6 ways hackers will use machine learning to launch attacks

Machine learning algorithms will improve security solutions, helping human analysts triage threats and close vulnerabilities quicker. But they are also going to help threat actors launch bigger, more complex attacks.

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Defined as the “ability for (computers) to learn without being explicitly programmed,” machine learning is huge news for the information security industry. It’s a technology that potentially can help security analysts with everything from malware and log analysis to possibly identifying and closing vulnerabilities earlier. Perhaps too, it could improve endpoint security, automate repetitive tasks, and even reduce the likelihood of attacks resulting in data exfiltration.

Naturally, this has led to the belief that these intelligent security solutions will spot - and stop - the next WannaCry attack much faster than traditional, legacy tools. “It’s still a nascent field, but it is clearly the way to go in the future. Artificial intelligence and machine learning will dramatically change how security is done,” said Jack Gold, president and principal analyst at J.Gold Associates, when speaking recently to CSO Online.

“With the fast-moving explosion of data and apps, there is really no other way to do security than through the use of automated systems built on AI to analyze the network traffic and user interactions.”

The problem is, hackers know this and are expected to build their own AI and machine learning tools to launch attacks.

How are cyber-criminals using machine learning?

Criminals - increasing organized and offering wide-ranging services on the dark web - are ultimately innovating faster than security defenses can keep up. This is concerning given the untapped potential of technologies like machine and deep learning.

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