A Survey of Crypto Ransomware Attack Detection Methodologies: An Evolving Outlook

Area of Science:

• Cybersecurity
• Computer Science
• Information Security

Background:

• Ransomware attacks are a major global threat, particularly targeting critical cyber-physical systems.
• Existing crypto ransomware early detection models rely on runtime data but are often circumvented by evasive attack mechanisms.
• There is a critical need to enhance current security defenses to counter the evolving momentum of ransomware attacks.

Purpose of the Study:

• To survey and analyze the state-of-the-art in ransomware attack detection.
• To facilitate the research community in developing effective strategies against ransomware.
• To focus on crypto ransomware due to its prevalence and destructive nature.

Main Methods:

• Reviewing existing literature on ransomware detection models.
• Analyzing the effectiveness of current approaches against evasive ransomware tactics.
• Identifying open issues and challenges in ransomware detection modeling.

Main Results:

• Current detection models face challenges due to sophisticated evasion techniques employed by ransomware.
• A significant gap exists between the capabilities of existing defenses and the evolving nature of ransomware attacks.
• The survey provides a comprehensive overview of current research and its limitations.

Conclusions:

• Further research is essential to develop next-generation ransomware detection systems.
• Future efforts should focus on adaptive and more robust detection mechanisms.
• Recommendations are established for future research directions to address the escalating ransomware problem.