Facial recognition systems are increasingly deployed by private corporations, government
agencies, and contractors for consumer services and mass surveillance programs alike …

Data poisoning and backdoor attacks manipulate victim models by maliciously modifying
training data. In light of this growing threat, a recent survey of industry professionals …

Deep neural networks have been shown to be susceptible to adversarial examples–small,
imperceptible changes constructed to cause mis-classification in otherwise highly accurate …

Data Poisoning Attacks (DPA) represent a sophisticated technique aimed at distorting the
training data of machine learning models, thereby manipulating their behavior. This process …

Algorithmic trading systems are often completely automated, and deep learning is
increasingly receiving attention in this domain. Nonetheless, little is known about the …

Deep neural network (DNN) accelerators received considerable attention in recent years
due to the potential to save energy compared to mainstream hardware. Low-voltage …

Audio classification aims at recognizing audio signals, including speech commands or
sound events. However, current audio classifiers are susceptible to perturbations and …

Exploring the idea of phase retrieval has been intriguing researchers for decades, due to its
appearance in a wide range of applications. The task of a phase retrieval algorithm is …

Machine learning (ML) has been successfully applied to classification tasks in many
domains, including computer vision, cybersecurity, and communications. Although highly …

To monitor the activity over a radio frequency (RF) channel and coordinate its access among
heterogeneous wireless systems, network administrators and/or users must be able to …