Over the past year, companies have had to deal with the COVID-19 pandemic and how it has affected their operations. From new digital services through to security, the response to more hybrid and remote working showed some of the assumptions that we have made over the years, and it required companies to innovate and fill those gaps.

Physical and IT security was no exception to this. In the rush to support home working, many IT security teams realised how much they rely on physical security to help with their identity management approaches. To adapt to what is taking place now, identity management has to evolve too.

Challenging our assumptions around identity management

Identity management involves ensuring that authorised and authenticated individuals can get access to the tools and data they need to work, and restricting access from those that don’t.  Identification is establishing who a user is, and then authentication verifies someone is who they say they are through a combination of different methods or factors linked to who they are, what device they are using, what they know, and what they have.

Physical security provides an identity perimeter by restricting device access to only those that are allowed to enter a location, whether this is through using technology like smart cards or biometrics through to people managing who can enter the building at reception. With this boundary in place, using a combination of username and password is enough to meet security requirements. A more ‘zero trust’ approach is needed where we trust nothing and verify everything 

However, the pandemic took this away. For many IT security teams, this showed how much they had taken physical security for granted in their security planning. Alongside having to provide remote access that is secure, these teams had to think about how to manage identities securely as well. The default approach of username and password is not enough when everyone can be working on any device and from essentially any location. Instead, identity has become the new perimeter.  The new office is wherever a user and device are,  and authentication must change that we can prove people are who they say they are.

A more ‘zero trust’ approach is needed where we trust nothing and verify everything. The mindset behind zero trust security is to regard all sources of network traffic, both external and internal, as potential routes for attacks. Therefore, all users and resources must be verified and authenticated wherever they come from, system data must be collected and analysed for risks, and network access and traffic must be limited and monitored. While it may seem a bit paranoid, zero-trust security is rooted in the realities of the cloud computing age.

Multi-factor authentication or MFA can be used to add more types and factors for authentication. So, in addition to something you know like a password,  you can use something you have as well. This would typically be a one time password sent to the user’s phone or from a mobile authenticator app, which fills the role of something they have. Managing this at any scale requires work. For large companies with established processes and identity management strategies, this would be something they could add on as part of that remote working implementation. However, for many smaller businesses that don’t have established IT directories or that have a wide range of different and new applications in place to support, it is more challenging.

Everything is different

One reason for this is the sheer variety of IT assets, devices, and applications that now have to be supported. Rather than the IT-designed network of machines that is standardised and fully controlled, we today have a far wider range of devices, operating systems and locations in play. Alongside this, there is the issue of controlling access to cloud-based services and Software-as-a-Service (SaaS) applications, which have also grown in popularity.

The traditional IT directory that is normally used as the starting point for identity management is not normally equipped to manage the modern identity landscape. Looking at cloud-based directories is therefore a worthwhile step, as these are built to manage Identities, SaaS applications and VPNs and also support both multiple operating systems and the wide range of different devices that today’s users have.

From a physical security perspective, identity and access management can be an area to develop. While the need for building access is reduced at the moment, it will return when the pandemic ends. In these circumstances, new approaches may also be needed. For example, fingerprint biometric security processes are popular to fill the requirement around verifying that someone is who they say they are. However, traditional approaches like fingerprint scanners may be less popular as they require users to touch the readers. For high traffic locations with lots of people, that will be a risk.

Instead, combining access and identity can be made easier through approaches that take advantage of the new flexibility that pandemic responses needed. For example, using the physical access control support in today’s smartphones can enable organisations to use biometric fingerprint readers or face recognition without having to enforce everyone using the same biometric reader. By linking to phone applications that employees have on their devices, fingerprints or other forms of biometric data can be used to grant access.

Thinking about context

Looking into the future, many of us are looking forward to things going back to the way that they were before the pandemic. However, there are a lot of things that we had to adapt and use to keep operations running and secure during lockdown that we should continue to make use of. Rather than simply going back, we should look ahead at a more hybrid approach to everything, including security.

This includes looking at context for identity and access management. Rather than simple approaches that are either too insecure or overkill for employees, we can set out situations that match the most common working situations and then enforce some rules on when access is granted. For this, we can look at how to use authentication and access control more effectively alongside other security factors. As we move to a more hybrid way of working, this flexibility of approach will be necessary to cope with all the different scenarios that employees will be in

The first element here is the devices that users have. Trusted devices can be their own factor for authentication, where a device trust can be set up with a specific user account and linked to a specific device like a PC, laptop or tablet. If the user is not using one of those devices, then they can have an additional factor for authentication used, such as entering a one-time password from their phone or a mobile push authentication. This approach does not restrict users that may need to work from other devices occasionally, but it does protect against theft of passwords or dictionary attacks on credentials.

The second element is location. When users connect, they will use an IP address that connects them to a network either in the office, to their home provider, or to a public network. Depending on the circumstances, you can put rules in place on how you manage those connections. For a user that is in the office, they may get access automatically in the same way they used to. 

