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AI in Cybersecurity
Buch von Leslie F. Sikos
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor
Leslie F. Sikos, Ph.D. is a computer scientist specializing in formal knowledge representation, ontology engineering, and automated reasoning applied to various domains, including cyberthreat intelligence and network applications that require cybersituational awareness. He has worked in both academia and the industry, and acquired hands-on skills with datacenter and cloud infrastructures, cyberthreat management, and firewall configuration. He holds professional certificates and is a member of various industry-leading organizations, such as the ACM, the Association for Automated Reasoning, the IEEE Special Interest Group on Big Data for Cyber Security and Privacy, and the IEEE Computer Society Technical Committee on Security and Privacy.
Zusammenfassung

Presents state-of-the-art AI research on cybersecurity, cyberthreat intelligence, and cybersituational awareness

Offers strategic defense mechanisms for malware, addresses cybercrime, and assesses vulnerabilities to yield proactive rather than reactive countermeasures

Addresses aspects of processing security-related network data, utilizing social media and open data for intelligence gathering and data analytics, and real-life monitoring for vulnerability assessment

Inhaltsverzeichnis
OWL Ontologies in Cybersecurity: Conceptual Modeling of Cyber-Knowledge.- Knowledge Representation of Network Semantics for Reasoning-Powered Cyber-Situational Awareness.- The Security of Machine Learning Systems.- Patch Before Exploited: An Approach to Identify Targeted Software Vulnerabilities.- Applying Artificial Intelligence Methods to Network Attack Detection.- Machine Learning Algorithms for Network Intrusion Detection.- Android Application Analysis using Machine Learning Techniques.
Details
Erscheinungsjahr: 2018
Fachbereich: Technik allgemein
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 224
Reihe: Intelligent Systems Reference Library
Inhalt: xvii
205 S.
20 s/w Illustr.
29 farbige Illustr.
205 p. 49 illus.
29 illus. in color.
ISBN-13: 9783319988412
ISBN-10: 3319988417
Sprache: Englisch
Herstellernummer: 978-3-319-98841-2
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Redaktion: Sikos, Leslie F.
Herausgeber: Leslie F Sikos
Auflage: 1st ed. 2019
Hersteller: Springer International Publishing
Springer International Publishing AG
Intelligent Systems Reference Library
Maße: 241 x 160 x 18 mm
Von/Mit: Leslie F. Sikos
Erscheinungsdatum: 27.09.2018
Gewicht: 0,506 kg
preigu-id: 114093679
Über den Autor
Leslie F. Sikos, Ph.D. is a computer scientist specializing in formal knowledge representation, ontology engineering, and automated reasoning applied to various domains, including cyberthreat intelligence and network applications that require cybersituational awareness. He has worked in both academia and the industry, and acquired hands-on skills with datacenter and cloud infrastructures, cyberthreat management, and firewall configuration. He holds professional certificates and is a member of various industry-leading organizations, such as the ACM, the Association for Automated Reasoning, the IEEE Special Interest Group on Big Data for Cyber Security and Privacy, and the IEEE Computer Society Technical Committee on Security and Privacy.
Zusammenfassung

Presents state-of-the-art AI research on cybersecurity, cyberthreat intelligence, and cybersituational awareness

Offers strategic defense mechanisms for malware, addresses cybercrime, and assesses vulnerabilities to yield proactive rather than reactive countermeasures

Addresses aspects of processing security-related network data, utilizing social media and open data for intelligence gathering and data analytics, and real-life monitoring for vulnerability assessment

Inhaltsverzeichnis
OWL Ontologies in Cybersecurity: Conceptual Modeling of Cyber-Knowledge.- Knowledge Representation of Network Semantics for Reasoning-Powered Cyber-Situational Awareness.- The Security of Machine Learning Systems.- Patch Before Exploited: An Approach to Identify Targeted Software Vulnerabilities.- Applying Artificial Intelligence Methods to Network Attack Detection.- Machine Learning Algorithms for Network Intrusion Detection.- Android Application Analysis using Machine Learning Techniques.
Details
Erscheinungsjahr: 2018
Fachbereich: Technik allgemein
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 224
Reihe: Intelligent Systems Reference Library
Inhalt: xvii
205 S.
20 s/w Illustr.
29 farbige Illustr.
205 p. 49 illus.
29 illus. in color.
ISBN-13: 9783319988412
ISBN-10: 3319988417
Sprache: Englisch
Herstellernummer: 978-3-319-98841-2
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Redaktion: Sikos, Leslie F.
Herausgeber: Leslie F Sikos
Auflage: 1st ed. 2019
Hersteller: Springer International Publishing
Springer International Publishing AG
Intelligent Systems Reference Library
Maße: 241 x 160 x 18 mm
Von/Mit: Leslie F. Sikos
Erscheinungsdatum: 27.09.2018
Gewicht: 0,506 kg
preigu-id: 114093679
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