Big Data Analytics for Cyber Security

Considering the dynamic nature of the security domain, big data analytics can play a major role in areas such as malware detection, intrusion detection, multi-factor authentication, etc. Most organizations today tend to over-compensate with techniques such as multi-factor authentication to protect themselves and their customers. Security almost always trades-off usability. If not moreso, usability is almost as important as security for some verticals like ecommerce. For an ecommerce site each extra step or extra second required to complete a transaction will negatively impact revenue. Big data and machine learning techniques can be employed to assess risk by collecting and analyzing various contributing factors such as IP address, device type, device location, browser, MAC address, ISP, user history, etc. Only if the risk is high will additional security measures be enforced. This way, usability will be impacted only for a few transactions that are deemed risky. This article documents and discusses such examples where big data analytics techniques can be used to tackle some of the difficult security challenges like Advanced Persistent Threat (APT), big ticket breaches plaguing both private and public sectors today.