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.

For business executives and internal information security specialists, it seems that every day brings a new potential risk to the company – and in the current threat environment, it isn’t hard to understand this viewpoint.

Sophisticated cybercriminals are continually on the lookout for the next big hacking strategy, and aren’t shy about trying out new approaches to breach targets and infiltrate enterprises’ IT assets and sensitive data. One of the best ways to stem the rising tide of threats in this type of landscape is to boost awareness and increase knowledge about the latest risks and how to guard against them.

Currently, an emerging strategy among hackers 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.

How are cyber-criminals using machine learning?

1. Increasingly evasive malware

2. Smart botnets for scalable attacks

3. Advanced spear phishing emails get smarter

4. Threat intelligence goes haywire

5. Unauthorized access

So how do hackers use machine learning to bypass the system and carry out malware or DDoS attacks?

Machine Learning For Gathering Information: The use of AI has become more widespread with hackers launching noise generation attacks to weaken the automated defense systems. The first step is gathering information and getting unauthorized access by knowing common security exploits. The more information is collected, the better the chances are of success. That is why hackers collect large amounts of data to improve social engineering techniques.

Conducting Personalised Attacks: According to a report by Information Age, hackers are using ML and AI capabilities to launch personalized attacks and are tailoring the malware according to each victim. McAfee 2018 Threat Predictions report indicates that the development in machine learning is going to turn into an arms race between the defenders and attackers since cybercriminals are also leveraging ML techniques to lower the defense of organizations.

Developers Are Developing Malware: With more and more developers developing sophisticated malware that can escape detection, even the best AI tools are failing due to the lack of maturity or precision of machine learning software. Most companies invest in expensive malware detection software but they are not selecting the right tool. Sometimes, the IT workers do not have the right tools to protect endpoints and keep the network safe. According to the HP report, hackers are essentially technicians who believe in improvising their craft with machine learning and incorporating new tools.

ways hackers will use machine learning to launch attacks