth rate (CAGR) of 50.9%. Intelligent applications The explosion of ingested voice, video, and meta-data, the interconnectivity of devices, people and places, and the integration of intelligent applications into expanding ecosystems all require faster communications. To be more accurate, 5G rollouts will accelerate in 2019; however, current project funding will include and be impacted by future enterprise security connectivity: 5G and FWA (Fixed Wireless Access). 5G rollouts will accelerate in 2019; however, current project funding will include and be impacted by future enterprise security connectivity Quite simply put, larger solution providers are gently coaxing practitioners into seemingly ‘open systems;’ the negative discovery during an M&A process, audit or integration with a smart city’s public/private partnerships will continue to be revealed, and related industries will force reform. Autonomous things will be enabled by AI and image recognition. With few affordable rollouts of security robots and outdoor unmanned ground vehicles (UGV) that leveraged platforms popular with research and even NASA, the autonomous security robot was mostly MIA from a security practitioner’s program in 2018. Perimeter intrusion detection One platform was even accused of intimidating homeless people in a public place, at a major city. Industries mutually beneficial are often unaware of each other; this will change gradually: one major domestic airport is currently evaluating a UGV platform performing perimeter intrusion detection, runway weather conditions and potential aircraft taxiing dangers. The platform is being used largely in transportation research, yet offers significant opportunities to the security industry. Research firm Gartner estimates that 70% of today’s technology products and services can be enhanced with ‘multi-experience’-based VR/AR/MR The ‘immersive experience’ of virtually any security or threat detection is a twist on virtual/augmented/mixed reality (VR/AR/MR) with additional sensory features. Although VR/AR/MR is well underway in other industries, there are several companies with solutions like VR-based active assailant training that could provide a fighting chance for practitioners, employees, visitors, faculty and children. Research firm Gartner estimates that 70% of today’s technology products and services can be enhanced with ‘multi-experience’-based VR/AR/MR. Security ecosystem members Not necessarily MIA, but of special mention is the need of security and safety practitioners to prioritise communications systems over ‘nice to have’ expansive video surveillance systems for mass casualty threats. This will eventually improve with 5G for Enterprise solution rollouts. At the past GSX and upcoming CES Technology trade shows, a new roundup of technologies is discovered: a wider diversity of protection promise to save ASIS members on their technical security program is realised. With each of the ‘winners,’ (5G, AI, NLP, LiDAR, UAS [Unmanned Aerial Vehicles aka drones], thermal imaging, digital security twins and smart-city-friendly technologies) it is both exciting and challenging work for both security practitioners and solution providers. All things equal and with the necessary technology acceptance testing processes, this is a truly great time for security ecosystem members.
Constantly optimising deep learning algorithms yields better video analytics performance, even in complex applications such as facial recognition or in scenarios with variable lighting, angles, postures, expressions, accessories, resolution, etc. Deep learning, a form of artificial intelligence (AI), holds the potential to enable video analytics to deliver on long-promised, but not often delivered performance. Our AI series continues here with part 2. Adapting existing hardware Today, low-cost system-on-chip (SoC) camera components enable deep neural network (DNN) processing for the next generation of intelligent cameras, thus expanding the availability of AI processing to a broader market. AI software can even add learning capabilities by adapting existing hardware to AI applications AI software can even add learning capabilities by adapting existing hardware to AI applications. Today’s smartphones include cameras, gyroscopes and accelerometers to provide sufficient data to drive AI applications. Software can adapt existing hardware to transform them into AI devices capable of continuous learning in the field. Inside a video camera, real-time deep learning processing can be used to detect discarded objects, issue loitering alarms and detect people or objects entering a pre-defined field. Data capture form to appear here! Detect anomalous data Additional capabilities are applicable to demanding environments and mission-critical applications, such as the perimeter protection of airports, critical infrastructures and government buildings, border patrol, ship-tracking and traffic-monitoring (e.g. wrong-way detection, traffic-counts and monitoring roadsides for parked cars: all vital video security solutions). IoT is transforming the lowly security camera from a device that simply captures images, into an intelligent sensor that plays an integral role in gathering the kind of vital business data that can be used to improve commercial operations in areas beyond security. For example, cities are transitioning into smart cities. Deep learning enables systems to search