160 citations · 534 across the 11 of their papers we have counts for
11 papers
Blockchain-Based and Fuzzy Logic-Enabled False Data Discovery for the Intelligent Autonomous Vehicular System
Ziaur Rahman, Xun Yi, Ibrahim Khalil +2
Since the beginning of this decade, several incidents report that false data injection attacks targeting intelligent connected vehicles cause huge industrial damage and loss of liv…
Smart Policy Control for Securing Federated Learning Management System
Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammed Atiquzzaman
The widespread adoption of Internet of Things (IoT) devices in smart cities, intelligent healthcare systems, and various real-world applications have resulted in the generation of…
Trustworthy Privacy-preserving Hierarchical Ensemble and Federated Learning in Healthcare 4.0 with Blockchain
Veronika Stephanie, Ibrahim Khalil, Mohammed Atiquzzaman +1
The advancement of Internet and Communication Technologies (ICTs) has led to the era of Industry 4.0. This shift is followed by healthcare industries creating the term Healthcare 4…
Blockchain-based Access Control for Secure Smart Industry Management Systems
Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammad Saidur Rahman +1
Smart manufacturing systems involve a large number of interconnected devices resulting in massive data generation. Cloud computing technology has recently gained increasing attenti…
Blockchain-based Federated Learning with SMPC Model Verification Against Poisoning Attack for Healthcare Systems
Aditya Pribadi Kalapaaking, Ibrahim Khalil, Xun Yi
Due to the rising awareness of privacy and security in machine learning applications, federated learning (FL) has received widespread attention and applied to several areas, e.g.,…
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…
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…
Adversarial Analysis of the Differentially-Private Federated Learning in Cyber-Physical Critical Infrastructures
Md Tamjid Hossain, Shahriar Badsha, Hung La +4
Federated Learning (FL) has become increasingly popular to perform data-driven analysis in cyber-physical critical infrastructures. Since the FL process may involve the client's co…
Local Differential Privacy for Federated Learning
M. A. P. Chamikara, Dongxi Liu, Seyit Camtepe +4
Advanced adversarial attacks such as membership inference and model memorization can make federated learning (FL) vulnerable and potentially leak sensitive private data. Local diff…
Blockchain based AI-enabled Industry 4.0 CPS Protection against Advanced Persistent Threat
Ziaur Rahman, Xun Yi Ibrahim Khalil
Industry 4.0 is all about doing things in a concurrent, secure, and fine-grained manner. IoT edge-sensors and their associated data play a predominant role in today's industry ecos…
Blockchain for IoT: A Critical Analysis Concerning Performance and Scalability
Ziaur Rahman, Xun Yi, Ibrahim Khalil +1
The world has been experiencing a mind-blowing expansion of blockchain technology since it was first introduced as an emerging means of cryptocurrency called bitcoin. Currently, it…