When Cryptographic Ransomware Poses Cyber Threats: Ethical Challenges and Proposed Safeguards for Cybersecurity Researchers

Botes, Marietjie; Lenzini, Gabriele

doi:10.1109/eurospw55150.2022.00067

Cited by 7 publications

(8 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Instead, a more recent work [10] provides a more comprehensive set of important ethics issues in this domain. We gathered risks from literature, especially [3], [10], and summarize such issues, together with their explanations and related principles, in Table I. Main organizing structure is the little 'scenarios' that researchers might encounter in their work and can easily relate to, while for each we provide short explanation, and link to the main underlying ethics principles.…”

Section: Ethics Principles and Values In Cybersecuritymentioning

confidence: 99%

See 1 more Smart Citation

Operationalizing Cybersecurity Research Ethics Review: From Principles and Guidelines to Practice

Reidsma¹,

Ham²,

Continella³

2023

Proceedings of the 2nd International Workshop on Binary Analysis Research

View full text Add to dashboard Cite

Cybersecurity research involves ethics risks such as accidental privacy breaches, corruption of production services, and discovery of weaknesses in networked systems. Although literature describes these and other issues in some depth, reflection on these issues is not yet well embedded in typical Ethics Review Board procedures. In this paper, we operationalize existing guidance on cybersecurity research ethics into a proposal that can be directly implemented in an Ethics Review Board. We provide a set of self-assessment questions to effectively and efficiently probe the ethics of proposed cybersecurity research, a Coordinated Vulnerability Disclosure procedure for discoveries made in the course of research, and an outline of a university policy to institutionally embed this procedure, which could be adapted and adopted by research institutes. With this paper, we hope to contribute to more Ethics Review Boards taking up the challenge of addressing cybersecurity research ethics in an adequate and productive manner.

show abstract

Section: Ethics Principles and Values In Cybersecuritymentioning

confidence: 99%

“…RISKS IN CYBERSECURITY RESEARCH, MOSTLY DERIVED FROM[10] EXCEPT R4 AND R9 WHICH WERE TAKEN FROM[3]. EACH RISK IS EXPLAINED THROUGH A LITTLE SCENARIO-LIKE DESCRIPTION THAT A RESEARCHER CAN EASILY RELATE TO THEIR DAY-TO-DAY RESEARCH PRACTICE, AS WELL AS CONNECTED TO THE LARGER UNDERLYING ETHICS PRINCIPLES.…”

mentioning

confidence: 99%

Operationalizing Cybersecurity Research Ethics Review: From Principles and Guidelines to Practice

Reidsma¹,

Ham²,

Continella³

2023

Proceedings of the 2nd International Workshop on Binary Analysis Research

View full text Add to dashboard Cite

show abstract

“…The significance of this development cannot be overstated, given the increasing complexity of ransomware attacks that are now frequently utilizing advanced encryption and concealment techniques [5], Fig. 4: Grayscale images of memory dumps from ransomware and benignware [50]. The high levels of accuracy obtained in differentiating ransomware from benign software have revealed the strong potential of this integrative method to bolster cybersecurity defenses [9], [4].…”

Section: A Advancements In Ransomware Detection Techniquesmentioning

confidence: 99%

“…From an ethical perspective, the use of sophisticated AI models like LLaMA-7B in cybersecurity warrants careful consideration. The power of these models in detecting and analyzing ransomware brings forth questions regarding data privacy, the security of the AI systems themselves, and the possibility of their misuse [50], [52], [53]. The ethical deployment of AI in cybersecurity necessitates strict adherence to responsible AI practices, including the assurance of data privacy and the fortification of AI systems against potential exploitation [53].…”

Section: A Advancements In Ransomware Detection Techniquesmentioning

confidence: 99%

Entropy and Memory Forensics in Ransomware Analysis: Utilizing LLaMA-7B for Advanced Pattern Recognition

Zhang,

Li,

Zhu

2023

Preprint

View full text Add to dashboard Cite

<p>This study investigated the utilization of memory forensics and the Large Language Model LLaMA-7B for the purpose of detecting and analyzing contemporary ransomware. It articulates a shift from traditional encryption-focused ransomware attacks to more sophisticated strategies, like data exfiltration, underscoring the evolving nature of these cyber threats. The methodology involves an integrated approach, combining memory forensic techniques with the advanced pattern recognition capabilities of LLaMA-7B, to identify and analyze ransomware signatures within system memory. The results demonstrate the efficacy of this combination in accurately distinguishing between ransomware and benign software, with a particular focus on identifying data exfiltration activities. Discussions revolve around the challenges of keeping pace with the evolving ransomware tactics and the ethical considerations in applying AI in cybersecurity. The study concludes by underscoring the importance of continuous innovation in cybersecurity strategies and the potential of AI integration in developing dynamic defense mechanisms against ransomware.</p>

show abstract

“…In the realm of ransom message analysis, researchers have worked to dissect the language and psychological tactics employed by attackers to coerce victims into paying ransoms [6], [10], [32]. Moreover, tracing the flow of bitcoin payments associated with ransomware attacks has garnered attention, as it offers a potential avenue for identifying attackers and understanding their financial networks [33], [34], [35]. However, the actual negotiation process between ransomware victims and attackers, which is a common practice in the industry (Figure 1), has not received the same level of academic focus [36], [37], [33].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Large Language Models in Ransomware Negotiation: A Comparative Analysis of ChatGPT and Claude

Kumamoto,

Yoshida,

Fujima

2023

Preprint

View full text Add to dashboard Cite

This study presents a comprehensive analysis of the application of Large Language Models (LLMs), specifically ChatGPT and Claude, in the context of ransomware negotiation. Ransomware, an increasingly prevalent and sophisticated cyber threat, necessitates innovative response strategies. This study examines the capabilities of these LLMs in simulating human-like negotiation tactics against ransomware attacks, focusing on two main types: cryptographic and data exfiltration ransomware. Through a series of controlled simulations, the efficacy of ChatGPT and Claude in understanding complex language constructs, formulating negotiation strategies, and their adaptability to varying ransomware scenarios is evaluated. The research highlights the strengths of these models in response accuracy, adaptability, and psychological manipulation resistance. However, it also reveals their susceptibility to producing hallucinations — instances of unrealistic or inaccurate responses. The study contributes to the understanding of AI's potential in cybersecurity, emphasizing the need for improvements in AI reliability, ethical considerations, and the integration of human oversight. The findings suggest that while LLMs hold promising potential in enhancing cyber defense mechanisms, their deployment in high-stakes scenarios like ransomware negotiations must be approached with caution and continuous oversight.

show abstract

When Cryptographic Ransomware Poses Cyber Threats: Ethical Challenges and Proposed Safeguards for Cybersecurity Researchers

Cited by 7 publications

References 12 publications

Operationalizing Cybersecurity Research Ethics Review: From Principles and Guidelines to Practice

Operationalizing Cybersecurity Research Ethics Review: From Principles and Guidelines to Practice

Entropy and Memory Forensics in Ransomware Analysis: Utilizing LLaMA-7B for Advanced Pattern Recognition

Evaluating Large Language Models in Ransomware Negotiation: A Comparative Analysis of ChatGPT and Claude

Contact Info

Product

Resources

About