Today’s digital data thieves are able to gain access to confidential business and customer data through an ever-increasing number of creative hacking schemes and one of them is the use of machine learning. Unfortunately, like many advanced and innovative technological processes, machine learning can be leveraged for both beneficial enterprise purposes as well as malicious activity.

Machine learning (ML) is an offshoot of artificial intelligence (AI), and is based on the ability to build automated analytical models. In other words, ML enables systems to increase their own knowledge and adapt their processes and activities according to their ongoing use and experience. Individuals have likely encountered some form of ML-algorithm in their daily life already – things like online recommendations from streaming services and retailers, as well as automated fraud detection represent ML-usecases already in place in the real world.

However, as legitimate agencies and white hat security professionals continue to dig deeper into advantageous ML-capabilities, hackers are increasingly looking toward AI-based processes to boost the effects of cyberattacks.

When hackers create malware, they don’t just look to breach a business – they also often want to remain within victims’ systems for as long as possible. One of the first, and likely most dangerous, ways ML will be leveraged by hackers is to fly under the radar of security systems aimed at identifying and blocking cybercriminal activity.

Security experts also predicted that ML could be utilized by cybercriminals to modify the code of new malware samples based on the ways in which security systems detect older infections. In this way, hackers will leverage ML to create smarter malware that could potentially fly under the radar within infected systems for longer periods of time.

This will require enterprises to be increasingly proactive with their security posture – monitoring of critical IT systems and assets must take place continually, and security officers must ensure that users are observing best protection practices in their daily access and network activities.

People stopped being friends with one of the most emerging technologies in these years. It’s not a surprise, though.

29 April 2018