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20192026
most citedDeep Image: A precious image based deep learning method for online malware detection in IoT Environment

3 citations · 5 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

A Risk-Stratified Benchmark Dataset for Bad Randomness (SWC-120) Vulnerabilities in Ethereum Smart Contracts

Hadis Rezaei, Rahim Taheri, Francesco Palmieri

Many Ethereum smart contracts rely on block attributes such as block.timestamp or blockhash to generate random numbers for applications like lotteries and games. However, these val…

cs.CR2024

Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks

Ehsan Nowroozi, Imran Haider, Rahim Taheri +1

Federated Learning (FL) is a machine learning (ML) approach that enables multiple decentralized devices or edge servers to collaboratively train a shared model without exchanging r…

cs.CR2022★ 2 cited

UNBUS: Uncertainty-aware Deep Botnet Detection System in Presence of Perturbed Samples

Rahim Taheri

A rising number of botnet families have been successfully detected using deep learning architectures. While the variety of attacks increases, these architectures should become more…

cs.CR2022

SETTI: A Self-supervised Adversarial Malware Detection Architecture in an IoT Environment

Marjan Golmaryami, Rahim Taheri, Zahra Pooranian +2

In recent years, malware detection has become an active research topic in the area of Internet of Things (IoT) security. The principle is to exploit knowledge from large quantities…

cs.CR2022★ 3 cited

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

Meysam Ghahramani, Rahim Taheri, Mohammad Shojafar +2

The volume of malware and the number of attacks in IoT devices are rising everyday, which encourages security professionals to continually enhance their malware analysis tools. Res…

cs.CR2019

Similarity-based Android Malware Detection Using Hamming Distance of Static Binary Features

Rahim Taheri, Meysam Ghahramani, Reza Javidan +3

In this paper, we develop four malware detection methods using Hamming distance to find similarity between samples which are first nearest neighbors (FNN), all nearest neighbors (A…