With conditional access based on geolocation, user access can be allowed or blocked based on a user’s physical location or challenged with a step-up authentication. For example, your business may be based in the UK and with offices in Europe. Getting an access request from India or China may not be legitimate, so IP addresses from those countries can be automatically blocked. Alternatively, if you do have staff that will travel to those countries, then access can be dependent on using a known device and authentication step before signing in.

The approach here is to use conditional access based on identity, location, and device and make access as simple as possible for the user and without causing excess risk to the organisation. By looking at specific circumstances and context, you can design your access management approach to fit the user. As we move to a more hybrid way of working, this flexibility of approach will be necessary to cope with all the different scenarios that employees will be in.

Share with LinkedIn Share with Twitter Share with Facebook Share with Facebook
Download PDF version Download PDF version

Author profile

Neil Riva Principal Product Manager, JumpCloud

Neil Riva is a Principal Product Manager at JumpCloud focusing on identity & authentication. Award-winning product leader with extensive experience creating a diverse portfolio of identity & access management, authentication, & cybersecurity products. Former Director of Product Management at HID Global IAM, Crossmatch Inc & DigitalPersona. With 20+ years of experience, Neil has led & developed products in the authentication, biometric, network management, security & artificial intelligence areas. He was the CTO of noHold Inc. designing & developing a patented Artificial Intelligence cloud-based technology to improve enterprise services. Neil’s graduate school practicum project was conducted at IBM Scientific Research Laboratory focusing on artificial intelligence and expert systems used for Information Management.

In case you missed it

The future of accommodation: when coliving and PropTech combine
The future of accommodation: when coliving and PropTech combine

As technology develops at an ever-faster rate, the possibilities for where and how new innovations can be used are endless. The property sector is one such area where new technology, such as smarter video surveillance, is being used to improve the quality of life for families and communities by increasing security as well as implementing changes based on new insights. Specifically for the coliving movement, cloud-based video surveillance is helping operators to improve the communal spaces for their tenants in ways that on-premises surveillance never could. From tighter security measures to better social spaces, here’s how coliving is benefitting from the PropTech (property technology) boom. What is coliving? The coliving movement is the latest iteration of a recurring human trend. The act of communally sharing space and resources while benefiting from a supportive community is something we’ve seen time and again throughout history. A place that everyone can call home addresses multiple needs. With the concept of shared spaces, and the possibility to work and socialise together, it’s no longer simply a trend. Specifically for the coliving movement, cloud-based video surveillance is helping operators to improve the communal spaces for their tenants in ways that on-premises surveillance never could. As living expenses become ever higher, for many – particularly younger – people getting on the property ladder is difficult, and renting an apartment alone can feel isolating. Coliving spaces offer a ready-built community, and many responsibilities – like maintenance, for example – lie with the building owners, and the cost is included. Where does PropTech come in? PropTech is dramatically changing the way people research, rent, buy, sell and manage property. The combination of the internet, huge compute power, cloud platforms and artificial intelligence (AI) have all combined to create technologies that are transforming the way the entire property sector works. Whether that’s helping buildings to operate more efficiently or even become more sustainable, PropTech is a sector that’s on the rise. When it comes to coliving, PropTech is helping to make these environments safer and smarter for the people who live there. One of the fundamental areas of building design is people’s safety. Following the past year where health has been at the forefront of everyone’s minds, PropTech is enabling entrance systems with touchless doorways and innovative ventilation systems, for example. And even without taking the pandemic into consideration, people living in shared spaces need to be confident that the security is well-managed, and the management wants to ensure that only tenants and their guests can enter the premises. How cloud video surveillance drives better coliving Once seen as an ‘add-on’ to building design, video surveillance and access control are now becoming increasingly important elements of the PropTech movement, and they are equally as desirable for coliving too. Surveillance cameras are essentially sensors that can monitor activity, patterns, and any other changes in a given environment. Analysis of video data can occur in real-time to effect changes immediately, or video can be stored and evaluated at a later date. In a coliving environment, a cloud-based video surveillance system can help operators to understand how tenants use their space, and implement changes to benefit them. Traditionally, video surveillance data stored on-premises had limited uses, as it was often only accessed after a security incident, such as a break-in. The video therefore wouldn’t be used frequently and the camera and storage system would just be another cost not yielding any ROI. Cloud technology has had a dramatic impact on video surveillance. Remote management delivers the ability to modify, adjust and perfect the system without needing to be present at the site, while remote monitoring alerts operators to any unusual incidents such as an equipment malfunction or breakage. In a coliving environment, a cloud-based video surveillance system can help operators to understand how tenants use their space, and implement changes to benefit them. For example, surveillance can show operators which areas in the communal spaces are frequented the most and at what times, including areas such as the laundry room or gym where space might be limited. By using AI to analyse the video, operators can use insights from it to improve the existing set up wherever possible, and also learn lessons about how to better design future co-living spaces. In today’s world, this technology can also help to keep everyone safe and healthy. Cameras can identify if someone is wearing a face mask as they go to enter a building and deny entry until they put one on. Thermal cameras are another easy tool to screen people for an elevated temperature before they even enter a communal space. Though a raised temperature does not mean you have COVID-19, the technology can provide an initial screening, so that individuals with elevated temperature readings can be checked manually for other symptoms or possibly be recommended for a test. The future of smart living Coliving is not a new phenomenon – humans have been living in communal places for many years, working and socialising together for the benefit of everyone. What makes today’s coliving movement unique is the range of rapidly developing technology that is being implemented to improve the environments for tenants. As an arguably lower cost and higher quality way of life, coliving spaces are certainly here to stay, and so the PropTech surge is no doubt going to grow with it.

