Ransomware Attack Modeling and Artificial Intelligence-Based Ransomware Detection for Digital Substations

Alvee, Syed Raqueed Bin; Ahn, Bohyun; Kim, Taesic; Shen, Ying; Youn, Young-Woo; Ryu, Myung-Hyo

doi:10.1109/egrid52793.2021.9662158

Cited by 14 publications

(15 citation statements)

References 5 publications

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“…It is clear that defensive strategies must transcend the realm of mere technological solutions and encompass tactical counteractions to combat the psychological manipulation and persuasive elements prevalent in ransomware assaults [19], [21]. This necessitates the consideration and implementation of deceptive methodologies, such as the deployment of honeypots [2], [45]. These honeypots serve a dual purpose: they act as baits to lure potential ransomware threats, thereby allowing for their early identification and comprehensive analysis, and they function as a means to safeguard the broader network infrastructure from the damaging impact of these threats [46], [47].…”

Section: B Strategic Adjustments In Cyber Defensementioning

confidence: 99%

“…This possibility necessitates a cautious approach to interpreting the results, suggesting that they should be viewed as indicative rather than conclusive. Such caution is advised especially when integrating these findings into a broader cybersecurity research framework, where they should be corroborated with additional studies and methods to ensure a more holistic understanding of the ransomware landscape [45], [50], [51].…”

Section: Limitations Of the Studymentioning

confidence: 99%

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Using ChatGPT to Analyze Ransomware Messages and to Predict Ransomware Threats

Fujima,

Kumamoto,

Yoshida

2023

Preprint

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This study looked into the complex landscape of ransomware communications, utilizing advanced language models like ChatGPT to analyze ransomware messages. The research focused on identifying and interpreting the linguistic and strategic elements embedded in these communications. Key findings revealed a significant evolution in ransomware tactics, marked by sophisticated linguistic patterns and psychological manipulation strategies. The study emphasized the need for integrating advanced linguistic analysis tools within cybersecurity frameworks and advocates for customized cybersecurity education programs. Future research directions were proposed, including expanding the dataset and integrating diverse analytical methodologies. This research contributed to a deeper understanding of ransomware threats and offered insights into developing more effective cybersecurity measures against them.

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Section: B Strategic Adjustments In Cyber Defensementioning

confidence: 99%

Section: Limitations Of the Studymentioning

confidence: 99%

Using ChatGPT to Analyze Ransomware Messages and to Predict Ransomware Threats

Fujima,

Kumamoto,

Yoshida

2023

Preprint

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“…The study's results demonstrate that while LLMs like ChatGPT and Claude can effectively simulate human-like negotiation tactics, their performance varies based on the ransomware type and the specific scenario [1], [31], [46]. This variability underscores the potential and limitations of AI-driven cybersecurity solutions, [28], [31].…”

Section: B Implications For Cybersecuritymentioning

confidence: 99%

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

Kumamoto,

Yoshida,

Fujima

2023

Preprint

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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.

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“…• Cryptoransomware: Exhibiting greater complexity than locker variants, cryptoransomware is notorious for encrypting crucial data and files within the victim's system [30]. The process of recovery without the specific decryption key, which is typically in the possession of the attacker, is often an insurmountable task [31]. • Data Theft Ransomware: Representing an advanced stage in the evolution of ransomware, this variant not only encrypts the data but also poses the threat of publicizing sensitive information extracted from the victim's network unless a ransom is paid, thus introducing an extra layer of pressure and coercion [32], [33], [34].…”

Section: A Understanding Ransomwarementioning

confidence: 99%

“…For organizations, the repercussions are multifaceted, encompassing not just the immediate financial drain due to ransom payments but also extending to long-term reputational harm, operational disruptions, and the looming threat of legal repercussions [29]. These attacks also have a profound impact on the societal level, where the erosion of public confidence in digital infrastructure becomes apparent, and the potential disruption of essential services emerges as a significant concern [30], [31]. For instance, the 2021 cyber attack on the Colonial Pipeline, a crucial fuel conduit in the USA, led to extensive fuel scarcities and served as a stark reminder of how ransomware can cripple critical infrastructure [32], [34].…”

Section: B Impact Of Ransomware Attacksmentioning

confidence: 99%

Enhancing Public Awareness and Education of Ransomware Attacks

Kumar

2023

Preprint

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<p>Ransomware, a formidable cybersecurity challenge, has escalated in prevalence and sophistication, impacting individuals, organizations, and infrastructures globally. This article delves into the operational mechanisms, progression, and tactics of ransomware, particularly focusing on locker, cryptoransomware, and data theft ransomware. It highlights the significant effects of these assaults across various sectors and emphasizes the pivotal role of knowledge dissemination and educational efforts in ransomware defense. The article encompasses an examination of preventative measures, appraisal of awareness campaigns, and educational initiatives, along with a critical assessment of challenges and future directions in ransomware mitigation. It argues that public awareness and educational programs are not merely supplementary but fundamental aspects of a comprehensive cybersecurity strategy. This piece contributes to the ongoing conversation in cybersecurity, providing insights and recommendations for policymakers, professionals, educators, and the public, and emphasizes the necessity of a well-informed and proactive approach in combating ransomware threats.</p>

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Ransomware Attack Modeling and Artificial Intelligence-Based Ransomware Detection for Digital Substations

Cited by 14 publications

References 5 publications

Using ChatGPT to Analyze Ransomware Messages and to Predict Ransomware Threats

Using ChatGPT to Analyze Ransomware Messages and to Predict Ransomware Threats

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

Enhancing Public Awareness and Education of Ransomware Attacks

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