ProjectBlog: Where Does Machine Learning Stand in Cyber Security?

Blog: Where Does Machine Learning Stand in Cyber Security?

How far with 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 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 errors, imbalanced data sets, the attacker-defender games, difficulty in identifying malicious sources, the tragedy of metrics, and more.

Access to Datasets

Since one of the key hindrances to investigating cyber-security problems is a lack of appropriate data sets, researchers have provided access to datasets that can enable the academic community to investigate the aforementioned challenges and suggest methods that can help minimize or eliminate them. They also present a methodology to help generate labels via pivoting and in so doing provide a solution to common problems such as lack of labels in cyber-security.

Potential Uses and Effects

Researchers behind are of the idea that the use of ML in cybersecurity should change. They also believe that the cyber community has a duty to help the ML community to become more active in the field. Tell you what? I think so too!

Currently, there’s a lack of enough qualified and experienced cyber security analysts to help minimize the skyrocketing global cyber-attacks. And, there already exists an overabundance of big data that can be used in several algorithms to improve the current state of cybersecurity with ML. Let’s all hope that these research developments will help drive new methods that will boost current state-of-the-art in both ML and cybersecurity.

To gain access to available datasets, you can contact with ‘Access to data request’ as the subject title.

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Source: Artificial Intelligence on Medium

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