Network Science and Cybersecurity introduces new research and development efforts for cybersecurity solutions and applications taking place within various U.S. Government Departments of Defense, industry and academic laboratories. This book examines new algorithms and tools, technology platforms and reconfigurable technologies for cybersecurity systems. Anomaly-based intrusion detection systems (IDS) are explored as a key component of any general network intrusion detection service, complementing signature-based IDS components by attempting to identify novel attacks. These attacks may not yet be known or have well-developed signatures. Methods are also suggested to simplify the construction of metrics in such a manner that they retain their ability to effectively cluster data, while simultaneously easing human interpretation of outliers.This is a professional book for practitioners or government employees working in cybersecurity, and can also be used as a reference. Advanced-level students in computer science or electrical engineering studying security will also find this book useful .
This book explores cybersecurity research and development efforts, including ideas that deal with the growing challenge of how computing engineering can merge with neuroscience. The contributing authors, who are renowned leaders in this field, thoroughly examine new technologies that will automate security procedures and perform autonomous functions with decision making capabilities. To maximize reader insight into the range of professions dealing with increased cybersecurity issues, this book presents work performed by government, industry, and academic research institutions working at the frontier of cybersecurity and network sciences. Cybersecurity Systems for Human Cognition Augmentation is designed as a reference for practitioners or government employees working in cybersecurity. Advanced-level students or researchers focused on computer engineering or neuroscience will also find this book a useful resource.
Physical implementation of the memristor at industrial scale sparked the interest from various disciplines, ranging from physics, nanotechnology, electrical engineering, neuroscience, to intelligent robotics. As any promising new technology, it has raised hopes and questions; it is an extremely challenging task to live up to the high expectations and to devise revolutionary and feasible future applications for memristive devices. The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural Networks held in San Jose, CA, has offered us the unique opportunity of organizing a series of special events on the present status and future perspectives in neuromorphic memristor science. This book presents a selection of the remarkable contributions given by the leaders of the field and it may serve as inspiration and future reference to all researchers that want to explore the extraordinary possibilities given by this revolutionary concept.