Search Results for author:
Found 8 papers, 3 papers with code
The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices
However, recent advanced backdoor attacks show that this assumption is no longer valid in dynamic backdoors where the triggers vary from input to input, thereby defeating the existing defenses.
StyleFool: Fooling Video Classification Systems via Style Transfer
In this paper, we focus on unrestricted perturbations and propose StyleFool, a black-box video adversarial attack via style transfer to fool the video classification system.
DeFuzz: Deep Learning Guided Directed Fuzzing
Fuzzing is one of the most effective technique to identify potential software vulnerabilities.
Analysis of Trending Topics and Text-based Channels of Information Delivery in Cybersecurity
We further compare the identified 16 security categories across different sources based on their popularity and impact.
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models
First, such attacks must acquire the outputs from the models by multiple times before actually launching attacks, which is difficult for the MitM adversary in practice.
Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples
Experimental results demonstrate that the attack effectively stops NMS from filtering redundant bounding boxes.
Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection
In contrast to existing works, the adversarial examples crafted by our method can also deceive recent machine learning based detectors that rely on semantic features such as control-flow-graph.
Cryptography and Security
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training
For example, proactive defending methods are invalid against grey-box or white-box attacks, while reactive defending methods are challenged by low-distortion adversarial examples or transferring adversarial examples.
