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Protection of Computational Machine Learning Models against Extraction Threat
AbstractThe extraction threat to machine learning models is considered. Most contemporary methods of defense against the extraction of computational...
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On Regenerating Codes and Proactive Secret Sharing: Relationships and Implications
We look at two basic coding theoretic and cryptographic mechanisms developed separately and investigate relationships between them and their...
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NBA: defensive distillation for backdoor removal via neural behavior alignment
Recently, deep neural networks have been shown to be vulnerable to backdoor attacks. A backdoor is inserted into neural networks via this attack...
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Security-as-a-Service with Cyberspace Mimic Defense Technologies in Cloud
Users usually focus on the application-level requirements which are quite friendly and direct to them. However, there are no existing tools...
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CONTINGENT: Advanced Solution to Enhance Cyber Resilience Through Machine Learning Techniques
The CONTINGENT project, developed under the CYRENE H2020 (Horizon 2020) project [1], is a pioneering initiative by FAVIT [2] to bolster cybersecurity...
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From sinking to saving: MITRE ATT &CK and D3FEND frameworks for maritime cybersecurity
Cybersecurity is a growing concern for maritime sector. Modern ships are practical realism of cyber physical systems that utilize both information...
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Proactive Network Defense with Game Theory
Traditional proactive network defenses deploy security resources in the network based on probabilistic policies to confuse potential attackers....
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Combating the Cyber-Security Kill Chain: Moving to a Proactive Security Model
A former boss of mine (Peter Drissell ( https://www.linkedin.com/in/peter-drissell-b917896/ ) (Commandant...
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Transferable adversarial sample purification by expanding the purification space of diffusion models
Deep neural networks (DNNs) have been demonstrated to be vulnerable to adversarial samples and many powerful defense methods have been proposed to...
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Proactive Detection of Phishing Kit Traffic
Current anti-phishing studies mainly focus on either detecting phishing pages or on identifying phishing emails sent to victims. In this paper, we...
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Proactive Defense Through Deception
Cyberattacks are typically preceded by a reconnaissance phase in which attackers aim at collecting valuable information about the target system,...
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Robust Training for Deepfake Detection Models Against Disruption-Induced Data Poisoning
As Generative Adversarial Networks continue to evolve, deepfake images have become notably more realistic, escalating societal, economic, and...
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Strategic Learning for Active, Adaptive, and Autonomous Cyber Defense
The increasing instances of advanced attacks call for a new defense paradigm that is active, autonomous, and adaptive, named as the ‘3A’ defense...
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Vulnerability Assessment Framework Based on In-The-Wild Exploitability for Prioritizing Patch Application in Control System
With the increasing understanding of attackers towards the characteristics of control systems and the growing connectivity with information...
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Adversarial defence by learning differentiated feature representation in deep ensemble
Deep learning models have been shown to be vulnerable to critical attacks under adversarial conditions. Attackers are able to generate powerful...
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Securing recommender system via cooperative training
Recommender systems are often susceptible to well-crafted fake profiles, leading to biased recommendations. Among existing defense methods,...
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Cyber Deception Techniques, Strategies, and Human Aspects
This book introduces recent research results for cyber deception, a promising field for proactive cyber defense. The beauty and challenge of cyber...
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Conventional Defense Technologies
From the perspective of technology, the current cyberspace defense methods fall into three categories: the first category focuses on the protection...
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Deep learning adversarial attacks and defenses on license plate recognition system
The breakthroughs in Machine learning and deep neural networks have revolutionized the handling of critical practical challenges, achieving...
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AI-Enabled Cybersecurity for IoT and Smart City Applications
AI-driven cybersecurity is crucial to enhancing the resilience of the Internet of Things (IoT) and smart city ecosystems. Due to the dynamic and...