Security through the Eyes of AI: How Visualization is Shaping Malware Detection
Authors: Asmitha K. A., Matteo Brosolo, Serena Nicolazzo, Antonino Nocera, Vinod P., Rafidha Rehiman K. A., Muhammed Shafi K. P | Published: 2025-05-12
Adversarial Example Detection
Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations
Authors: Ahod Alghuried, Ali Alkinoon, Abdulaziz Alghamdi, Soohyeon Choi, Manar Mohaisen, David Mohaisen | Published: 2025-04-24
Mind the Gap: Detecting Black-box Adversarial Attacks in the Making through Query Update Analysis
Authors: Jeonghwan Park, Niall McLaughlin, Ihsen Alouani | Published: 2025-03-04 | Updated: 2025-03-16
ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning
Authors: Giuseppe Floris, Christian Scano, Biagio Montaruli, Luca Demetrio, Andrea Valenza, Luca Compagna, Davide Ariu, Luca Piras, Davide Balzarotti, Battista Biggio | Published: 2023-08-09 | Updated: 2025-05-21
Towards A Conceptually Simple Defensive Approach for Few-shot classifiers Against Adversarial Support Samples
Authors: Yi Xiang Marcus Tan, Penny Chong, Jiamei Sun, Ngai-man Cheung, Yuval Elovici, Alexander Binder | Published: 2021-10-24
Adversarial Example Detection for DNN Models: A Review and Experimental Comparison
Authors: Ahmed Aldahdooh, Wassim Hamidouche, Sid Ahmed Fezza, Olivier Deforges | Published: 2021-05-01 | Updated: 2022-01-07
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT
Authors: Pavlos Papadopoulos, Oliver Thornewill von Essen, Nikolaos Pitropakis, Christos Chrysoulas, Alexios Mylonas, William J. Buchanan | Published: 2021-04-26
Random Noise Defense Against Query-Based Black-Box Attacks
Authors: Zeyu Qin, Yanbo Fan, Hongyuan Zha, Baoyuan Wu | Published: 2021-04-23 | Updated: 2021-10-30
Performance Evaluation of Adversarial Attacks: Discrepancies and Solutions
Authors: Jing Wu, Mingyi Zhou, Ce Zhu, Yipeng Liu, Mehrtash Harandi, Li Li | Published: 2021-04-22
Jacobian Regularization for Mitigating Universal Adversarial Perturbations
Authors: Kenneth T. Co, David Martinez Rego, Emil C. Lupu | Published: 2021-04-21 | Updated: 2021-09-13