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20202026
most citedExplainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges

43 citations · 145 across the 15 of their papers we have counts for

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14 papers · 1 filter

cs.CR2026

Malformer: A Multi-Modal Malware Detector Using Transformers

Samuel Howard, Kshitiz Aryal, Mahmoud Abdelsalam +3

Traditional malware detection systems that rely on a single representation of malware often fail to identify novel threats. These representations of malware binaries, also known as…

cs.CR2024★ 43 cited

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

Harikha Manthena, Shaghayegh Shajarian, Jeffrey Kimmell +3

Machine learning (ML) has rapidly advanced in recent years, revolutionizing fields such as finance, medicine, and cybersecurity. In malware detection, ML-based approaches have demo…

cs.CR2024

Explainability Guided Adversarial Evasion Attacks on Malware Detectors

Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam +1

As the focus on security of Artificial Intelligence (AI) is becoming paramount, research on crafting and inserting optimal adversarial perturbations has become increasingly critica…

cs.CR2024

SoK: Leveraging Transformers for Malware Analysis

Pradip Kunwar, Kshitiz Aryal, Maanak Gupta +2

The introduction of transformers has been an important breakthrough for AI research and application as transformers are the foundation behind Generative AI. A promising application…

cs.CR2024★ 4 cited

Intra-Section Code Cave Injection for Adversarial Evasion Attacks on Windows PE Malware File

Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam +1

Windows malware is predominantly available in cyberspace and is a prime target for deliberate adversarial evasion attacks. Although researchers have investigated the adversarial ma…

cs.CR2023★ 4 cited

Automated Machine Learning for Deep Learning based Malware Detection

Austin Brown, Maanak Gupta, Mahmoud Abdelsalam

Deep learning (DL) has proven to be effective in detecting sophisticated malware that is constantly evolving. Even though deep learning has alleviated the feature engineering probl…

cs.CR2023★ 2 cited

Analysis of Label-Flip Poisoning Attack on Machine Learning Based Malware Detector

Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam

With the increase in machine learning (ML) applications in different domains, incentives for deceiving these models have reached more than ever. As data is the core backbone of ML…

cs.CR2022

Online Malware Classification with System-Wide System Calls in Cloud IaaS

Phillip Brown, Austin Brown, Maanak Gupta +1

Accurately classifying malware in an environment allows the creation of better response and remediation strategies by cyber analysts. However, classifying malware in a live environ…

cs.CR2022★ 8 cited

Machine Learning in Access Control: A Taxonomy and Survey

Mohammad Nur Nobi, Maanak Gupta, Lopamudra Praharaj +3

An increasing body of work has recognized the importance of exploiting machine learning (ML) advancements to address the need for efficient automation in extracting access control…

cs.CR2021★ 21 cited

A Survey on Adversarial Attacks for Malware Analysis

Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam

Machine learning has witnessed tremendous growth in its adoption and advancement in the last decade. The evolution of machine learning from traditional algorithms to modern deep le…

cs.CR2021

Autoencoder-based Anomaly Detection in Smart Farming Ecosystem

Mary Adkisson, Jeffrey C Kimmel, Maanak Gupta +1

The inclusion of Internet of Things (IoT) devices is growing rapidly in all application domains. Smart Farming supports devices connected, and with the support of Internet, cloud o…

cs.CR2021

Analyzing Machine Learning Approaches for Online Malware Detection in Cloud

Jeffrey C Kimmell, Mahmoud Abdelsalam, Maanak Gupta

The variety of services and functionality offered by various cloud service providers (CSP) have exploded lately. Utilizing such services has created numerous opportunities for ente…

cs.CR2020★ 2 cited

AI assisted Malware Analysis: A Course for Next Generation Cybersecurity Workforce

Maanak Gupta, Sudip Mittal, Mahmoud Abdelsalam

The use of Artificial Intelligence (AI) and Machine Learning (ML) to solve cybersecurity problems has been gaining traction within industry and academia, in part as a response to w…

cs.CR2020★ 30 cited

Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS

Andrew McDole, Mahmoud Abdelsalam, Maanak Gupta +1

Cloud Infrastructure as a Service (IaaS) is vulnerable to malware due to its exposure to external adversaries, making it a lucrative attack vector for malicious actors. A datacente…