Behavioural analysis uses machine learning, artificial intelligence, big data, and analytics to recognize malicious behavior by examining differences in everyday activities. Behavioural analysis is an extremely important tool when it comes to fending off cyber-attacks.
We all are aware that cyber-attacks have evolved at a rapid rate over the years and the rate has further been accelerated due to the pandemic as most of the workforce and companies have adopted the online platform as a new norm for executing their day-to-day activities.
One thing is common for all malicious activities- they behave differently as compared to normal behaviour and hence leave different signatures which would normally allow companies to identify and terminate them. However, sophisticated cyber-attacks become harder to identify due to the new tactics and techniques cyber attackers use.
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But now with the help of large volumes of unfiltered endpoint data, security personnel can now use behavioural-based tools, algorithms, and machine learning to discover what the normal behaviour of everyday users is and help distinguish it from the bad actors.
Behavioural analysis help recognise trends, patterns and events that are different from everyday norms. To put it better into perspective, consider this scenario: how do we find a needle in a haystack? It’s simple, you bring a magnet. Behavioural analysis is the “magnet” which can be used to find the threats and malware i.e., “needle” in a “haystack” of genuine traffic.
By using this tool security teams can attain visibility and recognise unexpected behavioural tactics of attackers in the early stages and save millions of dollars perhaps which could have been the cost of the cyber-attacks. Behavioural analysis can also help reveal root elements and present insights for future identification and foresight of similar attacks.
One must note that most behavioural analysis systems come with a pre-decided standard set of policies and some systems can be toggled and customized at the discretion of the user.
How behavioural analysis is changing the WAF environment?
As established before, threats are continuously evolving and so our countermeasures should evolve as well. The most advanced perimeter threats for data loss or exfiltration occur at the application layer.
A few points from the current scenarios of threats:
- DDoS attacks may or may not be volumetric in nature.
- Attacks are getting more and more automated in nature. DDoS attacks have become fully automated and all execution at over 1Tbps speed. Automation has become even harder to detect as it is specifically designed to masquerade as genuine traffic and evade. Usage of CAPTCHA is considered a way to combat these however they have been rendered less effective over time.
- Malware is used to exploit weaknesses in browsers and the users operating those browsers. Malware has multiple methods of delivery such as infected ads, links, attachments.
All this information helps one understand why behavioural analysis has become the need of the hour. Basically, most of these attacks may bypass traditional WAF detection mechanisms as they are specifically designed and traditional WAFs are “outgunned” as they say. This is further worsened by almost unlimited supplies of compromised devices or websites.
In order to combat all these malicious activities, WAF vendors like F5 and Prophaze are now offering top of line Behavioural analysis as a part of their WAF features.
To top it all off, behavioural analysis is complemented by the cloud and usage of its extreme computational powers, scalability and efficiency of management. The cloud provides a way that combines big data with powerful analytics to help beat even the most sophisticated attacks.
Vendors also offer cloud-based WAF coupled with behavioural analysis which makes streaming analytics possible. This has further paved the way for monitoring and comparing all activities to any unfiltered historical endpoint data.
Behavioural analysis is a must for any company that has critical data or important online assets to protect. Behavioural analysis will definitely augment the current defence system the company has in place for cybersecurity and will enable IT teams to handle sophisticated attacks thrown their way.
Some behaviour-security products are sophisticated enough to apply machine learning algorithms to data streams so that security analysts don’t need to identify what comprises normal behaviour.
Other products include behavioural biometrics features that are capable of mapping specific behaviour, such as typing patterns, to specific user behaviour. Most products have sophisticated correlation engines to minimize the number of alerts and false positives.
One more point I would like to add is that signature-based tools help identify and fend off known threats whereas behavioural analysis help mitigate zero-day attacks as well which mean attacks that haven’t been registered yet.
In conclusion behavioural based analysis is a tool that your company most probably will not go wrong in employing for cybersecurity measures. In fact, there are malwares such as fileless malware which can only be identified by behavioural technology