surveillance footage, to detect anomalous data, and to shift surveillance from post-incident response to providing alerts during, or even before, an event. The ability of deep learning for video analytics is much more sophisticated and accurate Make critical decisions Deep learning can eliminate previous video analytics limitations such as dependence on a scene’s background. Deep learning is also more adept than humans at discerning subtle changes in an image. The ability of deep learning for video analytics is much more sophisticated – and accurate – than the programmed approaches previously employed to identify targets. AI is a timely solution in an age when there is more video surveillance than ever. There are too many cameras and too much recorded video for security operators to keep pace with. On top of that, people have short attention spans. AI is a technology that doesn’t get bored and can analyse more video data than humans. Systems are designed to bring the most important events and insight to users’ attention, freeing them to do what they do best: make critical decisions. Multiple camera streams AI can reduce information overload to enable humans to work with the data more efficiently The video benefits reflect the larger goal of AI to amplify human skills. AI can reduce information overload to enable humans to work with the data more efficiently. Another benefit is faster search, and new systems make searching video as easy as searching the internet. AI enables specific people or cameras to be located quickly across all the cameras at a site. Searching can be directed by a reference images or by physical descriptors such as gender or clothing colour. Consider a scenario of a child missing from a crowded shopping mall: Every second can seem like hours, and artificial intelligence and neural networks can enable a rapid search among multiple camera streams using only one photo of the child. The photo does not have to be a full-frontal passport-type photos; it could be a selfie from a party as long as the face is there. Intrusion detection scenario AI can find her and match her face from among hundreds of thousands of faces captured from video, in nearly real time. AI can also continuously analyse video streams from the surveillance cameras in its network, distinguishing human faces from non-human objects such as statues and animals. Privacy concerns are minimal as there is no ID or personal information on the photo, and the image can be erased after use. And there is no database of stored images. In a perimeter security/intrusion detection scenario, an AI-driven video system can avoid false alarms by easily distinguishing different types of people and objects, e.g., in a region set up to detect people, a car driving by, a cat walking by, or a person’s shadow will not trigger the alarm. Part three coming soon. If you missed part one, see it here.
AI Is currently a buzzword in the physical security industry, and it is also a force that has the potential to transform the industry. Following are the basics of AI (and the related term “deep learning") in part one of our AI series. Artificial intelligence (AI) is the broad computing category referring to intelligence that is displayed by a machine, as opposed to a living creature. Informally, AI refers to machines that mimic the cognitive functions we associate with living creatures, such as learning and problem-solving. Trends driving growth in AI Three trends in the computer industry are driving rapid growth in artificial intelligence. The trends are: Data capture form to appear here! Video surveillance data makes up 60 percent of Big Data, and the amount is rising 20 percent annually Emergence of computer hardware capable of solving complex calculations, specifically graphics processing units (GPUs, which use “parallel processing” instead of “serial processing” used by familiar central processing units [CPUs]). Multiple computations are carried out simultaneously, in parallel rather than in a series. It’s a more scalable approach: Large problems are divided into lots of smaller problems that can be solved at the same time. Development of programming approaches to “train” systems more effectively, specifically neural networks, which work in conjunction with the parallel processing of GPUs. A neural network is a computing system made up of numerous simple, highly interconnected processing elements, typically organised in layers, with each layer made up of interconnected nodes. As each layer computes a result, that result determines the input for the next layer. There may be more than a hundred layers, which enables processing of large amounts of data into complex classifications. A proliferation of sensors (including video cameras) that produce a large enough mass of data to enable systems to be “trained” effectively (a.k.a., “Big Data”). The proliferation of “Big Data” ensures there is plenty of data for training. Video surveillance data makes up 60 percent of Big Data, and the amount is rising 20 percent annually. This proliferation of data feeds artificial intelligence and increases capabilities for a range of systems. Training of an AI-powered system In a neural network operating on a GPU, learning rules modify the weights (importance) of connections; each layer has a different “weighting” that reflects on what was learned at the previous layer. When presented with a data pattern (such as a