Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier
days of conceptual theories, to being an integral part of today's technological society. Rapid …

As the adoption of explainable AI (XAI) continues to expand, the urgency to address its
privacy implications intensifies. Despite a growing corpus of research in AI privacy and …

The “black-box” nature of artificial intelligence (AI) models has been the source of many
concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a …

Machine Learning methods are playing a vital role in combating ever-evolving threats in the
cybersecurity domain. Explanation methods that shed light on the decision process of black …

As the adoption of explainable AI (XAI) continues to expand, the urgency to address its
privacy implications intensifies. Despite a growing corpus of research in AI privacy and …

Machine learning techniques are increasingly used for high-stakes decision-making, such
as college admissions, loan attribution or recidivism prediction. Thus, it is crucial to ensure …

We assess the security of machine learning based biometric authentication systems against
an attacker who submits uniform random inputs, either as feature vectors or raw inputs, in …

The black-box nature of artificial intelligence (AI) models has been the source of many
concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a …

Motivated by mitigating potentially harmful impacts of technologies, the AI community has
formulated and accepted mathematical definitions for certain pillars of accountability: eg …

Machine learning techniques are increasingly used for high-stakes decision making, such
as college admissions, loan attribution or recidivism prediction. It is thus crucial to ensure …