Machine Learning Provides Many Benefits… But It Also Has Many Risks.
Cybersecurity and artificial intelligence (AI) were seen as separate innovations in technology. Today, cybersecurity and artificial intelligence go hand in hand as experts use machine learning to develop advanced security methods. But cybercriminals also use machine learning and innovate faster than security experts can keep up.
Cybercriminals have developed attacks that enable machine learning and are starting to use them against businesses. This has significant implications for entire industries as attacks become more sophisticated and ultimately more successful.
What Are Machine Learning Active Attacks?
Machine learning refers to the ability of computers to learn, adapt, and respond without being specifically programmed to perform specific tasks. Machine learning-enabled attacks occur when cybercriminals use this artificial intelligence technology to carry out a cyberattack.
How to use machine learning in cyber attacks;
Vulnerability discovery—finding a weakness in the targeted network.
First exploit – exploiting the vulnerability to gain access to the network.
Targeted exploit—finding and exploiting vulnerabilities within the network.
Data theft—the removal of sensitive or valuable data from the network.
Password brute force-machine learning is used on social media etc to give the attacker shorter password lists. uses it to search.
Evade malware – the attacker uses machine learning-based malware that hides from antiviruses and other security programs.
Advanced phishing attackers can use machine learning to find your boss or family relatives and use this information in more advanced phishing attacks.
These are the most used types of attacks with machine learning, we will definitely see more advanced ones in the near future.