video image), the neural network analyses what the pattern might be. Deep learning involves use of large amounts of data from which the system can “learn” in a neural network Training involves determining how far the initial answer is from the actual one and making appropriate adjustment in the connection weights. In highly simplified terms, that’s how the system “learns.” There are multiple stages of classification, almost like filters, with each guiding the path to a correct analysis. Deep learning is part of a broader family of machine learning methods and the concept that is most relevant to the video market. Deep learning involves use of large amounts of data (for example, video images) from which the system can “learn” in a neural network. Deep learning in video surveillance systems By being exposed to many instances of data, deep learning systems discern patterns and begin to generaliseThe interconnected processing elements of a neural network, working in parallel on a graphics processing unit (GPU) to solve a problem, are designed to mimic the human brain and its billions of interconnected neurons. This aspect of artificial intelligence, known as deep learning, is the basis for a new family of video surveillance systems offering superior performance to historic systems. This approach is poised to transform the effectiveness of video surveillance systems. Historically, computers have been programmed using video analytics algorithms. In contrast, deep learning systems are “trained.” If you want to identify a cat, you provide lots of images of cats, data which the system breaks down into smaller components and looks for commonalities. It then “learns” the common characteristics among the examples. To maximise training, the more data a system is presented, the more refined it becomes – i.e., the more it “learns.” By being exposed to many instances of data, deep learning systems discern patterns and begin to generalise. From training to inference Deep learning can achieve super-human pattern recognition accuracy, resist interference, and classify and recognise thousands of featuresWhile a computer programmer might spend months writing instructions to tell a computer what a car looks like, a neural network can “learn” by being exposed to many examples – no additional programming involved. But training a neural network is also time-consuming; it might take hours or days to complete. Training is also computationally intensive. However, once a neural network has been trained, it can be used to “infer,” for example, to decide whether a new image is a cat. Inference is less computationally intensive, which enables deployment of trained systems on devices such as network video recorders (NVRs) or even in video cameras at the network edge. Deep learning can achieve super-human pattern recognition accuracy, resist interference, and classify and recognise thousands of features. Those qualities make it especially useful for video analytics applications. Part two coming soon.
A rapid string of merger and acquisition (M&A) transactions as 2018 passed into 2019 suggests the physical security industry may be on the verge of a busy year of companies buying other companies. Observers have noted a large amount of investment capital currently available to be invested in security M&A, and plenty of entrepreneurial companies are looking to be acquired. Joe Grillo, CEO of ACRE, previously hinted at upcoming M&A activity for his company by the end of 2018, foreshadowing ACRE’s late-year announcement to acquire access control company Open Options, Addison, Texas.The VaaS cloud-based image capture platform includes fixed and mobile license plate reader cameras driven by machine learning Just days later, in the midst of the holiday season, Qognify announced its plan to acquire On-Net Surveillance Systems Inc. (OnSSI) and sister company SeeTec GmbH. Then came an even larger announcement: Motorola has acquired VaaS International Holdings Inc., a data and image analytics company for $445 million. The VaaS cloud-based image capture and analysis platform includes fixed and mobile license plate reader cameras driven by machine learning and artificial intelligence. Most recently, ADT announced yet another acquisition, Advanced Cabling Systems, a technology integration company in the South, thus continuing consolidation on the integration side of the business. There are likely to be further mergers and acquisitions in the video surveillance supply base in 2019 Continuation of the trend In the case of the Qognify and Motorola deals, Jon Cropley, Principal Analyst, Video Surveillance & Security Services, IHS Global Limited, sees them as the next chapter in an M&A trend going back several years. “I think this is a continuation of what we have been seeing in recent years of video surveillance software vendors being acquired,” he says. In the face of intense price competition, vendors have found it increasingly difficult to compete based on hardware features" “In the face of intense price competition, vendors have found it increasingly difficult to compete based on hardware features and are looking at software to offer unique competitive advantages.” In short, he sees it as a continuation of a trend that previously saw Canon acquiring Milestone Systems and Briefcam, Panasonic acquiring Video Insight and Tyco acquiring Exacq. “There are likely to be further mergers and acquisitions in