Mahmoud Abdelsalam

Orcid: 0000-0001-5627-5239

According to our database1, Mahmoud Abdelsalam authored at least 30 papers between 2017 and 2024.

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Bibliography

2024
Automated machine learning for deep learning based malware detection.
Comput. Secur., February, 2024

Deep Learning Based XIoT Malware Analysis: A Comprehensive Survey, Taxonomy, and Research Challenges.
CoRR, 2024

Explainable Malware Analysis: Concepts, Approaches and Challenges.
CoRR, 2024

SoK: Leveraging Transformers for Malware Analysis.
CoRR, 2024

Intra-Section Code Cave Injection for Adversarial Evasion Attacks on Windows PE Malware File.
CoRR, 2024

Explainability Guided Adversarial Evasion Attacks on Malware Detectors.
Proceedings of the 33rd International Conference on Computer Communications and Networks, 2024

Poster: Intelligent Network Management: RAG-Enhanced LLMs for Log Analysis, Troubleshooting, and Documentation.
Proceedings of the 20th International Conference on emerging Networking EXperiments and Technologies, 2024

2023
Analyzing and Explaining Black-Box Models for Online Malware Detection.
IEEE Access, 2023

Explainable AI-Based Intrusion Detection Systems for Cloud and IoT.
Proceedings of the 32nd International Conference on Computer Communications and Networks, 2023

Exploiting Windows PE Structure for Adversarial Malware Evasion Attacks.
Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy, 2023

2022
Machine Learning in Access Control: A Taxonomy and Survey.
CoRR, 2022

Online Malware Classification with System-Wide System Calls in Cloud IaaS.
Proceedings of the 23rd IEEE International Conference on Information Reuse and Integration for Data Science, 2022

Analysis of Label-Flip Poisoning Attack on Machine Learning Based Malware Detector.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
A Survey on Adversarial Attacks for Malware Analysis.
CoRR, 2021

Recurrent Neural Networks Based Online Behavioural Malware Detection Techniques for Cloud Infrastructure.
IEEE Access, 2021

Analyzing Machine Learning Approaches for Online Malware Detection in Cloud.
Proceedings of the IEEE International Conference on Smart Computing, 2021

Ontology driven AI and Access Control Systems for Smart Fisheries.
Proceedings of the SAT-CPS@CODASPY 2021, 2021

Artificial Intelligence Assisted Malware Analysis.
Proceedings of the SAT-CPS@CODASPY 2021, 2021

Autoencoder-based Anomaly Detection in Smart Farming Ecosystem.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
AI assisted Malware Analysis: A Course for Next Generation Cybersecurity Workforce.
CoRR, 2020

Enabling and Enforcing Social Distancing Measures using Smart City and ITS Infrastructures: A COVID-19 Use Case.
CoRR, 2020

Security and Privacy in Smart Farming: Challenges and Opportunities.
IEEE Access, 2020

Ontologies and Artificial Intelligence Systems for the Cooperative Smart Farming Ecosystem.
IEEE Access, 2020

Knowledge Enrichment by Fusing Representations for Malware Threat Intelligence and Behavior.
Proceedings of the IEEE International Conference on Intelligence and Security Informatics, 2020

Cyber Attacks on Smart Farming Infrastructure.
Proceedings of the 6th IEEE International Conference on Collaboration and Internet Computing, 2020

Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS.
Proceedings of the Cloud Computing - CLOUD 2020, 2020

YieldPredict: A Crop Yield Prediction Framework for Smart Farms.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Online Malware Detection in Cloud Auto-scaling Systems Using Shallow Convolutional Neural Networks.
Proceedings of the Data and Applications Security and Privacy XXXIII, 2019

2018
Malware Detection in Cloud Infrastructures Using Convolutional Neural Networks.
Proceedings of the 11th IEEE International Conference on Cloud Computing, 2018

2017
Clustering-Based IaaS Cloud Monitoring.
Proceedings of the 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 2017


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