Cybersecurity Systems For Human Cognition Augmentation by Robinson E. PinoCybersecurity Systems For Human Cognition Augmentation by Robinson E. Pino

Cybersecurity Systems For Human Cognition Augmentation

byRobinson E. PinoEditorAlexander Kott, Michael Shevenell

Paperback | September 10, 2016

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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.
Title:Cybersecurity Systems For Human Cognition AugmentationFormat:PaperbackDimensions:209 pages, 23.5 × 15.5 × 0.17 inPublished:September 10, 2016Publisher:Springer NatureLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319352229

ISBN - 13:9783319352220


Table of Contents

Situational awareness, sensemaking, and situation understanding in cyber warfare.- Neuromorphic Computing for Cognitive Augmentation in Cyber Defense.- Automated Cyber Situation Awareness Tools and Models for Improving Analyst Performance.- Data Mining in Cyber Operations.- Trusted Computation through Biologically Inspired Processes.- Dynamic Logic Machine Learning for Cybersecurity.- Towards Neural Network Based Malware Detection on Android Mobile Devices.- Sustainability Problems and a Novelty in the Concept of Energy.- Memristors as Synapses in Artificial Neural Networks: Biomimicry Beyond Weight Change.- Low Power Neuromorphic Architectures to Enable Pervasive Deployment of Intrusion Detection Systems.- Memristor SPICE Model Simulation and Device Hardware Correlation.- Reconfigurable Memristor Based Computing Logic.- Cyber Security Considerations for Reconfigurable Systems.