the video surveillance supply base in 2019,” adds Cropley. “However, a spree of large-scale mergers and acquisitions is not expected.” Memoori, another market research firm, forecasts that the value of acquisitions could actually decline marginally in 2019 in value terms but increase in number. This observation is based on Memoori’s charting of physical security deals over the last 18 years. Jim McHale, Managing Director of Memoori, says there have been four cycles of increase and decline in activity, often exaggerated by billion dollar deals in one year such as the merger of Johnson Controls and Tyco of $165Bn in 2016. Access control when combined with identity management is punching well above its weight, and this trend has continued Access control to open systems Only time will tell whether the new year pattern of M&A activity is a coincidence or a harbinger of a busy M&A year ahead “It may be too early to make judgements on the future based on the last four weeks, but there are some interesting points that can be made when compared with our 2018 analysis,” says McHale. “Access control when combined with identity management is punching well above its weight, and this trend has continued. "Acre has been a major contributor and has completed some 10 acquisitions. In general, the access control business has been slow to move to open systems, and hopefully we can expect this trend toward openness to continue as it will give additional growth to the business.” For more commentary from Memoori, see their report “Major Trends in the Global Access Control Market 2018”. Only time will tell whether the new year pattern of M&A activity is a coincidence or a harbinger of a busy M&A year ahead. While past trends may provide a glimpse of what’s coming, there are always new variables. It’s a sure bet the overall trend toward consolidation will continue but predicting the pace and timing of individual transactions is almost impossible. In any case, it will be interesting to watch how 2019 unfolds on the M&A front, among other factors in a changing industry.
Exabeam, the next-gen SIEM company, announces that NTT DATA Corporation (NTT DATA), its partner and one of the providers of technology and services for government and business, has chosen to secure its global operations using Exabeam’s Security Management Platform (SMP), which provides unlimited data collection, machine learning and analytics for modern cyber threat detection and response. NTT DATA’s internal system is used throughout more than 50 countries and regions, 210 cities and by 34,500 employees in Japan and 75,500 employees overseas. It is a fast-moving company that has acquired many businesses over the last five to 10 years, resulting in the inheritance of a number of different legacy SIEM platforms. However, these solutions were lacking, and NTT Data wasn’t obtaining the visibility it needed to keep pace with modern cyberthreats. Disparate legacy systems Exabeam was already our valued partner, and we were so confident in the company’s security solution" “Exabeam was already our valued partner, and we were so confident in the company’s security solution, we decided to use it ourselves, to remove complexity and unify our disparate legacy systems that were ineffective at protecting against modern threats,” said Hiroshi Honjo, head of Cyber Security and Governance at NTT DATA. “Having Exabeam’s unlimited data lake and attractive pricing model made the difference for our large organisation.” Exabeam’s SMP provides NTT DATA with scalable, behavioural modelling, machine learning, and advanced analytics for comprehensive insider and entity threat detection throughout Japan, APAC, North America, and Europe. This functionality was vital to the NTT DATA team because they required greater visibility into potential cyberthreats throughout the organisation and in all locations around the world. Automated incident response “NTT DATA’s journey was a unique one, since they had multiple legacy logging platforms in use globally. Exabeam was able to replace or consolidate each system using our next generation platform, and we accomplished the initial rollout in a matter of months,” said Nir Polak, CEO, Exabeam. “The swiftness of that transition is critical to maintaining secure operations, especially when dealing with such a geographically dispersed enterprise.” Automated incident response allows teams to respond to security incidents rapidly and with less effort Automated incident response allows teams to respond to security incidents rapidly and with less effort. At the SMP’s foundation is the Exabeam security data lake, designed to store all event logs at a predictable and flat price. This frees the NTT DATA security team from manually analysing data logs – and instead they can focus on quickly identifying and responding to security threats. SIEM solution According to Honjo, “The second phase of our project will be to look at use cases and fine tune the SIEM solution to work for our business needs. Overall, we are very happy with how well Exabeam met our stated deadlines and how quickly we are able to realise value from the product. We look forward to introducing Exabeam to our global customers.” Recently, Exabeam was identified by Gartner, Inc. in the 2018 Magic Quadrant for Security Information and Event Management. The company was positioned as a Leader based on completeness of vision and ability to execute.
