Software verification and validation of safe autonomous cars: A systematic literature review
Autonomous, or self-driving, cars are emerging as the solution to several problems primarily
caused by humans on roads, such as accidents and traffic congestion. However, those …
caused by humans on roads, such as accidents and traffic congestion. However, those …
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning
Despite the rapid increase of data available to train machine-learning algorithms in many
domains, several applications suffer from a paucity of representative and diverse data. The …
domains, several applications suffer from a paucity of representative and diverse data. The …
Av-fuzzer: Finding safety violations in autonomous driving systems
This paper proposes AV-FUZZER, a testing framework, to find the safety violations of an
autonomous vehicle (AV) in the presence of an evolving traffic environment. We perturb the …
autonomous vehicle (AV) in the presence of an evolving traffic environment. We perturb the …
The security of autonomous driving: Threats, defenses, and future directions
Autonomous vehicles (AVs) have promised to drastically improve the convenience of driving
by releasing the burden of drivers and reducing traffic accidents with more precise control …
by releasing the burden of drivers and reducing traffic accidents with more precise control …
Dirty road can attack: Security of deep learning based automated lane centering under {Physical-World} attack
Automated Lane Centering (ALC) systems are convenient and widely deployed today, but
also highly security and safety critical. In this work, we are the first to systematically study the …
also highly security and safety critical. In this work, we are the first to systematically study the …
Towards low-latency service delivery in a continuum of virtual resources: State-of-the-art and research directions
The advent of softwarized networks has enabled the deployment of chains of virtual network
and service components on computational resources from the cloud up to the edge, creating …
and service components on computational resources from the cloud up to the edge, creating …
Patchattack: A black-box texture-based attack with reinforcement learning
Patch-based attacks introduce a perceptible but localized change to the input that induces
misclassification. A limitation of current patch-based black-box attacks is that they perform …
misclassification. A limitation of current patch-based black-box attacks is that they perform …
Who is in control? practical physical layer attack and defense for mmwave-based sensing in autonomous vehicles
With the wide bandwidths in millimeter wave (mmWave) frequency band that results in
unprecedented accuracy, mmWave sensing has become vital for many applications …
unprecedented accuracy, mmWave sensing has become vital for many applications …
[PDF][PDF] Evasion attacks and defenses on smart home physical event verification
In smart homes, when an actuator's state changes, it sends an event notification to the IoT
hub to report this change (eg, the door is unlocked). Prior works have shown that event …
hub to report this change (eg, the door is unlocked). Prior works have shown that event …
[HTML][HTML] An architecture-level analysis on deep learning models for low-impact computations
Deep neural networks (DNNs) have made significant achievements in a wide variety of
domains. For the deep learning tasks, multiple excellent hardware platforms provide efficient …
domains. For the deep learning tasks, multiple excellent hardware platforms provide efficient …