Understanding cybersecurity from machine learning POV

Cybersecurity has undergone massive shifts technology-wise, led by data science. The extraction of security incident patterns or insights from cybersecurity data and building data-driven models on it is the key to making a security system automated and intelligent.

Cybersecurity data science is a phenomenon where the data and analytics acquired from relevant cybersecurity sources suit the data-driven patterns that give more effective security solutions. The concept of cybersecurity data science makes the computing process more actionable and intelligent when compared to traditional ones in cybersecurity. Therefore, an ML-based multi-layered framework for cybersecurity modelling is sought after today.

Today, companies depend more on digitalisation and Internet-of-Things (IoT) after various security issues like unauthorised access, malware attack, zero-day attack, data breach, denial of service (DoS), social engineering or phishing surfaced at a significant rate. Cybercrime causes disastrous and sometimes irreversible financial losses that affect both organisations and individuals. A data breach costs $8.19 million in the United States and $3.9 million on an average, according to an IBM report. Meanwhile, the annual cost for the global economy from cybercrime is $400 billion. 

What is cybersecurity data science?

Data science brought about a global change in various industries. However, it has become an important segment for the future of robust cybersecurity systems and services. This comes after cybersecurity has become all about data. For example, while detecting cyber threats, it analyses security data in files, logs, network packets, or other sources. Commonly, security professionals did not use data science to detect cyber threats. Instead, they used file hashes, custom-written rules, and manually defined heuristics.

Although it has its own merits, it requires a lot of manual labour to keep up with the ever-changing threat landscape. On the other hand, data science can change the industry with machine learning algorithms that can be used to extract insights of security event patterns from training data for detection and prevention. It can be used to detect…