Knightscope, Inc., a developer of advanced physical security technologies focussed on enhancing U.S. security operations, announced that it is has taken a major step in its commitment to help better secure schools across the country by selecting Clovis Unified School District in California as its beta testing location for a suite of new technologies under development. The Company had prior announced this effort earlier this year when it solicited students to get involved and submit essays on how Knightscope’s fully autonomous security robots could help in a school setting. Security robots to monitor school safety “With over 100,000 schools in the country, we need to develop a new set of tools and technologies as a critical part of our long-term mission to better secure the United States of America,” said William Santana Li, chairman and chief executive officer, Knightscope, Inc. Knightscope’s robots will provide the authoritative presence needed on a school campus and provide actual intelligence by filling in the blind spots"“Being able to utilise a real-world environment to test, sample, and iterate on new capabilities while inspiring students to pursue STEM careers is certainly a winning combination,” continued Li. “As a teacher of thirty years, my philosophy has always been to be proactive instead of reactive, and the idea of security robots monitoring a school is definitely a proactive approach to school safety. Knightscope’s robots will provide the authoritative presence needed on a school campus and provide actual intelligence by filling in the blind spots with their ‘eyes and ears,’” said Clifford A. Nitschke, Jr., AP United States Government and Politics Instructor, Clovis North High School. Trialling a new technology in school safety Mr. Nitschke’s class submitted the winning proposal to Knightscope. “We are honoured to be chosen by Knightscope and to be given the opportunity to pilot a new and exciting technology in the field of school safety.” The Clovis United Unified School District Governing Board is scheduled to meet on January 16, 2019 to formally accept the beta testing program by Knightscope. The meeting is planned to occur at 6:30pm at the Clovis Unified Professional Development Building, 1680 David E Cook Way, Clovis, CA 93611. Assuming an approval by the Board, the parties will determine implementation timing thereafter.
According to Save The Rhino statistics, over 1000 rhinos are killed annually in South Africa. These harrowing poaching statistics display a gloomy future for survival of this beautiful species. While many attempts have been undertaken over the past ten years to combat the devastating results of poaching, the country has not yet seen a steady decline in numbers year-on-year. It is with this knowledge that AxxonSoft’s Global Marketing Director, Colleen Glaeser, who is based in South Africa, decided to create a strategical and proactive anti-poaching approach, utilising the tools at her disposal, assisting a country in dire need of assistance. While Deep Learning, using Artificial Intelligence and neural network analytics in its algorithm, is not new to the security and surveillance industry, Colleen and the team at AxxonSoft global took the technology a step further, developing and implementing the software to help differentiate between humans and animals. Identifying actual poaching threats AxxonSoft’s surveillance software, which leverages Artificial Intelligence and Deep Learning technology now alerts the operators in the control room to an immediate poaching threat The implementation of this technology in game reserves and parks across South Africa has certainly been a game-changer regarding the war against poaching. For two reasons namely; this neural network solution can identify actual poaching threats (distinguishing poachers from their prey) while providing a proactive surveillance solution as opposed to a reactive one. Predominately utilised for face and license plate recognition, Deep Learning technology has never been adapted to tell the difference between humans and animals. Prior to the incorporation of Deep Learning in anti-poaching surveillance, software often failed control rooms and response units in that false alarms were on many occasions, set off by animals, insects and weather. Control rooms were not able to tell the difference between an actual threat and a false alarm, which often resulted in exhausting resources as teams were dispatched for animals who had touched the fence while grazing in their natural habitat. AxxonSoft’s leading surveillance software, which leverages Artificial Intelligence and Deep Learning technology now alerts the operators in the control room to an immediate poaching threat as poachers try and breach the fence perimeter to enter the reserve or park. Proactive surveillance solution AxxonSoft’s Deep Learning technology provides a proactive solution to surveillance whereas previous systems were somewhat archaic and reactive in their response to real threats Global Marketing Director for AxxonSoft, Colleen Glaeser says, “Our Deep Learning technology has been