Information Studies: MIDS & MICS

This timely book offers rare insight into the field of cybersecurity in Russia -- a significant player with regard to cyber-attacks and cyber war. Big Data Technologies for Monitoring of Computer Security presents possible solutions to the relatively new scientific/technical problem of developing an early-warning cybersecurity system for critically important governmental information assets. 

This handbook documents and organizes conversations, bringing together some of the most thoughtful and impactful contributors to contemporary surveillance debates, policies, and practices. Its pages explore surveillance techniques and technologies; their value for law enforcement, national security, and private enterprise; their impacts on citizens and communities; and the many ways societies do - and should - regulate surveillance.

As human activities moved to the digital domain, so did all the well-known malicious behaviors including fraud, theft, and other trickery. There is no silver bullet, and each security threat calls for a specific answer. One specific threat is that applications accept malformed inputs, and in many cases it is possible to craft inputs that let an intruder take full control over the target computer system.

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.

Network Security and Cryptography introduces the basic concepts in computer networks and the latest trends and technologies in cryptography and network security. The book is a definitive guide to the principles and techniques of cryptography and network security, and introduces basic concepts in computer networks such as classical cipher schemes, public key cryptography, authentication schemes, pretty good privacy, and Internet security.

This book presents a practical framework for the application of big data, cloud, and pervasive and complex systems to sustainable solutions for urban environmental challenges.  It covers the technologies, potential, and possible and impact of big data on energy efficiency and the urban environment.

This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations.

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.

This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework.