Rahim Taheri

Orcid: 0000-0002-4078-3105

According to our database1, Rahim Taheri authored at least 16 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks.
CoRR, 2024

2023
SIEMS: A Secure Intelligent Energy Management System for Industrial IoT Applications.
IEEE Trans. Ind. Informatics, 2023

Robust Aggregation Function in Federated Learning.
Proceedings of the Advances in Information Systems, Artificial Intelligence and Knowledge Management, 2023

Moving Towards Explainable Artificial Intelligence Using Fuzzy Rule-Based Networks in Decision-Making Process.
Proceedings of the Advances in Information Systems, Artificial Intelligence and Knowledge Management, 2023

2022
SETTI: A Self-supervised AdvErsarial Malware DeTection ArchiTecture in an IoT Environment.
ACM Trans. Multim. Comput. Commun. Appl., 2022

UNBUS: Uncertainty-aware Deep Botnet Detection System in Presence of Perturbed Samples.
CoRR, 2022

Deep Image: A precious image based deep learning method for online malware detection in IoT Environment.
CoRR, 2022

Can Open and AI-Enabled 6G RAN Be Secured?
IEEE Consumer Electron. Mag., 2022

2021
Fed-IIoT: A Robust Federated Malware Detection Architecture in Industrial IoT.
IEEE Trans. Ind. Informatics, 2021

LEVER: Secure Deduplicated Cloud Storage With Encrypted Two-Party Interactions in Cyber-Physical Systems.
IEEE Trans. Ind. Informatics, 2021

Adversarial android malware detection for mobile multimedia applications in IoT environments.
Multim. Tools Appl., 2021

RSS: An Energy-Efficient Approach for Securing IoT Service Protocols Against the DoS Attack.
IEEE Internet Things J., 2021

2020
On defending against label flipping attacks on malware detection systems.
Neural Comput. Appl., 2020

Similarity-based Android malware detection using Hamming distance of static binary features.
Future Gener. Comput. Syst., 2020

Can machine learning model with static features be fooled: an adversarial machine learning approach.
Clust. Comput., 2020

2019
Automatic Clustering of Attacks in Intrusion Detection Systems.
Proceedings of the 16th IEEE/ACS International Conference on Computer Systems and Applications, 2019


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