Adversary-Aware Learning Techniques and Trends in Cybersecurity
暫譯: 對抗者意識的學習技術與網路安全趨勢
Dasgupta, Prithviraj, Collins, Joseph B., Mittu, Ranjeev
相關主題
商品描述
Part I: Game-Playing AI and Game Theory-based Techniques for Cyber Defenses
Rethinking Intelligent Behavior as Competitive Games for Handling Adversarial Challenges to Machine Learning
Joseph B Collins and Prithviraj Dasgupta
Security of Distributed Machine Learning: A Game-Theoretic Approach to Design Secure DSVM
Rui Zhang and Quanyan Zhu
Be Careful When Learning Against Adversaries: Imitative Attacker Deception in Stackelberg Security Games
Haifeng Xu and Thanh H. Nguyen
Part II: Data Modalities and Distributed Architectures for Countering Adversarial Cyber Attacks
Adversarial Machine Learning in Text: A Case Study of Phishing Email Detection with RCNN model
Daniel Lee and Rakesh M. Verma
Overview of GANs for Image Synthesis and Detection Methods
Eric Tjon, Melody Moh and Teng-Sheng Moh
Robust Machine Learning using Diversity and Blockchain
Raj Mani Shukla, Shahriar Badsha, Deepak Tosh, and Shamik Sengupta
Part III: Human Machine Interactions and Roles in Automated Cyber Defenses
Automating the Investigation of Sophisticated Cyber Threats with Cognitive Agents
Steven Meckl, Gheorghe Tecuci, Dorin Marcu and Mihai Boicu
Integrating Human Reasoning and Machine Learning to Classify Cyber Attacks
Ying Zhao and Lauren Jones
Homology as an Adversarial Attack Indicator
Ira S. Moskowitz, Nolan Bay, Brian Jalaian and Arnold Tunick
Cyber-(in)security, revisited: Proactive Cyber-defenses, Interdependence and Autonomous Human Machine Teams (A-HMTs)
William Lawless, Ranjeev Mittu, Ira Moskowitz, Donald Sofge and Stephen Russell
商品描述(中文翻譯)
**第一部分：遊戲玩法 AI 與基於遊戲理論的網路防禦技術**
**重新思考智能行為作為競爭遊戲，以應對對機器學習的對抗挑戰**
Joseph B Collins 和 Prithviraj Dasgupta
**分散式機器學習的安全性：設計安全的 DSVM 的遊戲理論方法**
Rui Zhang 和 Quanyan Zhu
**在對抗者面前學習時要小心：Stackelberg 安全遊戲中的模仿攻擊者欺騙**
Haifeng Xu 和 Thanh H. Nguyen
**第二部分：對抗性網路攻擊的數據模式與分散式架構**
**文本中的對抗性機器學習：使用 RCNN 模型進行釣魚郵件檢測的案例研究**
Daniel Lee 和 Rakesh M. Verma
**圖像合成與檢測方法的 GAN 概述**
Eric Tjon、Melody Moh 和 Teng-Sheng Moh
**利用多樣性和區塊鏈的穩健機器學習**
Raj Mani Shukla、Shahriar Badsha、Deepak Tosh 和 Shamik Sengupta
**第三部分：人機互動與自動化網路防禦中的角色**
**利用認知代理自動調查複雜的網路威脅**
Steven Meckl、Gheorghe Tecuci、Dorin Marcu 和 Mihai Boicu
**整合人類推理與機器學習以分類網路攻擊**
Ying Zhao 和 Lauren Jones
**同源性作為對抗性攻擊指標**
Ira S. Moskowitz、Nolan Bay、Brian Jalaian 和 Arnold Tunick
**網路（不）安全的再思考：主動網路防禦、相互依賴與自主人機團隊（A-HMTs）**
William Lawless、Ranjeev Mittu、Ira Moskowitz、Donald Sofge 和 Stephen Russell