extremely successful thus far in telling the difference between animals and humans as the neural network algorithm can identify, through certain indicators, whether a human or animal has set off the alarm. If the software detects a human, the operations team is immediately notified and a dispatch team is sent to the scene in question.” Furthermore, AxxonSoft’s Deep Learning technology provides a proactive solution to surveillance whereas previous systems were somewhat archaic and reactive in their response to real threats. Due to expansive terrain and limited resources, rangers and antipoaching units often get to the scene of the crime too late. With the AxxonSoft technology, as soon as the breach occurs, cameras will identify if the breach has been caused by an animal or human, and the control room is immediately notified as to where the occurrence has taken place in the reserve or park. The dispatch team is given the necessary information and they head to the site where the occurrence has taken place. Real-time identification of threats By utilising this technology, we have been able to take a proactive approach, identifying the threat in a real time situation" The beauty about Deep Learning and Neural Network analysis is in its ability to learn and understand the conditions which lead up to an event, and that ultimately allows us to prepare for threats or potential breaches when the known conditions are met. “AxxonSoft’s technology has proved very successful in preventing killings as the team is able to get to the scene of the crime quickly. “By utilising this technology, we have been able to take a proactive approach, identifying the threat in a real time situation. The AxxonSoft team and I really believe this anti-poaching solution can aid in the war against poaching and drastically bring down the upsetting statistics. I can attest to the fact that we have seen great success in curbing poaching,” concludes Glaeser.
For more than seven decades, the name Porsche has been synonymous with quality and performance in automobiles. In 2018, the German automaker’s position and recognition around the world is unparalleled among luxury car brands, engendering consumer passion and loyalty that runs from admirers through collectors. Such qualities are proudly shared and returned around by those who represent the brand around the world, emblematic of the brand’s commitment to providing a sales and service experience as effortlessly exceptional as the vehicles themselves. Such commitment is the order of the day in Chandler, Arizona, where the family-owned and locally operated Porsche Chandler serves brand enthusiasts daily, showcasing a select range of new, certified and pre-owned Porsche models in a 36,500-square-foot facility, beautifully designed to feature both the majesty of the Porsche brand and the surrounding Arizona landscape. Camera surveillance solutions New and existing camera installations integrated seamlessly via IDIS’s DirectIP line of true plug-and-play network video recorders Porsche Chandler is known throughout Arizona for providing exceptional customer experiences, on behalf of a brand known globally for effortless, high-quality performance Scottsdalebased SARC Monitoring designed a security solution to match. Crafting and implementing an innovative virtual guarding solution that brought together powerful military, intelligence, and law enforcement expertise (and best practices) with equally powerful, next-generation surveillance technologies, SARC worked closely with dealership security personnel to comprehensively secure the full dealership space, including all personnel, visitors, around the clock, beyond the reach and capability of traditional manned guarding, video verification, and camera surveillance solutions. At the heart of SARC’s solution is IDIS technology. New and existing camera installations integrated seamlessly via IDIS’s DirectIP line of true plug-and-play network video recorders. Minimising downtime IDIS NVRs, designed to eliminate device compatibility issues through the support of multiple industry standards and 3rd party protocols, avoid the most common integration, compatibility, and installation challenges, preventing delays and minimising downtime. Multiple IDIS DR-8364(F) NVRs provide Porsche Chandler signature high-performance, and a user-friendly surveillance system that fully supports their existing IP camera infrastructure. The combination of cameras and recorders are installed, integrated with the dealership’s low-profile speaker system, and used by on-site personnel and SARC’s highly trained rapidresponse team of remote monitors to provide edge-to-edge comprehensive surveillance in support of security, analytics, and even business intelligence, including after hours. Situational awareness The presence of multiple security guards, large visible camera installations, at the levels required to cover the nearly 36,500 square foot indoor/outdoor In keeping with the tradition of effortless luxury experiences for Porsche customers, the sales environment is designed to facilitate a stress-free