Sedat Akleylek – författare

This handbook of formal analysis in cryptography is very important for secure communication and processing of information. It introduces readers to several formal verification methods and software used to analyse cryptographic protocols. The chapters give readers general knowledge and formal methods focusing on cryptographic protocols.Handbook of Formal Analysis and Verification in Cryptography includes major formalisms and tools used for formal verification of cryptography, with a spotlight on new-generation cryptosystems such as post-quantum, and presents a connection between formal analysis and cryptographic schemes. The text offers formal methods to show whether security assumptions are valid and compares the most prominent formalism and tools as they outline common challenges and future research directions.Graduate students, researchers, and engineers worldwide will find this an exciting read.

This handbook of formal analysis in cryptography is very important for secure communication and processing of information. It introduces readers to several formal verification methods and software used to analyse cryptographic protocols. The chapters give readers general knowledge and formal methods focusing on cryptographic protocols.Handbook of Formal Analysis and Verification in Cryptography includes major formalisms and tools used for formal verification of cryptography, with a spotlight on new-generation cryptosystems such as post-quantum, and presents a connection between formal analysis and cryptographic schemes. The text offers formal methods to show whether security assumptions are valid and compares the most prominent formalism and tools as they outline common challenges and future research directions.Graduate students, researchers, and engineers worldwide will find this an exciting read.

Generative AI for Cybersecurity explores how rapidly evolving generative models are reshaping modern digital defense. As organizations become more interconnected and data-driven, traditional cybersecurity measures are increasingly challenged by adaptive, AI-powered threats. Generative AI (GenAI) introduces new capabilities that can significantly enhance threat detection, automate security operations, and improve situational awareness, but it also enables sophisticated offensive techniques, deepfakes, automated malware generation, and large-scale misinformation.This book provides a balanced and comprehensive examination of this dual-use technology. It highlights how generative models can be leveraged to build resilient, intelligent, and proactive defense mechanisms capable of anticipating and countering emerging cyber risks. At the same time, it critically analyzes the vulnerabilities, ethical dilemmas, and regulatory challenges introduced by the misuse of GenAI. Through diverse perspectives and expert contributions, the book bridges theoretical foundations with real-world applications, demonstrating how GenAI can support adaptive intrusion detection, anomaly analysis, secure autonomous systems, and more transparent and explainable security solutions.Beyond technical considerations, the book addresses broader societal, geopolitical, and governance implications, including issues of trust, sovereignty, and responsible AI deployment. It offers frameworks, methodologies, and practical insights suitable for researchers, practitioners, students, and policymakers seeking to understand, develop, or regulate GenAI-driven cybersecurity systems.By examining both the opportunities and the risks, Generative AI for Cybersecurity serves as a timely reference for navigating an era where AI is not only a tool for defense but also a catalyst for new forms of cyber aggression, highlighting the urgent need for innovative, ethical, and resilient approaches to securing the digital world.

Generative AI for Cybersecurity explores how rapidly evolving generative models are reshaping modern digital defense. As organizations become more interconnected and data-driven, traditional cybersecurity measures are increasingly challenged by adaptive, AI-powered threats. Generative AI (GenAI) introduces new capabilities that can significantly enhance threat detection, automate security operations, and improve situational awareness, but it also enables sophisticated offensive techniques, deepfakes, automated malware generation, and large-scale misinformation.This book provides a balanced and comprehensive examination of this dual-use technology. It highlights how generative models can be leveraged to build resilient, intelligent, and proactive defense mechanisms capable of anticipating and countering emerging cyber risks. At the same time, it critically analyzes the vulnerabilities, ethical dilemmas, and regulatory challenges introduced by the misuse of GenAI. Through diverse perspectives and expert contributions, the book bridges theoretical foundations with real-world applications, demonstrating how GenAI can support adaptive intrusion detection, anomaly analysis, secure autonomous systems, and more transparent and explainable security solutions.Beyond technical considerations, the book addresses broader societal, geopolitical, and governance implications, including issues of trust, sovereignty, and responsible AI deployment. It offers frameworks, methodologies, and practical insights suitable for researchers, practitioners, students, and policymakers seeking to understand, develop, or regulate GenAI-driven cybersecurity systems.By examining both the opportunities and the risks, Generative AI for Cybersecurity serves as a timely reference for navigating an era where AI is not only a tool for defense but also a catalyst for new forms of cyber aggression, highlighting the urgent need for innovative, ethical, and resilient approaches to securing the digital world.

Generative AI for Cybersecurity explores how rapidly evolving generative models are reshaping modern digital defense. As organizations become more interconnected and data-driven, traditional cybersecurity measures are increasingly challenged by adaptive, AI-powered threats. Generative AI (GenAI) introduces new capabilities that can significantly enhance threat detection, automate security operations, and improve situational awareness, but it also enables sophisticated offensive techniques, deepfakes, automated malware generation, and large-scale misinformation.This book provides a balanced and comprehensive examination of this dual-use technology. It highlights how generative models can be leveraged to build resilient, intelligent, and proactive defense mechanisms capable of anticipating and countering emerging cyber risks. At the same time, it critically analyzes the vulnerabilities, ethical dilemmas, and regulatory challenges introduced by the misuse of GenAI. Through diverse perspectives and expert contributions, the book bridges theoretical foundations with real-world applications, demonstrating how GenAI can support adaptive intrusion detection, anomaly analysis, secure autonomous systems, and more transparent and explainable security solutions.Beyond technical considerations, the book addresses broader societal, geopolitical, and governance implications, including issues of trust, sovereignty, and responsible AI deployment. It offers frameworks, methodologies, and practical insights suitable for researchers, practitioners, students, and policymakers seeking to understand, develop, or regulate GenAI-driven cybersecurity systems.By examining both the opportunities and the risks, Generative AI for Cybersecurity serves as a timely reference for navigating an era where AI is not only a tool for defense but also a catalyst for new forms of cyber aggression, highlighting the urgent need for innovative, ethical, and resilient approaches to securing the digital world.

This book features selected papers from the 7th International Conference on Mathematics and Computing (ICMC 2021), organized by Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India, during March 2021. It covers recent advances in the field of mathematics, statistics, and scientific computing. The book presents innovative work by leading academics, researchers, and experts from industry.