Cyber-Enabled Intelligence

Cyber-Enabled Intelligence

Author: Huansheng Ning

Publisher: Taylor & Francis

Published: 2019-08-08

Total Pages: 355

ISBN-13: 0429591675

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The book provides an advanced vision and trends of computational intelligence in cyberspace and cyber-enabled spaces. It reviews architectures and models, as well as state-of-the-art computational and interpretation capabilities for social, industrial, and multimedia applications. Cyber-enabled intelligence involves the design and development of intelligent and innovative application scenarios in social networks, computer vision, multimedia, and image processing. Application scenarios can also cover the applicability of intelligent sensing, data collection and predictive analysis in Internet of Things.


Cyber-Enabled Intelligence

Cyber-Enabled Intelligence

Author: Huansheng Ning

Publisher: Taylor & Francis

Published: 2019-08-08

Total Pages: 261

ISBN-13: 0429589735

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The book provides an advanced vision and trends of computational intelligence in cyberspace and cyber-enabled spaces. It reviews architectures and models, as well as state-of-the-art computational and interpretation capabilities for social, industrial, and multimedia applications. Cyber-enabled intelligence involves the design and development of intelligent and innovative application scenarios in social networks, computer vision, multimedia, and image processing. Application scenarios can also cover the applicability of intelligent sensing, data collection and predictive analysis in Internet of Things.


Implications of Artificial Intelligence for Cybersecurity

Implications of Artificial Intelligence for Cybersecurity

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2020-01-27

Total Pages: 99

ISBN-13: 0309494508

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In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.


AI In The Age Of Cyber-Disorder

AI In The Age Of Cyber-Disorder

Author: Fabio Rugge

Publisher: Ledizioni

Published: 2020-12-15

Total Pages: 109

ISBN-13: 8855263846

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The rise of Artificial Intelligence applications is accelerating the pace and magnitude of the political, securitarian, and ethical challenges we are now struggling to manage in cyberspace and beyond. So far, the relationship between Artificial Intelligence and cyberspace has been investigated mostly in terms of the effects that AI could have on the digital domain, and thus on our societies. What has been explored less is the opposite relationship, namely, how the cyberspace geopolitics can affect AI. Yet, AI applications have so far suffered from growing unrest, disorder, and lack of normative solutions in cyberspace. As such, from algorithm biases, to surveillance and offensive applications, AI could accelerate multiple growing threats and challenges in and through cyberspace. This report by ISPI and The Brookings Institution is an effort to shed light on this less studied, but extremely relevant, relationship.


AI-Enabled Threat Detection and Security Analysis for Industrial IoT

AI-Enabled Threat Detection and Security Analysis for Industrial IoT

Author: Hadis Karimipour

Publisher: Springer Nature

Published: 2021-08-03

Total Pages: 250

ISBN-13: 3030766136

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This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.


Cyberspace and Artificial Intelligence

Cyberspace and Artificial Intelligence

Author: Carlos Pedro Gonçalves

Publisher:

Published: 2019

Total Pages: 0

ISBN-13:

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While, until recently, cyber operations have constituted a specific subset of defense and security concerns, the synergization of cyberspace and artificial intelligence (AI), which are driving the Fourth Industrial Revolution, has raised the threat level of cyber operations, making them a centerpiece of what are called hybrid threats. The concept of hybrid threat is presently a key concern for the defense and security community; cyber-enabled and cyber-enhanced hybrid operations have been amplified in scope, frequency, speed, and threat level due to the synergies that come from the use of cyberspace and machine learning (ML)-based solutions. In the present work, we address the relevance of cyberspace-based operations and artificial intelligence for the implementation of hybrid operations and reflect on what this cyber dimension of hybrid operations implies for the concept of what constitutes a cyberweapon, the concept of hybrid human intelligence (hybrid HUMINT) and possible responses to the hybrid threat patterns.


MATLAB Deep Learning

MATLAB Deep Learning

Author: Phil Kim

Publisher: Apress

Published: 2017-06-15

Total Pages: 162

ISBN-13: 1484228456

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Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.


Advancing Cybersecurity for Digital Transformation

Advancing Cybersecurity for Digital Transformation

Author: Kamaljeet Sandhu

Publisher: Information Science Reference

Published: 2021

Total Pages: 315

ISBN-13: 9781799869757

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"This book offers a variety of perspectives on issues, problems, and innovative solutions and strategies that are linked to cybersecurity and its an impact on private and public organizations, government institutions, and consumers interacting on digital data"--


Intelligence (ADP 2-0)

Intelligence (ADP 2-0)

Author: Headquarters Department of the Army

Publisher: Lulu.com

Published: 2019-10-09

Total Pages: 86

ISBN-13: 0359970540

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ADP 2-0 provides a common construct for intelligence doctrine from which Army forces adapt to conduct operations. ADP 2-0 augments and is nested with the capstone doctrine from both ADRP 3-0 and FM 3-0. The principal audience for ADP 2-0 is every Soldier and Department of the Army Civilian who interact with the intelligence warfighting function. This publication is the foundation for the intelligence warfighting function and subsequent doctrine development. It also serves as a reference for personnel who are developing doctrine, leader development, materiel and force structure, and institutional and unit training for intelligence. ADP 2-0 uses joint terms where applicable. Selected joint and Army terms and definitions appear in both the glossary and the text. Terms for which ADP 2-0 is the proponent publication (the authority) are marked with an asterisk (*) in the glossary. Definitions for which ADP 2-0 is the proponent publication are boldfaced in the text.


AI in Cybersecurity

AI in Cybersecurity

Author: Leslie F. Sikos

Publisher: Springer

Published: 2018-09-17

Total Pages: 215

ISBN-13: 3319988425

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This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.