browsing, sales, and customer service experience for guests, seeking to offer a perfect balance of staff support for questions and transactions, with space to move and explore inventory and consider options without crowding, hassle, or pressure. The presence of multiple security guards, large visible camera installations, at the levels required to cover the nearly 36,500 square foot indoor/outdoor, multi-level and multi-purpose complex, would not ideally serve the dealership’s commitment to a seamless, low hassle, pleasant, and stress-free sales and customer-service environment. Porsche Chandler required a next-generation security and surveillance solution that would provide maximum visibility and facilitate full situational awareness by dealership management and security staff, comprehensively protecting both people and property, without unnecessary intrusion. Law enforcement fields SARC Monitoring’s unique and innovative virtual guarding model—which goes beyond traditional remote monitoring and video verification models by leveraging experienced personnel and best practices from the military and law enforcement fields, and incorporates latest-generation, feature-rich video surveillance technologies—now delivers round-the-clock coverage of Porsche Chandler’s sprawling indoor/outdoor complex, exceeding the typical capabilities of traditional security approaches to such spaces, while doing so at a significantly lower cost. Features enhancing the value and utility of the IDIS DR-8364(F) NVRs toward meeting Porsche Chandler’s security requirements and the needs of SARC Monitoring’s team of 24/7 remote monitoring and rapid response personnel, include the the DR-8364(F)’s support for 64 IP channels of 4K UHD (with a maximum incoming throughput of 900Mbps), meaning that fewer NVRs are needed to support large numbers of cameras now (and as added in the future). Ensuring data integrity Fewer devices mean less time spent on maintenance tasks and reduced complexity of the surveillance system. Support for H.265 with IDIS Intelligent Codec and Motion Adaptive Transmission (MAT) further reduces the need for additional bandwidth and storage upgrades, providing up to a 90% reduction in both bandwidth and storage utilisation, meaning more data can be transferred on existing cabling and saved in existing storage space. IDIS’s Critical Failover suite of features includes features such as RAID 5 storage redundancy, dual power supply redundancy, and NVR failover The included IDIS’s Critical Failover suite of features includes features such as RAID 5 storage redundancy, dual power supply redundancy, and NVR failover (which provides support for a standby NVR that continually monitors the primary NVR, taking over recording if the primary hardware fails), ensuring data integrity and system operation are automatically monitored and maintained, simplifying system support and maintenance tasks. Optimised security posture And the intuitive DR-8364(F) NVR interface, common to all IDIS products, minimised installation, training, and transition costs. IDIS’s unusual license-free software model, compatibility guarantees, and industry-leading warranty further minimises total costs for Porsche Chandler. “The comprehensive virtual guarding solution helps Porsche Chandler to achieve better security outcomes, keeping the people and property in our care safer than ever while still providing a seamless and non-intrusive customer experience. Our ability to achieve an optimised security posture at a lower total cost than traditional approaches means our dealership can keep security overhead low and invest as much as possible in both the customer experience and making great deals. It’s security as forward-thinking and high performance as our brand.”
Round table discussion
The year ahead holds endless promise for the physical security industry, and much of that future will be determined by which technologies the industry embraces. The menu of possibilities is long – from artificial intelligence to the Internet of Things to the cloud and much more – and each technology trend has the potential to transform the market in its own way. We tapped into the collective expertise of our Expert Panel Roundtable to answer this question: What technology trend will have the biggest impact on the security market in 2019?
The new year 2019 is brimming with possibilities for the physical security industry, but will those possibilities prove to be good news or bad news for our market? Inevitably, it will be a combination of good and bad, but how much good and how bad? We wanted to check the temperature of the industry as it relates to expectations for the new year, so we asked this week’s Expert Panel Roundtable: How optimistic is your outlook for the physical security industry in 2019? Why?
In many regards, 2018 was a turbulent year for the physical security marketplace, driven by evolving technologies and changing customer needs, among other factors. Year-end is a great time to reflect, so we asked our Expert Panel Roundtable: What caused the most disruption in the physical security marketplace in 2018?