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08/21/2023
Using Large Language Models for Cybersecurity Capture-The-Flag Challenges and Certification Questions
The assessment of cybersecurity Capture-The-Flag (CTF) exercises involve...
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06/02/2023
Adaptive Attractors: A Defense Strategy against ML Adversarial Collusion Attacks
In the seller-buyer setting on machine learning models, the seller gener...
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05/10/2023
Finding Meaningful Distributions of ML Black-boxes under Forensic Investigation
Given a poorly documented neural network model, we take the perspective ...
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12/31/2022
Tracing the Origin of Adversarial Attack for Forensic Investigation and Deterrence
Deep neural networks are vulnerable to adversarial attacks. In this pape...
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12/01/2022
Purifier: Defending Data Inference Attacks via Transforming Confidence Scores
Neural networks are susceptible to data inference attacks such as the me...
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08/03/2022
Mixed Fault Tolerance Protocols with Trusted Execution Environment
Blockchain systems are designed, built and operated in the presence of f...
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06/27/2022
De-END: Decoder-driven Watermarking Network
With recent advances in machine learning, researchers are now able to so...
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05/03/2022
Scalable Private Decision Tree Evaluation with Sublinear Communication
Private decision tree evaluation (PDTE) allows a decision tree holder to...
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11/30/2021
Mitigating Adversarial Attacks by Distributing Different Copies to Different Users
Machine learning models are vulnerable to adversarial attacks. In this p...
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07/27/2021
Poisoning of Online Learning Filters: DDoS Attacks and Countermeasures
The recent advancements in machine learning have led to a wave of intere...
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12/12/2020
Filtering DDoS Attacks from Unlabeled Network Traffic Data Using Online Deep Learning
DDoS attacks are simple, effective, and still pose a significant threat ...
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06/06/2020
SHADOWCAST: Controlling Network Properties to Explain Graph Generation
We introduce the problem of explaining graph generation, formulated as c...
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05/08/2020
Defending Model Inversion and Membership Inference Attacks via Prediction Purification
Neural networks are susceptible to data inference attacks such as the mo...
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04/24/2020
Benefits and Pitfalls of Using Capture the Flag Games in University Courses
The concept of Capture the Flag (CTF) games for practicing cybersecurity...
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03/05/2020
Detection and Recovery of Adversarial Attacks with Injected Attractors
Many machine learning adversarial attacks find adversarial samples of a ...
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11/21/2019
Self-Expiring Data Capsule using Trusted Execution Environment
Data privacy is unarguably of extreme importance. Nonetheless, there exi...
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06/14/2019
Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking
The rise of machine learning as a service and model sharing platforms ha...
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06/01/2019
Enhancing Transformation-based Defenses using a Distribution Classifier
Adversarial attacks on convolutional neural networks (CNN) have gained s...
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05/15/2019
Autonomous Membership Service for Enclave Applications
Trusted Execution Environment, or enclave, promises to protect data conf...
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02/22/2019
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment
The rise of deep learning technique has raised new privacy concerns abou...
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08/29/2018
Fair Marketplace for Secure Outsourced Computations
The cloud computing paradigm offers clients ubiquitous and on demand acc...
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04/02/2018
Chain of Trust: Can Trusted Hardware Help Scaling Blockchains?
As blockchain systems proliferate, there remains an unresolved scalabili...
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02/13/2018
Learning Inverse Mappings with Adversarial Criterion
We propose a flipped-Adversarial AutoEncoder (FAAE) that simultaneously ...
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03/03/2010