Artificial Intelligence and Cyber Security

If you look into the trend of cyber attacks in recent years, it has increased drastically resulting in massive disruptive effects like interrupting commerce, shutting down hospitals and airports, and holding people and organizations ransom for their data. The bitter truth is what adversary has done to our privacy and the fear they keep us in. We never know when they will use their evil prowess to destroy us. This is the evil reality, and to combat and fight against such attacks we need expert machines that can help our security professionals.

Daily we see the cyber battle against organized crime, terrorists, thieves, etc. There are criminal enterprises who prey on our businesses and lives by exploiting people around the world. Cybersecurity is the only defense against these challenges. However, a perfect defense is not possible to create and the preventative measure will not always work as adversarial techniques evolve each day. Thus, a correct detective mechanism is required and significant assistance is needed to make security professionals more efficient and expand their intelligence. AI has come to help.

Artificial Intelligence (AI) is the ability of machines to perform tasks that would require intelligence if performed by humans. Its primary goal is to provide answers from massive archives of data. Smart machines are good at analyzing data using pattern recognition. Pattern recognition is a branch of machine learning and uses supervised and/or unsupervised learning methods to find patterns in data. Supervised learning allows for training of AI using labeled/classified data while unsupervised learning uses unlabeled/unclassified data. Deep learning is a branch of AI and an unsupervised machine learning that uses neural network and emulates human brains. It learns, collects information (data mining), and understands patterns.

Cybersecurity professionals use analytics to detect anomalies in network patterns, network traffic, and normal user activities. Exploits are identified by their signatures which works well with known patterns of attack. However, in the real world, there are many unknowns than knowns. So, cybersecurity has moved on from a signature based detection to behavioral based where each entity is scored based on their network's activities. This is called predictive analysis.

One of the goals of using AI in cybersecurity is to reduce out false positives. Computers, on their own, even really smart ones, fall prey to the false positive. But, using the insights of a computer in partnership with a human in a type of hybrid approach lowers the risk that non-malicious network use will be seen as a false positive. Because the AI is always learning, it can also learn from its human partner. The security researcher examines the alerts provided by the smart security system and determines which are and aren’t false positives. Those results are fed back to the AI, making it smarter. In time, the AI will report fewer false positives. 

In conclusion, artificial intelligence (AI) applied to cybersecurity provides security professionals with an augmented ability to protect endpoints, data, and networks. It provides insight to quickly and cost-effectively stop intrusions or even prevent them before they happen.