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Secret Key Extraction from Wireless Signal Strength in Real Environments
We evaluate the effectiveness of secret key extraction, for private communication between two wireless devices, from the received signal strength (RSS) variations on the wireless channel between theExpand
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DeepTest: Automated Testing of Deep-Neural-Network-Driven Autonomous Cars
Recent advances in Deep Neural Networks (DNNs) have led to the development of DNN-driven autonomous cars that, using sensors like camera, LiDAR, etc., can drive without any human intervention. MostExpand
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The most dangerous code in the world: validating SSL certificates in non-browser software
SSL (Secure Sockets Layer) is the de facto standard for secure Internet communications. Security of SSL connections against an active network attacker depends on correctly validating public-keyExpand
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DeepXplore: Automated Whitebox Testing of Deep Learning Systems
Deep learning (DL) systems are increasingly deployed in safety- and security-critical domains including self-driving cars and malware detection, where the correctness and predictability of a system'sExpand
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Certified Robustness to Adversarial Examples with Differential Privacy
Adversarial examples that fool machine learning models, particularly deep neural networks, have been a topic of intense research interest, with attacks and defenses being developed in a tightExpand
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DeepXplore: automated whitebox testing of deep learning systems
Deep learning (DL) systems are increasingly deployed in safetyand security-critical domains such as self-driving cars and malware detection, where the correctness and predictability of a system’sExpand
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High-Rate Uncorrelated Bit Extraction for Shared Secret Key Generation from Channel Measurements
Secret keys can be generated and shared between two wireless nodes by measuring and encoding radio channel characteristics without ever revealing the secret key to an eavesdropper at a thirdExpand
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Formal Security Analysis of Neural Networks using Symbolic Intervals
Due to the increasing deployment of Deep Neural Networks (DNNs) in real-world security-critical domains including autonomous vehicles and collision avoidance systems, formally checking securityExpand
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Efficient Formal Safety Analysis of Neural Networks
Neural networks are increasingly deployed in real-world safety-critical domains such as autonomous driving, aircraft collision avoidance, and malware detection. However, these networks have beenExpand
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Using Frankencerts for Automated Adversarial Testing of Certificate Validation in SSL/TLS Implementations
Modern network security rests on the Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols. Distributed systems, mobile and desktop applications, embedded devices, and all of secureExpand
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