Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges

Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges

Machine learning (ML) has rapidly advanced in recent years, revolutionizing fields such as finance, medicine, and cybersecurity. In malware detection, ML-based approaches have demonstrated high accuracy; however, their lack of transparency poses a significant challenge. Traditional ML models often f...

Full description

Saved in:

Bibliographic Details
Main Authors:	Harikha Manthena, Shaghayegh Shajarian, Jeffrey C. Kimmell, Mahmoud Abdelsalam, Sajad Khorsandroo, Maanak Gupta
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Explainable malware analysis interpretable malware analysis explainable AI AI for security malware detection malware classification
Online Access:	https://ieeexplore.ieee.org/document/10944807/
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Knowledge-infused and Explainable Malware Forensics
by: Neha Mohan Kumar, et al.
Published: (2024-05-01)

A Survey on Adversarial Attacks for Malware Analysis
by: Kshitiz Aryal, et al.
Published: (2025-01-01)

A Review of Explainable AI for Android Malware Detection and Analysis
by: Maryam Tanha, et al.
Published: (2025-01-01)

Multimodal and Explainable Android Adware Classification Techniques
by: Momoreoluwa Ayinde, et al.
Published: (2024-05-01)

Android Malware Category and Family Identification Using Parallel Machine Learning
by: Ahmed Hashem El Fiky, et al.
Published: (2022-07-01)

OPTISTACK: A Hybrid Ensemble Learning and XAI-Based Approach for Malware Detection in Compressed Files
by: Khaled Mahmud Sujon, et al.
Published: (2025-01-01)

A Review of the Recent Trends in Mobile Malware Evolution, Detection, and Analysis
by: Seetah Almarri, et al.
Published: (2025-01-01)

Application of deep learning in malware detection: a review
by: Yafei Song, et al.
Published: (2025-04-01)

Evaluating Lightweight Transformers With Local Explainability for Android Malware Detection
by: Fatima Bourebaa, et al.
Published: (2025-01-01)

An Explainable Hybrid CNN–Transformer Architecture for Visual Malware Classification
by: Mohammed Alshomrani, et al.
Published: (2025-07-01)

A Robust and Efficient Machine Learning Framework for Enhancing Early Detection of Android Malware
by: Fandi Kurniawan, et al.
Published: (2025-01-01)

Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques
by: Yadigar Imamverdiyev, et al.
Published: (2025-01-01)

I-MCM: IoT Malware Counter Measures for Cross-Architecture IoT Malware Detection
by: Ibrahim Gulatas, et al.
Published: (2025-01-01)

HoneyBow:an automated malware collection tool based on the high-interaction honeypot principle
by: ZHUGE Jian-wei1, et al.
Published: (2007-01-01)

Enhancing the Sustainability of Machine Learning-Based Malware Detection Techniques for Android Applications
by: Seyeon Park, et al.
Published: (2025-01-01)

CLASSIFYING ANDROID MALWARE CATEGORIES BASED ON DYNAMIC FEATURES: AN INTEGRATION OF FEATURE REDUCTION AND SELECTION TECHNIQUES
by: abdullah alsraratee, et al.
Published: (2025-04-01)

A Review of State-of-the-Art Malware Attack Trends and Defense Mechanisms
by: Jannatul Ferdous, et al.
Published: (2023-01-01)

An extrinsic random-based ensemble approach for android malware detection
by: Nektaria Potha, et al.
Published: (2021-10-01)

Method of anti-confusion texture feature descriptor for malware images
by: Yashu LIU, et al.
Published: (2018-11-01)

MALVADA: A framework for generating datasets of malware execution traces
by: Razvan Raducu, et al.
Published: (2025-05-01)

Hybrid Android Malware Detection and Classification Using Deep Neural Networks
by: Muhammad Umar Rashid, et al.
Published: (2025-03-01)

A Survey on Android Malware Detection Techniques Using Supervised Machine Learning
by: Safa J. Altaha, et al.
Published: (2024-01-01)

ISAnWin: inductive generalized zero-shot learning using deep CNN for malware detection across windows and android platforms
by: Umm-e-Hani Tayyab, et al.
Published: (2024-12-01)

Detection of Malicious Office Open Documents (OOXML) Using Large Language Models: A Static Analysis Approach
by: Jonas Heß , et al.
Published: (2025-06-01)

Malware-SeqGuard: An Approach Utilizing LSTM and GRU for Effective Detection of Evolving Malware in Android Environments
by: Muhammad Usama Tanveer, et al.
Published: (2025-01-01)

Study on modern malware analysis system
by: Yi ZHAO, et al.
Published: (2014-10-01)

Study on modern malware analysis system
by: Yi ZHAO, et al.
Published: (2014-10-01)

Effective classification of android malware families through dynamic features and neural networks
by: Gianni D'Angelo, et al.
Published: (2021-07-01)

Multimodal malware classification using proposed ensemble deep neural network framework
by: Sadia Nazim, et al.
Published: (2025-05-01)

GCSA-ResNet: a deep neural network architecture for Malware detection
by: Yukang Fan, et al.
Published: (2025-07-01)

FLSH: A Framework Leveraging Similarity Hashing for Android Malware and Variant Detection
by: Hassan Jalil Hadi, et al.
Published: (2025-01-01)

Two stage malware detection model in internet of vehicles (IoV) using deep learning-based explainable artificial intelligence with optimization algorithms
by: Manal Abdullah Alohali, et al.
Published: (2025-07-01)

A Delayed Malware Propagation Model Under a Distributed Patching Mechanism: Stability Analysis
by: Wei Zhang, et al.
Published: (2025-07-01)

Detecting Malicious .NET Executables Using Extracted Methods Names
by: Hamdan Thabit, et al.
Published: (2025-01-01)

Is Malware Detection Needed for Android TV?
by: Gokhan Ozogur, et al.
Published: (2025-03-01)

Practical Malware Analysis
by: D. A. Elizarov, et al.
Published: (2023-10-01)

GSIDroid: A Suspicious Subgraph-Driven and Interpretable Android Malware Detection System
by: Hong Huang, et al.
Published: (2025-07-01)

LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
by: Durmus Ozkan Sahin, et al.
Published: (2022-01-01)

Elastic Shifts: I/O Sequence Patterns of Ransomware and Detection Evasion
by: Il Hyeon Ju, et al.
Published: (2025-01-01)

MalHAPGNN: An Enhanced Call Graph-Based Malware Detection Framework Using Hierarchical Attention Pooling Graph Neural Network
by: Wenjie Guo, et al.
Published: (2025-01-01)