Application of Large Language Models (LLMs) for Software Vulnerability Detection by Marwan Omar
Large Language Models (LMs) are redefining the landscape of cybersecurity, offering innovative methods for detecting software vulnerabilities. By applying advanced AI techniques to identify and predict weaknesses in software code, including zero-day exploits and complex malware, LMs provide a proactive approach to securing digital environments. This integration of AI and cybersecurity presents new possibilities for enhancing software security measures. Application of Large Language Models (LMs) for Software Vulnerability Detection offers a comprehensive exploration of this groundbreaking field. These chapters are designed to bridge the gap between AI research and practical application in cybersecurity, in order to provide valuable insights for researchers, AI specialists, software developers, and industry professionals. Through real-world examples and actionable strategies, the publication will drive innovation in vulnerability detection and set new standards for leveraging AI in cybersecurity.-
Strategic Approaches to Digital Platform Security Assurance
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Privacy and Security Challenges in Location Aware Computing
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Revolutionary Applications of Blockchain-Enabled Privacy and Access Control
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Handbook of Research on Advancing Cybersecurity for Digital Transformation
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Social, Legal, and Ethical Implications of IoT, Cloud, and Edge Computing Technologies
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Multidisciplinary Approaches to Ethics in the Digital Era
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Enabling Blockchain Technology for Secure Networking and Communications
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Blockchain Applications in IoT Security
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Advances in Malware and Data-Driven Network Security
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Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies
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Applications of Encryption and Watermarking for Information Security
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Global Perspectives on Cybersecurity Risk in Contemporary Business Systems
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Cross-Industry Applications of Cyber Security Frameworks
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Quantum Cryptography and the Future of Cyber Security
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Handbook of Research on Cyber Security Intelligence and Analytics
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Handbook of Research on Cyber Law, Data Protection, and Privacy
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Multidisciplinary Approach to Modern Digital Steganography
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Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity
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Establishing Cyber Security Programs Through the Community Cyber Security Maturity Model (CCSMM)
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Personal Data Protection and Legal Developments in the European Union
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Limitations and Future Applications of Quantum Cryptography
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Privacy Concerns Surrounding Personal Information Sharing on Health and Fitness Mobile Apps
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Information Security Practices for the Internet of Things, 5G, and Next-Generation Wireless Networks
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Sensor Network Methodologies for Smart Applications
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Legal Regulations, Implications, and Issues Surrounding Digital Data
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Digital Transformation and Challenges to Data Security and Privacy
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Cases on Security, Safety, and Risk Management
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Smart and Agile Cybersecurity for IoT and IIoT Environments
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Integrating Artificial Intelligence in Cybersecurity and Forensic Practices
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Reshaping CyberSecurity With Generative AI Techniques
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5G and Fiber Optics Security Technologies for Smart Grid Cyber Defense
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Analyzing Privacy and Security Difficulties in Social Media: New Challenges and Solutions
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Analyzing Privacy and Security Difficulties in Social Media
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Redefining Security With Cyber AI
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Cryptography, Biometrics, and Anonymity in Cybersecurity Management
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Signal and Image Processing Techniques for Defense, Security, and Healthcare
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6G Security Education and Multidisciplinary Implementation
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Harnessing Quantum Cryptography for Next-Generation Security Solutions
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Modern Advancements in Surveillance Systems and Technologies
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Enhancing Steganography Through Deep Learning Approaches
| SKU | Unavailable |
| ISBN 13 | 9798369393116 |
| Title | Application of Large Language Models (LLMs) for Software Vulnerability Detection |
| Author | Marwan Omar |
| Series | Advances In Information Security Privacy And Ethics Ser |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | IGI Global |
| Year published | 2024-11-01 |
| Number of pages | 534 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |