Where Does Machine Learning Stand in Cyber Security?

What Really is the State of ML in Cybersecurity?

Cyber-security is a critical area in which machine learning(ML) is increasingly becoming significant. But ML in cyber-security extends far beyond merely applying established algorithms to cyber entities.

The ML community may be unaware, but cyber-security with ML has long-standing challenges that require methodological and theoretical handling. According to recently published research work, some scholars have presented the existing cyber-security problems and provided the AI and deep learning community with related datasets to help dive deeper into ML applications in cybersecurity.

Machine Learning in Cyber-Security — Problems, Challenges, and Data Sets

One of the significant challenges that researchers and the entire ML community need to deal with if they are going to apply ML in cybersecurity successfully is malware classification and detection.

It is not easy to identify malicious programs as attackers use complicated techniques such as polymorphism, impersonation, compression, and obfuscation to evade detection. Other challenges include limited domain experts which lead to lack of labeled samples and numerous labeling…