Generative AI for Threat Hunting and Behaviour Analysis DOI
Siva Raja Sindiramutty, N. Z. Jhanjhi,

Rehan Akbar

et al.

Advances in digital crime, forensics, and cyber terrorism book series, Journal Year: 2024, Volume and Issue: unknown, P. 235 - 286

Published: Sept. 12, 2024

Cyber threats are becoming more advanced, and so is cybersecurity, which getting intellectual better at hiding its presence. The requirement to achieve the balance between proactive resistive threat-hunting measures in this dynamic environment very high. Part four outlines how new AI techniques enable design of existing processes for hunting potential threats. main objective digress into core principles threat hunting, starting from being including scenarios deducing clues based on hypothesis. Then, authors will highlight limitations conventional methods detecting gimmicks that fool even skilled hunters with an unseen smoking hiddenly a never-ending evolutionary process. Two well-studied approaches tackling these challenges generative models like adversarial networks (GANs) variational autoencoders (VAEs).

Language: Английский

AI in Healthcare Safeguarding Patient Privacy and Confidentiality DOI
Siva Raja Sindiramutty, N. Z. Jhanjhi, Navid Ali Khan

et al.

Advances in information security, privacy, and ethics book series, Journal Year: 2025, Volume and Issue: unknown, P. 369 - 404

Published: Feb. 14, 2025

In the era of digitization, Artificial Intelligence (AI) integration in healthcare has become a necessity to ensure patient identification & privacy. With rise digitalisation health systems, it also increasingly important have more stringent data protection requirements. This transformation is heavily facilitated by AI-driven technologies that reinforce security, identify real-time threats and streamline compliance with regulations. By utilizing Machine Learning (ML) algorithms comb through big data, outliers can be pinpointed filtered out so unauthorized access prevented assistance advanced forms encryption which protect information while transit or at rest. But fast pace AI development creates as many opportunities challenges, especially when comes marrying availability These ethical concerns, for effective regulatory frameworks, are critical an evolving ecosystem technologies.

Language: Английский

Citations

0
Progress and Obstacles in Cloud Computing for Healthcare DOI

Abu Jor Al Gefari,

Imran Hasan,

Md Amin Ullah Sheikh

et al.

Advances in information security, privacy, and ethics book series, Journal Year: 2025, Volume and Issue: unknown, P. 347 - 368

Published: Feb. 14, 2025

Since the invention of Internet Things (IoT), people are seeing a new world in healthcare. The rapid growth IoT has brought with it solutions to dilemmas and few challenges cloud devices. But keeping mind benefits these devices, need be solved efficiency security. Putting place storage analysis for specific periods is very popular medicine. On other hand, creating big data, considering sensitivity, some limitations have accepted. use latency, throughput, bandwidth increases cost Internet. Numerous alternative paradigms, most notably edge computing fog computing, evolved solve shortcomings. Consequently, studies shown an increase hybrid based.

Language: Английский

Citations

0
Future Trends in AI Security DOI
Siva Raja Sindiramutty, N. Z. Jhanjhi, Navid Ali Khan

et al.

Advances in information security, privacy, and ethics book series, Journal Year: 2025, Volume and Issue: unknown, P. 229 - 262

Published: Feb. 14, 2025

Cybersecurity is enriched due to Artificial Intelligence (AI), which provides better real-time threat detection and anomaly identification, response systems. As attackers grow more sophisticated leverage AI in creating malware. The present study gives an overview of the future threats associated with AI-driven attacks challenges faced by existing cybersecurity countermeasures. Additionally, it also analyses feasibility using capabilities like predictive intelligence, advanced quantum computing for some these emerging threats. For such as, we need user permissions rights on this application, should take into consideration privacy policies while designing security as well. To end, get ready against risks a proactive adaptive approach needed stressing collaboration between industry, academia well global entities.

Language: Английский

Citations

0
Current Security Issues and Vulnerabilities Associated With Mobile Application DOI

Abdullahi Adewole Zakariyah,

Muhammand Intizar Ali,

Nima Yoezer

et al.

Advances in information security, privacy, and ethics book series, Journal Year: 2025, Volume and Issue: unknown, P. 41 - 62

Published: Feb. 14, 2025

Mobile applications have become a crucial part of modern life, facilitating everything from social interactions to financial transactions. However, this ubiquity also presents significant security challenge. The landscape mobile app is fraught with vulnerabilities and threats that can compromise user data, privacy, the overall integrity applications. This paper delves into issues affect It provides an in-depth analysis various attack methods used by cybercriminals extract data explores how users protect their information being compromised. discussion will cover common tactics employed attackers, potential consequences losing application these threats, critical measures necessary for safeguarding against such attacks.

Language: Английский

Citations

0
Generative AI for Threat Hunting and Behaviour Analysis DOI
Siva Raja Sindiramutty, N. Z. Jhanjhi,

Rehan Akbar

et al.

Advances in digital crime, forensics, and cyber terrorism book series, Journal Year: 2024, Volume and Issue: unknown, P. 235 - 286

Published: Sept. 12, 2024

Cyber threats are becoming more advanced, and so is cybersecurity, which getting intellectual better at hiding its presence. The requirement to achieve the balance between proactive resistive threat-hunting measures in this dynamic environment very high. Part four outlines how new AI techniques enable design of existing processes for hunting potential threats. main objective digress into core principles threat hunting, starting from being including scenarios deducing clues based on hypothesis. Then, authors will highlight limitations conventional methods detecting gimmicks that fool even skilled hunters with an unseen smoking hiddenly a never-ending evolutionary process. Two well-studied approaches tackling these challenges generative models like adversarial networks (GANs) variational autoencoders (VAEs).

Language: Английский

Citations

0