activity
20202025
most citedBlockchain-based Federated Learning with Secure Aggregation in Trusted Execution Environment for Internet-of-Things

160 citations · 237 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CR2025

ICS-SimLab: A Containerized Approach for Simulating Industrial Control Systems for Cyber Security Research

Jaxson Brown, Duc-Son Pham, Sie-Teng Soh +3

Industrial Control Systems (ICSs) are complex interconnected systems used to manage process control within industrial environments, such as chemical processing plants and water tre…

cs.CR2023★ 60 cited

SMPC-based Federated Learning for 6G enabled Internet of Medical Things

Aditya Pribadi Kalapaaking, Veronika Stephanie, Ibrahim Khalil +3

Rapidly developing intelligent healthcare systems are underpinned by Sixth Generation (6G) connectivity, ubiquitous Internet of Things (IoT), and Deep Learning (DL) techniques. Thi…

cs.CR2023★ 160 cited

Blockchain-based Federated Learning with Secure Aggregation in Trusted Execution Environment for Internet-of-Things

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammad Saidur Rahman +3

This paper proposes a blockchain-based Federated Learning (FL) framework with Intel Software Guard Extension (SGX)-based Trusted Execution Environment (TEE) to securely aggregate l…

cs.CR2022

PhishClone: Measuring the Efficacy of Cloning Evasion Attacks

Arthur Wong, Alsharif Abuadbba, Mahathir Almashor +1

Web-based phishing accounts for over 90% of data breaches, and most web-browsers and security vendors rely on machine-learning (ML) models as mitigation. Despite this, links posted…

cs.CR2022

Unraveling Threat Intelligence Through the Lens of Malicious URL Campaigns

Mahathir Almashor, Ejaz Ahmed, Benjamin Pick +6

The daily deluge of alerts is a sombre reality for Security Operations Centre (SOC) personnel worldwide. They are at the forefront of an organisation's cybersecurity infrastructure…

cs.CR2022★ 9 cited

Towards Web Phishing Detection Limitations and Mitigation

Alsharif Abuadbba, Shuo Wang, Mahathir Almashor +4

Web phishing remains a serious cyber threat responsible for most data breaches. Machine Learning (ML)-based anti-phishing detectors are seen as an effective countermeasure, and are…

cs.CV2022★ 2 cited

Resurrecting Trust in Facial Recognition: Mitigating Backdoor Attacks in Face Recognition to Prevent Potential Privacy Breaches

Reena Zelenkova, Jack Swallow, M. A. P. Chamikara +5

Biometric data, such as face images, are often associated with sensitive information (e.g medical, financial, personal government records). Hence, a data breach in a system storing…

cs.CR2021★ 1 cited

Characterizing Malicious URL Campaigns

Mahathir Almashor, Ejaz Ahmed, Benjamin Pick +4

URLs are central to a myriad of cyber-security threats, from phishing to the distribution of malware. Their inherent ease of use and familiarity is continuously abused by attackers…

cs.LG2020★ 5 cited

Evaluation of Federated Learning in Phishing Email Detection

Chandra Thapa, Jun Wen Tang, Alsharif Abuadbba +5

The use of Artificial Intelligence (AI) to detect phishing emails is primarily dependent on large-scale centralized datasets, which opens it up to a myriad of privacy, trust, and l…