This article discusses the use of biometrics in personal and enterprise applications, and the security challenges that come with it. It also highlights the…
Browsing: Adversarial Attacks
The article discusses the vulnerability of machine learning methods, particularly deep neural networks, to adversarial attacks. These attacks can drastically affect the accuracy of…
This article discusses the growing use of artificial intelligence (AI) in various industries, including healthcare, financial technology, and cybersecurity. While AI has many benefits,…
This article discusses the risks associated with machine learning-based intrusion detection models, including non-explainable results and adversarial attacks. It also explores new advanced protections…
This Special Issue focuses on the most recent advances in the models, algorithms, theories, and applications of Graph Machine Learning (GML), both in academic…
Deep learning has achieved incredible successes in tasks such as image recognition, speech recognition, language translation, and autonomous driving. However, there are still many…
Intel Innovation 2023 showcased a range of cutting-edge technologies, including a method to protect computer vision systems from adversarial attacks, Neural Object Cloning to…
Researchers at EPFL have developed a new training approach to ensure that machine learning models, particularly deep neural networks, consistently perform as intended, significantly…
Researchers at EPFL have developed a new training approach to ensure that machine learning models, particularly deep neural networks, consistently perform as intended, significantly…
Our research team is looking into ways to use quantum computing to protect machine learning frameworks from adversarial attacks. Recent advances in quantum computing…