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06/15/2022
Morphence-2.0: Evasion-Resilient Moving Target Defense Powered by Out-of-Distribution Detection
Evasion attacks against machine learning models often succeed via iterat...
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03/02/2022
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members
In membership inference attacks (MIAs), an adversary observes the predic...
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02/18/2022
Rethinking Machine Learning Robustness via its Link with the Out-of-Distribution Problem
Despite multiple efforts made towards robust machine learning (ML) model...
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12/24/2021
DP-UTIL: Comprehensive Utility Analysis of Differential Privacy in Machine Learning
Differential Privacy (DP) has emerged as a rigorous formalism to reason ...
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08/31/2021
Morphence: Moving Target Defense Against Adversarial Examples
Robustness to adversarial examples of machine learning models remains an...
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08/31/2021
EG-Booster: Explanation-Guided Booster of ML Evasion Attacks
The widespread usage of machine learning (ML) in a myriad of domains has...
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06/30/2021
Explanation-Guided Diagnosis of Machine Learning Evasion Attacks
Machine Learning (ML) models are susceptible to evasion attacks. Evasion...
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02/19/2021
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party Setting
When multiple parties that deal with private data aim for a collaborativ...
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06/28/2020
Best-Effort Adversarial Approximation of Black-Box Malware Classifiers
An adversary who aims to steal a black-box model repeatedly queries the ...
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09/30/2019
POIROT: Aligning Attack Behavior with Kernel Audit Records for Cyber Threat Hunting
Cyber threat intelligence (CTI) is being used to search for indicators o...
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10/12/2018
ProPatrol: Attack Investigation via Extracted High-Level Tasks
Kernel audit logs are an invaluable source of information in the forensi...
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10/03/2018
HOLMES: Real-time APT Detection through Correlation of Suspicious Information Flows
This version withdrawn by arXiv administrators because the author did no...
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01/06/2018