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Security eBooks Use the methodology in this study guide to design, manage, and operate a balanced enterprise cybersecurity program that is pragmatic and realistic in the face of resource constraints and other real-world limitations. This guide is an instructional companion to the book Enterprise Cybersecurity: How to Build a Successful Cyberdefense Program Against Advanced Threats. The study guide will help you understand the book's ideas and put them to work. The guide can be used for self-study or in the classroom. Enterprise cybersecurity is about implementing a cyberdefense program that will succeed in defending against real-world attacks.
While we often know what should be done, the resources to do it often are not sufficient. The reality is that the Cybersecurity Conundrum - what the defenders request, what the frameworks specify, and what the budget allows versus what the attackers exploit - gets in the way of what needs to be done. Cyberattacks in the headlines affectin. Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype?
Now you can dive into the science and answer this question for yourself. With this practical guide, you'll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters; Quickly detect anomalies, including breaches, fraud, and impending system failure; Conduct malware analysis by extracting useful information.