A Three-Level Ransomware Detection and Prevention Mechanism

Ren, Amos Lohj Yee; Liang, Chong Tze; Hyug, Im Jun; Broh, Sarfraz Nawaz; Jhanjhi, N. Z.

doi:10.4108/eai.13-7-2018.162691

Cited by 19 publications

(20 citation statements)

References 5 publications

(7 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to machine learning, heuristic-based approaches have also been a focal point of research [17,32,7]. These methods rely on a set of rules or algorithms to detect ransomware based on known behaviors and characteristics, allowing for the identification of ransomware even in the absence of specific malware signatures [33,34,4].…”

Section: Detection and Prevention Methodologiesmentioning

confidence: 99%

Applying Markov Decision Processes to Evaluate Ransomware Data Theft Risks

Zhu,

Li,

Zhang

2023

Preprint

View full text Add to dashboard Cite

Ransomware has rapidly evolved into sophisticated, stealthy threats built to extort payments through data encryption and extraction. This paper presents an innovative methodology for ransomware risk evaluation using the mathematical frameworks of Markov Decision Processes (MDP). By modeling ransomware scenarios as MDPs, overlaying risk equations, and applying our analysis, a quantitative assessment of dynamic risk levels and effectiveness of defensive strategies is enabled. The technique is demonstrated through comparative assessment of prominent ransomware groups, industry-specific impact analysis, and time projections of data theft risk trajectories. Despite limitations in model complexity and real-world validation, the methodology elucidates an interdisciplinary approach blending decision theory, control systems and applied mathematics to enrich cyber risk research.

show abstract

Section: Detection and Prevention Methodologiesmentioning

confidence: 99%

Applying Markov Decision Processes to Evaluate Ransomware Data Theft Risks

Zhu,

Li,

Zhang

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Little to no research has been conducted till now to detect ransomware inside the browser or even have the capability to warn the users. Ren et al [72] designed a three-layer-security solution that in its first stage used a browser extension that could identify malicious websites and also kept track of unauthorized down-loads that occurred through these websites. A major downside of this extension is that it can only block websites that are already residing in a predefined list.…”

Section: Browsers As the First Line On Defensementioning

confidence: 99%

Ransomware Detection, Avoidance, and Mitigation Scheme: A Review and Future Directions

Kapoor¹,

Gupta²,

Gupta

et al. 2021

Sustainability

View full text Add to dashboard Cite

Ransomware attacks have emerged as a major cyber-security threat wherein user data is encrypted upon system infection. Latest Ransomware strands using advanced obfuscation techniques along with offline C2 Server capabilities are hitting Individual users and big corporations alike. This problem has caused business disruption and, of course, financial loss. Since there is no such consolidated framework that can classify, detect and mitigate Ransomware attacks in one go, we are motivated to present Detection Avoidance Mitigation (DAM), a theoretical framework to review and classify techniques, tools, and strategies to detect, avoid and mitigate Ransomware. We have thoroughly investigated different scenarios and compared already existing state of the art review research against ours. The case study of the infamous Djvu Ransomware is incorporated to illustrate the modus-operandi of the latest Ransomware strands, including some suggestions to contain its spread.

show abstract

“…As soon as this pandemic outbreak started, a financial recession was already predicted by the experts. At the same time, the financial industries are vulnerable to cyber threats such as phishing and Malware [14] or ransomware [15] attacks. In addition to this, in a normal situation, the fintech users have mostly become the victim of social engineering, where the hackers use certain tricks to pretend to be the legit person and get access to personal information such as password recovery.…”

Section: ) Financial Servicesmentioning

confidence: 99%

Ten Deadly Cyber Security Threats Amid COVID-19 Pandemic

Khan¹,

Brohi²,

Jhanjhi³

2020

Preprint

View full text Add to dashboard Cite

<p>World Health Organization declared COVID-19 as a pandemic after the breakout in the city of Wuhan, China. The disease has negatively affected the global economy and daily life. Most of the countries around the world have imposed travel restrictions, locked down, and social distancing measures. In the current situation, Information and Communications Technology is playing a significant role in connecting people. Majority of the education organizations have adopted online platforms, students and staff are working from home. Besides, these businesses, e-healthcare systems, food deliveries, and online grocery shopping have witnessed a very high demand. Malicious attackers have considered COVID-19 as an opportunity to launch attacks for financial gains and to promote their evil intents. Healthcare systems are being attacked with ransomware and resources such as patient's records confidentiality, and integrity is being compromised. People are falling prey to phishing attacks through COVID-19 related content. In this research, we have identified the top ten cybersecurity threats that had and could take place during the pandemic. We have also discussed the privacy concerns raised amid COVID-19. <i></i></p>

show abstract

A Three-Level Ransomware Detection and Prevention Mechanism

Cited by 19 publications

References 5 publications

Applying Markov Decision Processes to Evaluate Ransomware Data Theft Risks

Applying Markov Decision Processes to Evaluate Ransomware Data Theft Risks

Ransomware Detection, Avoidance, and Mitigation Scheme: A Review and Future Directions

Ten Deadly Cyber Security Threats Amid COVID-19 Pandemic

Contact Info

Product

Resources

About