It's no secret that enterprise IT networks today face more threats than ever before. Employee demand for enterprise mobility, BYOD and shadow IT are just a few trends that add to the risks and dangers that an enterprise must deal with to maintain the security of its network and its data.
A single employee could create dozens of threats in a single day. They might use a corporately liable smartphone on their commute to the office, and connect to multiple public Wi-Fi networks en route. Once in the office, they might use a laptop on the corporate network, but share files over USB drives and cloud file-sharing platforms – some of which are authorised and some that are not. Finally, in a meeting that afternoon, they might use their own tablets, connected to the network via a VPN over an unsecured Wi-Fi network.
And that's just on one day, and for one employee.
However, the picture is not as bleak as it might initially seem. While the number of endpoints and inappropriate data sharing always needs to be controlled, the way in which each individual engages with the network on their own terms actually creates an opportunity to actually enhance enterprise security – if used correctly.
Security through context
If each employee accesses and engages with the network in their own way, at their own times and on their own combination of devices, then distinct individual usage patterns emerge. If these patterns can be identified, this context becomes its own form of a personal digital fingerprint that can be used to authenticate identity on devices.
Contextual authentication is a major advancement in securing mobile devices – removing the friction between mobility's promise of increased productivity and the reality of having to secure devices with excessive input requests. With contextual analytics and authentication, users only need to provide one factor of authentication, such as a password or fingerprint. Simultaneously, a number of other factors are evaluated in the background based on the device's use versus the context of what has been recently typical (e.g. the device's location, time and manner of use, proximity to other devices etc.).
If no discrepancy is detected, then single factor authentication is sufficient. Only if there is a marked difference between past activity and the current request will a further manual input be required – a requirement that becomes a welcome and reassuring exception rather than a source of recurring frustration.
At a stroke, the broad range of devices and methods available to workers to access a network changes from being a cause for IT concern to become a way to strengthen network security. The wide variation in how workers connect to and use the network itself creates individualised contextual profiles, which can be used to authenticate the user.
Benefits in patterns
This approach to authentication also removes the threat of “watered down” and weak authentication methods. The threat of unauthorised access to the corporate network via obvious or overused passwords falls dramatically if security is entrusted to the mechanical, dispassionate algorithm instead. As usage patterns are discovered and evolve along with an individual's behaviours, the machine-learning algorithm constantly learns and feeds back. This dynamic intelligence in turn protects the enterprise from new threats as they emerge, preventing these risks or threats from penetrating the network.
Moreover, by enabling organisations to identify usage patterns and create risk profiles based on these, enterprises are able to decide how much or how little deviation from their own security policies they will tolerate, ultimately improving security according to need.
A contextual future
The advent of BYOD and employees demanding greater flexibility on where and when they can access the network, together with an increase in the number of mobile devices and other network access points, has made preserving the security of the network in the era of enterprise mobility an uphill struggle.
The typical response to solving the secure mobility conundrum is to add extra authentication factors to strengthen the process. But the addition of context as part of authentication optimises the entire process by recognising when and where multiple authentication needs to be used, and how it needs to be used. It's this that makes the combination of authentication plus context so powerful.
The use of contextual analytics in this way not only makes for a more secure network. It can also be an enabler for boosting wider staff productivity by providing an accurate insight into the working practices of top-performing individuals – what apps and features they use; what devices they use them on; and when and where they use them. This type of granular user data can provide a template for other employees to emulate and follow, for their benefit and the benefit of the organisation they work for.
Contributed by Dave Schuette, EVP & president, Synchronoss Enterprise