Adversary-Aware Learning Techniques and Trends in Cybersecurity
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10

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Published By Springer International Publishing

9783030556914, 9783030556921

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Cyber-(in)Security, Revisited: Proactive Cyber-Defenses, Interdependence and Autonomous Human-Machine Teams (A-HMTs)

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_10 ◽

2021 ◽

pp. 197-224

Author(s):

William F. Lawless ◽

Ranjeev Mittu ◽

Ira S. Moskowitz ◽

Donald A. Sofge ◽

Stephen Russell

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Automating the Investigation of Sophisticated Cyber Threats with Cognitive Agents

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_7 ◽

2021 ◽

pp. 125-146

Author(s):

Steven Meckl ◽

Gheorghe Tecuci ◽

Dorin Marcu ◽

Mihai Boicu

Keyword(s):

Cognitive Agents ◽

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Security of Distributed Machine Learning

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_2 ◽

2020 ◽

pp. 17-36

Author(s):

Rui Zhang ◽

Quanyan Zhu

Keyword(s):

Machine Learning ◽

Distributed Machine Learning

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Integrating Human Reasoning and Machine Learning to Classify Cyber Attacks

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_8 ◽

2020 ◽

pp. 147-165

Author(s):

Ying Zhao ◽

Lauren Jones

Keyword(s):

Machine Learning ◽

Cyber Attacks ◽

Human Reasoning

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Overview of GANs for Image Synthesis and Detection Methods

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_5 ◽

2020 ◽

pp. 85-101

Author(s):

Eric Tjon ◽

Melody Moh ◽

Teng-Sheng Moh

Keyword(s):

Image Synthesis ◽

Detection Methods

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Robust Machine Learning Using Diversity and Blockchain

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_6 ◽

2020 ◽

pp. 103-121

Author(s):

Raj Mani Shukla ◽

Shahriar Badsha ◽

Deepak Tosh ◽

Shamik Sengupta

Keyword(s):

Machine Learning

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Adversarial Machine Learning in Text: A Case Study of Phishing Email Detection with RCNN Model

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_4 ◽

2020 ◽

pp. 61-83

Author(s):

Daniel Lee ◽

Rakesh M. Verma

Keyword(s):

Machine Learning

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Homology as an Adversarial Attack Indicator

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_9 ◽

2020 ◽

pp. 167-196

Author(s):

Ira S. Moskowitz ◽

Nolan Bay ◽

Brian Jalaian ◽

Arnold Tunick

Keyword(s):

Adversarial Attack

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Be Careful When Learning Against Adversaries: Imitative Attacker Deception in Stackelberg Security Games

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_3 ◽

2020 ◽

pp. 37-57

Author(s):

Haifeng Xu ◽

Thanh H. Nguyen

Keyword(s):

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Rethinking Intelligent Behavior as Competitive Games for Handling Adversarial Challenges to Machine Learning

Adversary-Aware Learning Techniques and Trends in Cybersecurity ◽

10.1007/978-3-030-55692-1_1 ◽

2020 ◽

pp. 3-16

Author(s):

Joseph B. Collins ◽

Prithviraj Dasgupta

Keyword(s):

Machine Learning ◽

Intelligent Behavior ◽

Competitive Games

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