Behavioral analytics, or user behavioral analytics, is a very hyped and hot research topic nowadays in cybersecurity, but it is not all that new. Throughout history, behavioral analytics has been used as part of the programming of different software and applications related to user security.
How does user behavior analytics work?
For instance, many anti-viruses and firewall solutions analyze the behaviors of IP addresses, and if an IP address shows suspicious or unusual behavior, the firewalls automatically block the IP address as a security defense measure. Similarly, anti-viruses regularly keep checking the files and settings of a users’ system for any malicious or unusual attempts or activities performed by a file or program and automatically quarantines such files that show any remote signs of virus infections.
However, recent developments have required the professionals to go beyond the use of behavioral analytics in firewalls and anti-virus software and extend the applications of this technology to further aid in cybersecurity defense measures. Nowadays cybersecurity professionals use behavioral analytics to analyze and study a range of operations including monitoring the aspects of human behavior including apps launched, network activity, and, most critically, files accessed (when the file or email was touched, who touched it, what was done with it, and how frequently).
This type of intelligent technology can defend against all types of hackers including ethical hackers because behavioral analytics technology continuously monitors the patterns of the usage of the user, and in case any unsafe activity, by even a user or a hacker, the technology can immediately block the related processes and also provide notification warnings that unusual activities are being detected. Even when a pentester is testing a system with stealth, the background monitoring of behavioral analytics will quickly identify this behavior as an attempt to breach the network and will block the related process resulting in preventing any type of attack.
This technology, however, has its limitations because human error plays a crucial role in evaluating the efficiency of behavioral analytics. Due to human nature, a user can mistakenly open a malicious file from any link or fall victim to cyber-crooks through phishing, social engineering, or can simply download and open viruses from malicious websites. The learning patterns of behavioral analytics can get complicated and even fail to learn the reasons why a user will open such malicious files.
Undetectable Malware and Attack Vectors
Some hackers have advanced skills and can get into target systems and computers with a high level of stealth and raising any suspicious activity. Then what will the behavioral analytics technology do if it cannot even identify the suspicious behavior? Because a hacker can mimic the normal behavior of the normal user and still even compromise the user’s data/information. Behavior analytics can only work if it detects suspicious activities, but hackers can use different attack vectors to fool behavior analytics. For instance, if a user is connected to an open or public Wi–Fi, then a hacker can also connect to this Wi-Fi and inject specifically coded malware using SQL-injections, phishing, or even can spread spyware into all the devices that are connected to this public Wi-Fi.
Development of Behavior Analytics in Cybersecurity
There has been a lot of work on behavior analytics solutions development relating to the improvement of cybersecurity defense measures for the last couple of years. Big establishments like Target, Netflix, and Amazon are using behavior analytics actively. The reason being that cybercriminals have developed their skills and can cause devastating damages from attacks like advanced social engineering that can break the security of traditional security mechanisms. The hackers nowadays use very sophisticated malware that is brilliantly programmed by expert coders that bypass most security systems without being detected as malware. The need for intelligent behavior analytics is increasing rapidly because its solutions have the capability of analyzing the data and behaviors to find undetected malware and malicious programs that were not identified by the other security defense measures like anti-virus solutions and firewalls. But the development of a behavior analytics solution that is both intelligent and efficient can be a challenge. A well-designed cybersecurity behavior analytics solution must respect three major components:
- It must be user-centric: it must be custom-built to answer complex, user-centric queries
- It must be real-time: ingested data should be available to query almost instantly
- It must be scalable: it needs to effortlessly scale to meet customers’ needs
Cybersecurity is quickly becoming a priority across industries, from automotive to finance to healthcare and beyond. Enterprises are seeking technologies and tactics to safeguard their interests from advanced and persistent threats. As the number of accidents and malicious attacks rises, the need for better cybersecurity only becomes more apparent.
However, despite the advent of novel security technologies and bigger cybersecurity budgets, enterprises with critical digital assets are still at great risk. Understanding the trends and technologies driving the future of cybersecurity is more important than ever, and behavioral analytics solutions will be playing an ever-increasing role in each organization’s security landscape.
Becoming a Certified Ethical Hacker (CEH) would put you on the front lines of being able to develop and implement much–needed cybersecurity solutions such as behavioral analytics. You would learn all the techniques and tools which hackers use to compromise systems, then use the same tools and techniques against the bad guys to help protect your clients.