Ransomware threat mitigation through network traffic analysis and machine learning techniques

In recent years, there has been a noticeable increase in cyberattacks using ransomware. Attackers use this malicious software to break into networks and harm computer systems. This has caused significant and lasting damage to various organizations, including government, private companies, and regular users. These attacks often lead to the loss or exposure of sensitive information, disruptions in normal operations, and persistent vulnerabilities. This paper focuses on a method for recognizing and identifying ransomware in computer networks. The approach relies on …

analysis attackers attacks companies computer cs.cr cs.lg cyberattacks government harm machine machine learning malicious malicious software mitigation network networks network traffic network traffic analysis organizations private ransomware regular software systems techniques threat threat mitigation traffic traffic analysis