Results 221 to 230 of about 150,359 (291)

Intrusion Detection and Real-Time Adaptive Security in Medical IoT Using a Cyber-Physical System Design. [PDF]

Sensors (Basel)
Alserhani F.
europepmc   +1 more source

Sociotechnical Cybersecurity Framework for Securing Health Care From Vulnerabilities and Cyberattacks: Scoping Review.

J Med Internet Res
Ewoh P, Vartiainen T, Mantere T.
europepmc   +1 more source

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Federated Conditional Variational Auto Encoders for Cyber Threat Intelligence: Tackling Non-IID Data in SDN Environments

IEEE Access
Federated Learning is a promising paradigm for sharing Cyber Threat Intelligence (CTI) without privacy issues by leveraging the cross-silos data in Software Defined Networking (SDN).
Syed Hussain Ali Kazmi, R. Hassan, Faizan Qamar, Kashif Nisar, M. Al-Betar   +4 more
semanticscholar   +1 more source

Towards Effective Identification of Attack Techniques in Cyber Threat Intelligence Reports using Large Language Models

The Web Conference
This work evaluates the performance of Cyber Threat Intelligence (CTI) extraction methods in identifying attack techniques from threat reports available on the web using the MITRE ATT&CK framework.
Hoang Cuong Nguyen, Shahroz Tariq, Mohan Baruwal Chhetri, Bao Quoc Vo   +3 more
semanticscholar   +1 more source

A heterogeneous graph-based approach for cyber threat attribution using threat intelligence

International Conference on Machine Learning and Computing
Cyber Threat attribution is the process of associating a cyberattack with the threat groups. This process is essential for enhancing defense strategies and enabling rapid response to threats, making threat attribution a critical component of an effective
Junting Duan, Yujie Luo,, Zhicheng Zhang, Jianjian Peng   +3 more
semanticscholar   +1 more source

Large Language Models are Unreliable for Cyber Threat Intelligence

ARES
Several recent works have argued that Large Language Models (LLMs) can be used to tame the data deluge in the cybersecurity field, by improving the automation of Cyber Threat Intelligence (CTI) tasks.
Emanuele Mezzi, Fabio Massacci, Katja Tuma   +2 more
semanticscholar   +1 more source

CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence

Neural Information Processing Systems
Cyber threat intelligence (CTI) is crucial in today's cybersecurity landscape, providing essential insights to understand and mitigate the ever-evolving cyber threats.
Md Tanvirul Alam, Dipkamal Bhusal, Le Nguyen, Nidhi Rastogi   +3 more
semanticscholar   +1 more source

Robust Cyber Threat Intelligence Sharing Using Federated Learning for Smart Grids

IEEE Transactions on Computational Social Systems
Given the escalating diversity, sophistication, and frequency of cyber attacks, it is imperative for critical infrastructure entities, e.g. smart grids, to recognize the inherent risks of operating in isolation.
Saifur Rahman, Shantanu Pal, Zahra Jadidi, C. Karmakar   +3 more
semanticscholar   +1 more source

AGIR: Automating Cyber Threat Intelligence Reporting with Natural Language Generation

BigData Congress [Services Society], 2023
Cyber Threat Intelligence (CTI) reporting is pivotal in contemporary risk management strategies. As the volume of CTI reports continues to surge, the demand for automated tools to streamline report generation becomes increasingly apparent.
Filippo Perrina, Francesco Marchiori, Mauro Conti, Nino Vincenzo Verde   +3 more
semanticscholar   +1 more source

AT4CTIRE: Adversarial Training for Cyber Threat Intelligence Relation Extraction

Electronics
Cyber Threat Intelligence (CTI) plays a crucial role in cybersecurity. However, traditional information extraction has low accuracy due to the specialization of CTI and the concealment of relations.
Yue Han, Rong Jiang, Changjian Li, Yanyi Huang, Kai Chen, Han Yu, Aiping Li, Weihong Han, Shengnan Pang, Xuechen Zhao   +9 more
semanticscholar   +1 more source