Cover Image

Ranking-Enhanced Anomaly Detection Using Active Learning-Assisted Attention Adversarial Dual AutoEncoders

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Benabderrahmane, Sidahmed, Cheney, James, Rahwan, Talal
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Refining Decision Boundaries In Anomaly Detection Using Similarity Search Within the Feature Space
by: Benabderrahmane, Sidahmed, et al.
Published: (2026)

From One Attack Domain to Another: Contrastive Transfer Learning with Siamese Networks for APT Detection
by: Benabderrahmane, Sidahmed, et al.
Published: (2025)

RPG-AE: Neuro-Symbolic Graph Autoencoders with Rare Pattern Mining for Provenance-Based Anomaly Detection
by: Tauhid, Asif, et al.
Published: (2026)

Hack Me If You Can: Aggregating AutoEncoders for Countering Persistent Access Threats Within Highly Imbalanced Data
by: Benabderrahmane, Sidahmed, et al.
Published: (2024)

Metric Matters: A Formal Evaluation of Similarity Measures in Active Learning for Cyber Threat Intelligence
by: Benabderrahmane, Sidahmed, et al.
Published: (2025)

Adversarial Augmentation and Active Sampling for Robust Cyber Anomaly Detection
by: Benabderrahmane, Sidahmed, et al.
Published: (2025)

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models
by: Benabderrahmane, Sidahmed, et al.
Published: (2025)

Attackers Strike Back? Not Anymore -- An Ensemble of RL Defenders Awakens for APT Detection
by: Benabderrahmane, Sidahmed, et al.
Published: (2025)

Rectifying Adversarial Examples Using Their Vulnerabilities
by: Morimoto, Fumiya, et al.
Published: (2026)

Hybrid Deep Learning Model for Multiple Cache Side Channel Attacks Detection: A Comparative Analysis
by: Joshi, Tejal, et al.
Published: (2025)

Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience
by: Liu, Ao, et al.
Published: (2023)

Guiding Evolutionary AutoEncoder Training with Activation-Based Pruning Operators
by: Jorgensen, Steven, et al.
Published: (2025)

On the Adversarial Robustness of Spiking Neural Networks Trained by Local Learning
by: Lin, Jiaqi, et al.
Published: (2025)

Privacy-Preserving Distributed Optimization Under Time Constraints Using Secure Multi-Party Computation and Evolutionary Algorithms
by: Gruber, Sebastian, et al.
Published: (2026)

Evasive Active Hypothesis Testing with Deep Neuroevolution: The Single- and Multi-Agent Cases
by: Stamatelis, George, et al.
Published: (2024)

Your Network May Need to Be Rewritten: Network Adversarial Based on High-Dimensional Function Graph Decomposition
by: Su, Xiaoyan, et al.
Published: (2024)

Data Poisoning-based Backdoor Attack Framework against Supervised Learning Rules of Spiking Neural Networks
by: Jin, Lingxin, et al.
Published: (2024)

MALT Powers Up Adversarial Attacks
by: Melamed, Odelia, et al.
Published: (2024)

Boosting Adversarial Robustness and Generalization with Structural Prior
by: Hou, Zhichao, et al.
Published: (2025)

Adversarially Robust Spiking Neural Networks with Sparse Connectivity
by: Schmolli, Mathias, et al.
Published: (2025)

Impact of White-Box Adversarial Attacks on Convolutional Neural Networks
by: Podder, Rakesh, et al.
Published: (2024)

Enhance the machine learning algorithm performance in phishing detection with keyword features
by: Yang, Zijiang
Published: (2025)

Enhancing IoT Security: A Novel Feature Engineering Approach for ML-Based Intrusion Detection Systems
by: Mahanipour, Afsaneh, et al.
Published: (2024)

A Homomorphic Encryption Framework for Privacy-Preserving Spiking Neural Networks
by: Nikfam, Farzad, et al.
Published: (2023)

Monotone but Exciting: On Evolving Monotone Boolean Functions with High Nonlinearity
by: Carlet, Claude, et al.
Published: (2026)

Degree is Important: On Evolving Homogeneous Boolean Functions
by: Carlet, Claude, et al.
Published: (2025)

IDEM Enough? Evolving Highly Nonlinear Idempotent Boolean Functions
by: Carlet, Claude, et al.
Published: (2026)

A Systematic Evaluation of Evolving Highly Nonlinear Boolean Functions in Odd Sizes
by: Carlet, Claude, et al.
Published: (2024)

Proof-of-Useful-Work Blockchain for Trustworthy Biomedical Hyperdimensional Computing
by: Wen, Jinghao, et al.
Published: (2022)

A Systematic Study on the Design of Odd-Sized Highly Nonlinear Boolean Functions via Evolutionary Algorithms
by: Carlet, Claude, et al.
Published: (2025)

NegaBent, No Regrets: Evolving Spectrally Flat Boolean Functions
by: Carlet, Claude, et al.
Published: (2026)

On Counts and Densities of Homogeneous Bent Functions: An Evolutionary Approach
by: Carlet, Claude, et al.
Published: (2025)

A Discrete Particle Swarm Optimizer for the Design of Cryptographic Boolean Functions
by: Mariot, Luca, et al.
Published: (2024)

Adapting Novelty towards Generating Antigens for Antivirus systems
by: Murali, Ritwik, et al.
Published: (2025)

A systematic review of metaheuristics-based and machine learning-driven intrusion detection systems in IoT
by: Ahsan, Mohammad Shamim, et al.
Published: (2025)

Differential Privacy in Machine Learning: A Survey from Symbolic AI to LLMs
by: Aguilera-Martínez, Francisco, et al.
Published: (2025)

CEPA: Consensus Embedded Perturbation for Agnostic Detection and Inversion of Backdoors
by: Yang, Guangmingmei, et al.
Published: (2024)

Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys
by: Ngo, Huy Q., et al.
Published: (2024)

Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent
by: Kummer, Lorenz, et al.
Published: (2023)

Use of Graph Neural Networks in Aiding Defensive Cyber Operations
by: Mitra, Shaswata, et al.
Published: (2024)