How AI is revolutionising fraud detection
How AI is revolutionising fraud detection

The Annual Fraud Indicator estimates that fraud costs the United Kingdom approximately £190 billion every year. The private sector is hit the hardest and loses around £140 billion a year, while the public sector loses more than £40 billion, and individuals lose roughly £7 billion. The effects of fraud can be devastating on both individuals and organisations. Companies can suffer irreversible damage to reputation and be forced to close, and individuals can experience significant personal losses. Everyone should be aware of the risks and take steps to protect themselves against fraudulent activity. Fraud detection technology Fraud detection technology has advanced rapidly, over the years and made it easier for security professionals to detect and prevent fraud. Here are some of the key ways that Artificial Intelligence (AI) is revolutionising fraud detection - with insight from Tessema Tesfachew, the Head of Product at Avora. An anomaly can be described as a behaviour that deviates from the expected An anomaly can be described as a behaviour that deviates from the expected. According to Tessema Tesfachew, “Autonomous monitoring and anomaly detection specifically, have made detecting fraudulent activity faster and more accurate. Machines can monitor data 24/7 as it comes in, build patterns of behaviour that take into account seasonality and shifting trends, and identify events that don’t fit the norm.” For example, banks can use AI software to gain an overview of a customer’s spending habits online. Having this level of insight allows an anomaly detection system to determine whether a transaction is normal or not. Suspicious transactions can be flagged for further investigation and verified by the customer. If the transaction is not fraudulent, then the information can be put into the anomaly detection system to learn more about the customer’s spending behaviour online. Accurate root cause analysis Root cause analysis goes one step further than anomaly detection, by allowing security professionals to pinpoint what caused the anomaly. Tessema explains how an example of this would be if a system detects that the rate of fraudulent transactions has increased. Root cause analysis would pinpoint the specific ATM or point of sale, where this increase is occurring. Swift action can then be taken to prevent fraudulent activity at that location in the future. Fewer false positives As mentioned, false positives can occur if a fraud detection system identifies behaviour that goes against the norm, for instance, if a customer makes a transaction in a new location. In many cases, customers are required to complete identity verification to prove that a transaction is not fraudulent. Digital customer identity verification can help brands build a strong and reputable image. That said, forcing users to complete identify certifications regularly can cause frustration and harm the customer experience. AI anomaly detection AI fraud detection systems can carry out accurate data analysis in milliseconds and identify complex patterns in data AI anomaly detection is far more accurate and results in fewer false positives. Increasing the accuracy of anomaly detection helps companies improve customer relationships and build a strong reputation. This will have a positive impact on brand image and sales revenue. AI fraud detection systems can carry out accurate data analysis in milliseconds and identify complex patterns in data. Machines are more efficient than even the most skilled fraud analysts and make fewer errors. This is why AI fraud detection software is the preferred option in larger organisations. Importance of fraud analysts However, fraud analysts still play an important role in fraud prevention. Using a combination of human intervention and AI is usually the most effective approach when it comes to fraud detection. According to pymnts.com, innovative organisations now use a variety of AI and supervised and unsupervised machine learning to identify and protect against fraud. AI systems can complete time-consuming and repetitive tasks, such as data collection and analysis. This means that fraud analysts can focus their time and attention on critical tasks that require human intervention, e.g. monitoring risk scores. AI can automate processes and enhance the quality of the fraud analysts’ work. Conclusion In to Tessema Tesfachew’s opinion, “Fraud detection has become vastly more efficient and effective with the introduction of Artificial Intelligence (AI). Previously, methods for detecting fraudulent activities were still data-rich, but relied more on human intervention and expert bias, and were thus, more time consuming and prone to error.” AI technology, particular anomaly detection, has streamlined fraud detection and created a more efficient, and accurate system for detecting and preventing fraud. Covid-19 has increased the number of online transactions, which creates more opportunities for fraudulent activity. However, it also allows businesses to gain more information on their customers and enhance the capabilities of AI security software. It is more important than ever for organisations to utilise AI technology in fraud detection strategies.

What new technologies and trends will shape video analytics?
What new technologies and trends will shape video analytics?

The topic of video analytics has been talked and written about for decades, and yet is still one of the cutting-edge themes in the physical security industry. Some say yesterday’s analytics systems tended to overpromise and underdeliver, and there are still some skeptics. However, newer technologies such as artificial intelligence (AI) are reinvigorating the sector and enabling it to finally live up to its promise. We asked this week’s Expert Panel Roundtable: What new technologies and trends will shape video analytics in 2021?