By Jason Andress
Cyber conflict, moment Edition, takes a finished examine how and why electronic battle is waged. The booklet explores the individuals, battlefields, and the instruments and strategies utilized in present day electronic conflicts. The strategies mentioned offers scholars of data protection a greater thought of the way cyber conflicts are conducted now, how they're going to swap sooner or later, and the way to discover and shield opposed to espionage, hacktivism, insider threats and non-state actors reminiscent of prepared criminals and terrorists.
This e-book presents concrete examples and real-world suggestions on how one can establish and shield a community opposed to malicious assaults. It probes correct technical and real details from an insider's perspective, in addition to the ethics, legislation and outcomes of cyber struggle and the way machine felony legislations may perhaps swap hence. Logical, actual, and mental guns utilized in cyber war are discussed.
This textual content will attract info defense practitioners, community defense directors, desktop method directors, and defense analysts.
- Provides concrete examples and real-world counsel on easy methods to determine and shield your community opposed to malicious attacks
- Dives deeply into suitable technical and genuine info from an insider's aspect of view
- Details the ethics, legislation and outcomes of cyber battle and the way computing device legal legislation may perhaps switch as a result
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Extra resources for Cyber warfare : techniques, tactics and tools for security practitioners
As a result, there is now an urgent need to develop secure systems. However, as systems are being secured, malware technologies have also exploded. Therefore, it is critical that we develop tools for detecting and preventing malware. 2. In this book we discuss data mining for malware detection. In particular, we discuss techniques such as support vector machines, clustering, and classification for cyber security applications. 3. 3 Data Mining for Email Worm Detection An email worm spreads through infected email messages.
In addition, the techniques should result in fewer false positives and negatives. Although there is still much to be done, the progress over the past decade is extremely promising. , T. Imielinski, A. Swami, Mining Association Rules between Sets of Items in Large Databases, in Proceedings of the ACM SIGMOD Conference on Management of Data, Washington, DC, May 1993, pp. 207–216. , C. Aggarwal, V. Prasad, A Tree Projection Algorithm for Generation of Frequent Item Sets, Journal of Parallel and Distributed Computing Archive, Vol.
18, 19, 20 Emerging technologies Core technologies Malicious code detection Ch. 9, 10, 11 Malware Ch. 3 Supporting technologies Applications Ch. 4 Tools Ch. 5 Contents of the book with respect to the framework. Part I D ata M ining and S ecurit y Introduction to Part I: Data Mining and Security Supporting technologies for data mining for malware detection include data mining and malware technologies. Data mining is the process of analyzing the data and uncovering hidden dependencies. The outcomes of data mining include classification, clustering, forming associations, as well as detecting anomalies.