43 citations · 145 across the 15 of their papers we have counts for
16 papers
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…
TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts
Pradip Kunwar, Minh N. Vu, Maanak Gupta +2
We propose Tensor-Trained Low-Rank Adaptation Mixture of Experts (TT-LoRA MoE), a novel computational framework integrating Parameter-Efficient Fine-Tuning (PEFT) with sparse MoE r…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Enabling and Enforcing Social Distancing Measures using Smart City and ITS Infrastructures: A COVID-19 Use Case
Maanak Gupta, Mahmoud Abdelsalam, Sudip Mittal
Internet of Things is a revolutionary domain that has the caliber to impact our lives and bring significant changes to the world. Several IoT applications have been envisioned to f…
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…