In a world of mobile access and Internet of Things devices there is no point trying to protect the perimeter any more.
Traditional ways of looking for existing code signatures in software crossing firewalls or other perimeters also fails because those signatures are changing far faster than ever before.
Even with the most up-to-date signature list there is still the risk of being ‘patient zero’ – malware has to claim one first victim before anyone else can be warned.
Instead businesses are looking for ways to spot behaviour by people or devices which should be raising alarms.
But observing the behaviour of every person and machine on the corporate network is impossible for a human team to do without machine help.
Niara specialises in User and Entity Behavioral Analytics which uses big data and machine learning to protect businesses against ever-evolving attacks.
UEBA combines profiling with intelligent behavioural analytics to spot unusual access to data – or other ‘out-of-the-ordinary’ activity to raise alarms.
Crucially this process is automated and does not rely on human intervention. When the system detects anomalous behaviour it can automatically isolate the user or the device from sensitive data and systems.
This gives security teams the ability to do their jobs without being overwhelmed by growing numbers of devices and false alarms demanding action.
Automation is necessary for two reasons.
Firstly the number and type of attacks continues to grow at an ever faster rate.
Secondly wider use of mobile devices, Internet of Things projects and closer integration with partners’ systems means the average enterprise has an ever growing number of possible vectors for attack.
Automated and intelligent systems give security teams the time to do their jobs effectively without constantly fighting real or imagined fires.
Niara technology will be integrated into HPE’s Aruba Clearpass security portfolio.