Generative AI for Cybersecurity Applications in Threat Simulation and Defense DOI
Yousef Sanjalawe, Salam Al-E’mari, Sharif Naser Makhadmeh

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 263 - 304

Published: April 23, 2025

The integration of generative AI in cybersecurity marks a transformative leap combating the growing complexity cyber threats. This chapter examines models like adversarial networks, variational autoencoders, and transformers, showcasing their role threat simulation, synthetic data generation, anomaly detection. Applications discussed include proactive defense testing, malware analysis, intrusion detection, highlighting AI's ability to predict, detect, mitigate sophisticated attacks. Emerging techniques, such as federated learning hybrid models, promise further advancements. However, poses challenges, including misuse vulnerabilities. Addressing these risks requires ethical guidelines, robust frameworks, collaboration. With its predictive adaptive potential, is reshaping cybersecurity, enabling resilient intelligent defenses for digital age.

Language: Английский

Innovative resource-saving security strategies for IoT devices DOI Creative Commons
Інна Розломій, Andrii Yarmilko, Serhii Naumenko

et al.

Journal of Edge Computing, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 12, 2025

The astounding trend of increasing the number connected IoT devices reflects growing importance this technology in industry, healthcare, domestic sphere, and other sectors. However, with expansion capabilities, challenges also rises, particularly regarding security these devices, many which are characterised by limited resources such as memory, power consumption, computational power, network bandwidth. This article examines key associated ensuring proposes potential solutions optimisation strategies that consider limitations. primary focus is developing analysing lightweight cryptographic algorithms capable providing robust data protection minimal resource usage. discusses efficient energy management optimising memory usage devices. Emphasis placed on adaptive mechanisms can effectively respond to dynamic operational conditions constraints. It noted further research development should creating integrated combine hardware, software, managerial aspects optimise overall efficiency systems.

Language: Английский

Citations

0
Generative AI for Cybersecurity Applications in Threat Simulation and Defense DOI
Yousef Sanjalawe, Salam Al-E’mari, Sharif Naser Makhadmeh

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 263 - 304

Published: April 23, 2025

The integration of generative AI in cybersecurity marks a transformative leap combating the growing complexity cyber threats. This chapter examines models like adversarial networks, variational autoencoders, and transformers, showcasing their role threat simulation, synthetic data generation, anomaly detection. Applications discussed include proactive defense testing, malware analysis, intrusion detection, highlighting AI's ability to predict, detect, mitigate sophisticated attacks. Emerging techniques, such as federated learning hybrid models, promise further advancements. However, poses challenges, including misuse vulnerabilities. Addressing these risks requires ethical guidelines, robust frameworks, collaboration. With its predictive adaptive potential, is reshaping cybersecurity, enabling resilient intelligent defenses for digital age.

Language: Английский

Citations

0