Machine learning has evolved into an enabling technology for a wide range of highly
successful applications. The potential for this success to continue and accelerate has placed …

Speech and speaker recognition systems are employed in a variety of applications, from
personal assistants to telephony surveillance and biometric authentication. The wide …

Adversarial examples are inputs to machine learning models designed by an adversary to
cause an incorrect output. So far, adversarial examples have been studied most extensively …

Speaker recognition (SR) is widely used in our daily life as a biometric authentication or
identification mechanism. The popularity of SR brings in serious security concerns, as …

Abstract Modern-day Connected and Autonomous Vehicles (CAVs) with more than 100
million code lines, running up-to a hundred Electronic Control Units (ECUs) will create and …

We propose a new class of signal injection attacks on microphones by physically converting
light to sound. We show how an attacker can inject arbitrary audio signals to a target …

Voice interfaces are becoming accepted widely as input methods for a diverse set of
devices. This development is driven by rapid improvements in automatic speech recognition …

While Deep Reinforcement Learning (DRL) has achieved outstanding performance in
extensive applications, exploiting its vulnerability with adversarial attacks is essential …

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 …

Voice is a behavioral biometric that conveys information related to a person's traits, such as
the speaker's ethnicity, age, gender, and feeling. Speaker recognition deals with recognizing …