6 citations · 16 across the 11 of their papers we have counts for
11 papers
Sidecars on the Central Lane: Impact of Network Proxies on Microservices
Prateek Sahu, Lucy Zheng, Marco Bueso +3
Cloud applications are moving away from monolithic model towards loosely-coupled microservices designs. Service meshes are widely used for implementing microservices applications m…
Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies
Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar
Modern software systems rely on mining insights from business sensitive data stored in public clouds. A data breach usually incurs significant (monetary) loss for a commercial orga…
Bandwidth Utilization Side-Channel on ML Inference Accelerators
Sarbartha Banerjee, Shijia Wei, Prakash Ramrakhyani +1
Accelerators used for machine learning (ML) inference provide great performance benefits over CPUs. Securing confidential model in inference against off-chip side-channel attacks i…
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
Wenxi Wang, Yang Hu, Mohit Tiwari +3
Propositional satisfiability (SAT) is an NP-complete problem that impacts many research fields, such as planning, verification, and security. Mainstream modern SAT solvers are base…
Power-Based Attacks on Spatial DNN Accelerators
Ge Li, Mohit Tiwari, Michael Orshansky
With proliferation of DNN-based applications, the confidentiality of DNN model is an important commercial goal. Spatial accelerators, that parallelize matrix/vector operations, are…
Challenges in cybersecurity: Lessons from biological defense systems
Edward Schrom, Ann Kinzig, Stephanie Forrest +18
We explore the commonalities between methods for assuring the security of computer systems (cybersecurity) and the mechanisms that have evolved through natural selection to protect…
SESAME: Software defined Enclaves to Secure Inference Accelerators with Multi-tenant Execution
Sarbartha Banerjee, Prakash Ramrakhyani, Shijia Wei +1
Hardware-enclaves that target complex CPU designs compromise both security and performance. Programs have little control over micro-architecture, which leads to side-channel leaks,…
The Shape of Alerts: Detecting Malware Using Distributed Detectors by Robustly Amplifying Transient Correlations
Mikhail Kazdagli, Constantine Caramanis, Sanjay Shakkottai +1
We introduce a new malware detector - Shape-GD - that aggregates per-machine detectors into a robust global detector. Shape-GD is based on two insights: 1. Structural: actions such…
Exploiting Latent Attack Semantics for Intelligent Malware Detection
Mkhail Kazdagli, Constantine Caramanis, Sanjay Shakkottai +1
Behavioral malware detectors promise to expose previously unknown malware and are an important security primitive. However, even the best behavioral detectors suffer from high fals…
EMMA: A New Platform to Evaluate Hardware-based Mobile Malware Analyses
Mikhail Kazdagli, Ling Huang, Vijay Reddi +1
Hardware-based malware detectors (HMDs) are a key emerging technology to build trustworthy computing platforms, especially mobile platforms. Quantifying the efficacy of HMDs agains…
Language Without Words: A Pointillist Model for Natural Language Processing
Peiyou Song, Anhei Shu, David Phipps +4
This paper explores two separate questions: Can we perform natural language processing tasks without a lexicon?; and, Should we? Existing natural language processing techniques are…