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Safety-critical computer vision: an empirical survey of adversarial evasion attacks and defenses on computer vision systems
Considering the growing prominence of production-level AI and the threat of adversarial attacks that can poison a machine learning model against a...
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Evaluation of neural networks defenses and attacks using NDCG and reciprocal rank metrics
The problem of attacks on neural networks through input modification (i.e., adversarial examples) has attracted much attention recently. Being...
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Adversarial attacks and defenses for large language models (LLMs): methods, frameworks & challenges
Large language models (LLMs) have exhibited remarkable efficacy and proficiency in a wide array of NLP endeavors. Nevertheless, concerns are growing...
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State of the art on adversarial attacks and defenses in graphs
Graph neural networks (GNNs) had shown excellent performance in complex graph data modelings such as node classification, link prediction and graph...
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Intelligent Malware Defenses
With rapidly evolving threat landscape surrounding malware, intelligent defenses based on machine learning are paramount. In this chapter, we review...
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Understanding deep learning defenses against adversarial examples through visualizations for dynamic risk assessment
In recent years, deep neural network models have been developed in different fields, where they have brought many advances. However, they have also...
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Attacks and Defenses of Smart Speakers: Voice Command Fingerprinting on Alexa
Smart speakers, such as Amazon Alexa and Google Home, are a form of voice-based interactive technology that helps consumers solve queries with...
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Stronger data poisoning attacks break data sanitization defenses
Machine learning models trained on data from the outside world can be corrupted by data poisoning attacks that inject malicious points into the...
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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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Threats, attacks and defenses to federated learning: issues, taxonomy and perspectives
Empirical attacks on Federated Learning (FL) systems indicate that FL is fraught with numerous attack surfaces throughout the FL execution. These...
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Towards Effective and Robust Neural Trojan Defenses via Input Filtering
Trojan attacks on deep neural networks are both dangerous and surreptitious. Over the past few years, Trojan attacks have advanced from using only a...
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Adversarial Attacks and Defenses in Capsule Networks: A Critical Review of Robustness Challenges and Mitigation Strategies
Capsule Networks (CapsNets) have gained significant attention in recent years due to their potential for improved representation learning and...
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Synthesis of Optimal Defenses for System Architecture Design Model in MaxSMT
Attack-Defense Trees (ADTrees) are widely used in the security analysis of software systems. In this paper, we introduce a novel approach to analyze...
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Effective and Lightweight Defenses Against Website Fingerprinting on Encrypted Traffic
Recently, website fingerprinting (WF) attacks that eavesdrop on the web browsing activity of users by analyzing the observed traffic can endanger the...
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Data Poisoning Attack and Defenses in Connectome-Based Predictive Models
Connectome-based predictive models are widely used in the neuroimaging community and hold great clinical potential. Recent literature has focused on...
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A survey on adversarial attacks and defenses for object detection and their applications in autonomous vehicles
Object detection is considered as one of the most important applications of deep learning. However, the object detection techniques lose their...
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Real-Time Adversarial Perturbations Against Deep Reinforcement Learning Policies: Attacks and Defenses
Deep reinforcement learning (DRL) is vulnerable to adversarial perturbations. Adversaries can mislead the policies of DRL agents by perturbing the...
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Visual privacy attacks and defenses in deep learning: a survey
The concerns on visual privacy have been increasingly raised along with the dramatic growth in image and video capture and sharing. Meanwhile, with...
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Hybrid AI-Based iBeacon Indoor Positioning Cybersecurity Attacks and Defenses Thereof
Currently, iBeacon systems have been increasingly established in public areas to position people and assist users in indoor for location navigation....