Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.

在安全和隐私实践方面，网络犯罪仍然是一个越来越大的挑战。通过合作，深度学习和网络安全专家最近在入侵检测、恶意代码分析和法医鉴定领域取得了重大进展。本书讨论了如何利用深度学习方法来推进网络安全目标的问题，包括检测、建模、监测和分析以及防御敏感数据和安全系统的各种威胁。本书填补了深度学习和网络安全社区之间的一个重要空白，讨论的主题涵盖了广泛的现代和实用的深度学习技术、框架和开发工具，使读者能够参与到网络安全各方面的前沿研究中。本书专注于成熟的、经过验证的技术，并提供了大量的例子来帮助读者掌握关键点。