273 citations · 914 across the 36 of their papers we have counts for
7 papers · 1 filter
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments
Alesia Chernikova, Alina Oprea
As advances in Deep Neural Networks (DNNs) demonstrate unprecedented levels of performance in many critical applications, their vulnerability to attacks is still an open question.…
AppMine: Behavioral Analytics for Web Application Vulnerability Detection
Indranil Jana, Alina Oprea
Web applications in widespread use have always been the target of large-scale attacks, leading to massive disruption of services and financial loss, as in the Equifax data breach.…
The House That Knows You: User Authentication Based on IoT Data
Talha Ongun, Oliver Spohngellert, Alina Oprea +3
Home-based Internet of Things (IoT) devices have gained in popularity and many households have become 'smart' by using devices such as smart sensors, locks, and voice-based assista…
On Designing Machine Learning Models for Malicious Network Traffic Classification
Talha Ongun, Timothy Sakharaov, Simona Boboila +2
Machine learning (ML) started to become widely deployed in cyber security settings for shortening the detection cycle of cyber attacks. To date, most ML-based systems are either pr…
QFlip: An Adaptive Reinforcement Learning Strategy for the FlipIt Security Game
Lisa Oakley, Alina Oprea
A rise in Advanced Persistent Threats (APTs) has introduced a need for robustness against long-running, stealthy attacks which circumvent existing cryptographic security guarantees…
Are Self-Driving Cars Secure? Evasion Attacks against Deep Neural Networks for Steering Angle Prediction
Alesia Chernikova, Alina Oprea, Cristina Nita-Rotaru +1
Deep Neural Networks (DNNs) have tremendous potential in advancing the vision for self-driving cars. However, the security of DNN models in this context leads to major safety impli…
Private Hierarchical Clustering and Efficient Approximation
Xianrui Meng, Dimitrios Papadopoulos, Alina Oprea +1
In collaborative learning, multiple parties contribute their datasets to jointly deduce global machine learning models for numerous predictive tasks. Despite its efficacy, this lea…