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09/18/2023
Realistic Website Fingerprinting By Augmenting Network Trace
Website Fingerprinting (WF) is considered a major threat to the anonymit...
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03/08/2023
On the Risks of Stealing the Decoding Algorithms of Language Models
A key component of generating text from modern language models (LM) is t...
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12/04/2022
Security Analysis of SplitFed Learning
Split Learning (SL) and Federated Learning (FL) are two prominent distri...
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11/01/2022
The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning
Semi-supervised machine learning (SSL) is gaining popularity as it reduc...
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05/20/2022
E2FL: Equal and Equitable Federated Learning
Federated Learning (FL) enables data owners to train a shared global mod...
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10/15/2021
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture
Membership inference attacks are a key measure to evaluate privacy leaka...
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10/08/2021
FSL: Federated Supermask Learning
Federated learning (FL) allows multiple clients with (private) data to c...
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08/27/2021
Superstring-Based Sequence Obfuscation to Thwart Pattern Matching Attacks
User privacy can be compromised by matching user data traces to records ...
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08/23/2021
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Federated Learning
While recent works have indicated that federated learning (FL) is vulner...
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02/01/2021
Robust Adversarial Attacks Against DNN-Based Wireless Communication Systems
Deep Neural Networks (DNNs) have become prevalent in wireless communicat...
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07/22/2020
Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising
Deep learning models leak significant amounts of information about their...
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07/12/2020
Asymptotic Privacy Loss due to Time Series Matching of Dependent Users
The Internet of Things (IoT) promises to improve user utility by tuning ...
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05/01/2020
Practical Traffic Analysis Attacks on Secure Messaging Applications
Instant Messaging (IM) applications like Telegram, Signal, and WhatsApp ...
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02/16/2020
Blind Adversarial Network Perturbations
Deep Neural Networks (DNNs) are commonly used for various traffic analys...
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12/24/2019
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer
Collaborative (federated) learning enables multiple parties to train a m...
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12/04/2019
Leveraging Prior Knowledge Asymmetries in the Design of Location Privacy-Preserving Mechanisms
The prevalence of mobile devices and Location-Based Services (LBS) neces...
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06/15/2019
Reconciling Utility and Membership Privacy via Knowledge Distillation
Large capacity machine learning models are prone to membership inference...
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03/27/2019
Fundamental Limits of Covert Packet Insertion
Covert communication conceals the existence of the transmission from a w...
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02/18/2019
Asymptotic Limits of Privacy in Bayesian Time Series Matching
Various modern and highly popular applications make use of user data tra...
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12/03/2018
Comprehensive Privacy Analysis of Deep Learning: Stand-alone and Federated Learning under Passive and Active White-box Inference Attacks
Deep neural networks are susceptible to various inference attacks as the...
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10/08/2018
Fundamental Limits of Covert Bit Insertion in Packets
Covert communication is necessary when revealing the mere existence of a...
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09/27/2018
Asymptotic Loss in Privacy due to Dependency in Gaussian Traces
Rapid growth of the Internet of Things (IoT) necessitates employing priv...
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09/23/2018
Fundamental Limits of Invisible Flow Fingerprinting
Network flow fingerprinting can be used to de-anonymize communications o...
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08/22/2018
DeepCorr: Strong Flow Correlation Attacks on Tor Using Deep Learning
Flow correlation is the core technique used in a multitude of deanonymiz...
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07/16/2018
Machine Learning with Membership Privacy using Adversarial Regularization
Machine learning models leak information about the datasets on which the...
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06/28/2018
Privacy of Dependent Users Against Statistical Matching
Modern applications significantly enhance user experience by adapting to...
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05/02/2018
Privacy against Statistical Matching: Inter-User Correlation
Modern applications significantly enhance user experience by adapting to...
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11/28/2017
Towards Provably Invisible Network Flow Fingerprints
Network traffic analysis reveals important information even when message...
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09/12/2017