10 citations · 29 across the 16 of their papers we have counts for
16 papers
D2H-AD: A Hybrid Model Utilizing Hyperdimensional Computing for Advanced Anomaly Detection
Ghazal Ghajari, Elaheh Ghajari, Ashutosh Ghimire +3
Anomaly detection is a fundamental component of intelligent systems with applications in healthcare, cybersecurity, smart grids, and IoT environments. Although conventional machine…
Blockchain-Driven AI-Enhanced Post-Quantum Multivariate Identity-based Signature and Privacy-Preserving Data Aggregation Scheme for Fog-enabled Flying Ad-Hoc Networks
Sufian Al majmaie, Ghazal Ghajari, Niraj Prasad Bhatta +1
The integration of Fog Computing with Flying Ad-Hoc Networks (FANETs) offers promising capabilities for decentralized, low-latency intelligence in UAV-based applications. However,…
Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data
Abdulrahman Albaiz, Fathi Amsaad
This paper presents a fully autonomous Tiny Machine Learning (TinyML) Z-Score-based anomaly detection system deployed on a low-power microcontroller for real-time monitoring of app…
K-Means Based TinyML Anomaly Detection and Distributed Model Reuse via the Distributed Internet of Learning (DIoL)
Abdulrahman Albaiz, Fathi Amsaad
This paper presents a lightweight K-Means anomaly detection model and a distributed model-sharing workflow designed for resource-constrained microcontrollers (MCUs). Using real pow…
Enhancing IoT Intrusion Detection Systems through Adversarial Training
Karma Gurung, Ashutosh Ghimire, Fathi Amsaad
The augmentation of Internet of Things (IoT) devices transformed both automation and connectivity but revealed major security vulnerabilities in networks. We address these challeng…
A Benchmark Reference for ESP32-CAM Module
Sayed T. Nowroz, Nermeen M. Saleh, Siam Shakur +2
The ESP32-CAM is one of the most widely adopted open-source modules for prototyping embedded vision applications. Since its release in 2019, it has gained popularity among both hob…
Optimizing Distributed Training Approaches for Scaling Neural Networks
Vishnu Vardhan Baligodugula, Fathi Amsaad
This paper presents a comparative analysis of distributed training strategies for large-scale neural networks, focusing on data parallelism, model parallelism, and hybrid approache…
Enhancing Cybersecurity in Critical Infrastructure with LLM-Assisted Explainable IoT Systems
Ashutosh Ghimire, Ghazal Ghajari, Karma Gurung +2
Ensuring the security of critical infrastructure has become increasingly vital with the proliferation of Internet of Things (IoT) systems. However, the heterogeneous nature of IoT…
Intrusion Detection in IoT Networks Using Hyperdimensional Computing: A Case Study on the NSL-KDD Dataset
Ghazal Ghajari, Elaheh Ghajari, Hossein Mohammadi +1
The rapid expansion of Internet of Things (IoT) networks has introduced new security challenges, necessitating efficient and reliable methods for intrusion detection. In this study…
Network Anomaly Detection for IoT Using Hyperdimensional Computing on NSL-KDD
Ghazal Ghajari, Ashutosh Ghimire, Elaheh Ghajari +1
With the rapid growth of IoT devices, ensuring robust network security has become a critical challenge. Traditional intrusion detection systems (IDSs) often face limitations in det…
Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data
Vishnu Vardhan Baligodugula, Fathi Amsaad
This paper presents a comprehensive comparative analysis of prominent clustering algorithms K-means, DBSCAN, and Spectral Clustering on high-dimensional datasets. We introduce a no…
Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification
Ghazal Ghajari, Mithun Kumar PK, Fathi Amsaad
Unsupervised anomaly detection is a promising technique for identifying unusual patterns in data without the need for labeled training examples. This approach is particularly valua…
Real-Time Automated donning and doffing detection of PPE based on Yolov4-tiny
Anusha Verma, Ghazal Ghajari, K M Tawsik Jawad +2
Maintaining patient safety and the safety of healthcare workers (HCWs) in hospitals and clinics highly depends on following the proper protocol for donning and taking off personal…
AI-Driven Predictive Analytics Approach for Early Prognosis of Chronic Kidney Disease Using Ensemble Learning and Explainable AI
K M Tawsik Jawad, Anusha Verma, Fathi Amsaad +1
Chronic Kidney Disease (CKD) is one of the widespread Chronic diseases with no known ultimo cure and high morbidity. Research demonstrates that progressive Chronic Kidney Disease (…
A Comprehensive Review on Blockchains for Internet of Vehicles: Challenges and Directions
Brian Hildebrand, Mohamed Baza, Tara Salman +3
Internet of Vehicles (IoVs) consist of smart vehicles, Autonomous Vehicles (AVs) as well as roadside units (RSUs) that communicate wirelessly to provide enhanced transportation ser…
Detection of Lying Electrical Vehicles in Charging Coordination Application Using Deep Learning
Ahmed Shafee, Mostafa M. Fouda, Mohamed Mahmoud +3
The simultaneous charging of many electric vehicles (EVs) stresses the distribution system and may cause grid instability in severe cases. The best way to avoid this problem is by…