A5059424027- IoT and Edge/Fog Computing
- Cloud Computing and Resource Management
- Caching and Content Delivery
- Blockchain Technology Applications and Security
- Artificial Intelligence in Healthcare
- COVID-19 diagnosis using AI
- Vehicular Ad Hoc Networks (VANETs)
- Anomaly Detection Techniques and Applications
- Advanced Malware Detection Techniques
- IoT-based Smart Home Systems
- Privacy-Preserving Technologies in Data
- Water Quality Monitoring Technologies
- Imbalanced Data Classification Techniques
- Cryptography and Data Security
- Network Security and Intrusion Detection
- Cloud Data Security Solutions
- IoT Networks and Protocols
- Energy Efficient Wireless Sensor Networks
- Distributed and Parallel Computing Systems
- Sentiment Analysis and Opinion Mining
- User Authentication and Security Systems
- Age of Information Optimization
- Software System Performance and Reliability
- Privacy, Security, and Data Protection
- Advanced Authentication Protocols Security
Torrens University Australia
2023-2025
Queensland University of Technology
2020-2024
Jahangirnagar University
2016-2024
Daffodil International University
2022
Bangabandhu Sheikh Mujibur Rahman Digital University
2022
University of Malaya
2013-2016
Information Technology University
2014
The Internet of Medical Things (IoMT) has become an attractive playground to cybercriminals because its market worth and rapid growth. These devices have limited computational capabilities, which ensure minimum power absorption. Moreover, the manufacturers use simplified architecture offer a competitive price in market. As result, IoMTs cannot employ advanced security algorithms defend against cyber-attacks. IoMT easy prey for due access valuable data rapidly expanding market, as well being...
Security has always been a significant concern since the dawn of human civilization. That is why we build houses to keep ourselves and our belongings safe. And do not hesitate spend lot on front-door locks install CCTV cameras monitor security threats. This paper presents an innovative automatic Front Door (FDS) algorithm that uses Human Activity Recognition (HAR) detect four different threats at front door from real-time video feed with 73.18% accuracy. The activities are recognized using...
Lung diseases are the third-leading cause of mortality in world. Due to compromised lung function, respiratory difficulties, and physiological complications, disease brought on by toxic substances, pollution, infections, or smoking results millions deaths every year. Chest X-ray images pose a challenge for classification due their visual similarity, leading confusion among radiologists. To imitate those issues, we created an automated system with large data hub that contains 17 datasets...
To slow down the spread of COVID-19, governments worldwide are trying to identify infected people, and contain virus by enforcing isolation, quarantine. However, it is difficult trace people who came into contact with an person, which causes widespread community transmission, mass infection. address this problem, we develop e-government Privacy-Preserving Mobile, Fog computing framework entitled PPMF that can infected, suspected cases nationwide. We use personal mobile devices tracing app,...
Fog computing complements cloud by removing several limitations, such as delays and network bandwidth. It emerged to support Internet of Things (IoT) applications wherein its computations tasks are carried out at the network's edge. Heterogeneous IoT devices interact with different users throughout a network. However, data security is crucial concern for IoT, fog ecosystems. Since number anonymous increases new identity disclosures occur within IoTs, it becoming challenging grow mesh...
Health information technology is one of today's fastest-growing and most powerful technologies. This used predominantly for predicting illness obtaining medications quickly because visiting a doctor performing pathological tests can be time-consuming expensive. has prompted many researchers to contribute by developing new disease prediction systems or improving existing ones. paper presents smartwatch-based system named 'MedAi' multiple diseases such as ischemic heart disease, hypertension,...
Cyber-physical security is vital for protecting key computing infrastructure against cyber attacks. Individuals, corporations, and society can all suffer considerable digital asset losses due to attacks, including data loss, theft, financial reputation harm, company interruption, damage, ransomware espionage. A cyber-physical attack harms both physical assets. system more challenging than software-level because it requires inspection monitoring. This paper proposes an innovative effective...
Internet of Medical Things (IoMT) is an ecosystem composed connected electronic items such as small sensors/actuators and other cyber-physical devices (CPDs) in medical services. When these are linked together, they can support patients through monitoring, analysis, reporting more autonomous intelligent ways. The IoMT devices; however, often do not have sufficient computing resources onboard for service security assurance while the services handle large quantities sensitive private...
The Internet of Things (IoT) represents a swiftly expanding sector that is pivotal in driving the innovation today's smart services. However, inherent resource-constrained nature IoT nodes poses significant challenges embedding advanced algorithms for cybersecurity, leading to an escalation cyberattacks against these nodes. Contemporary research Intrusion Detection Systems (IDS) predominantly focuses on enhancing IDS performance through sophisticated algorithms, often overlooking their...
Recognizing fraudulent activity in the banking system is essential due to significant risks involved. When transactions are vastly outnumbered by non-fraudulent ones, dealing with imbalanced datasets can be difficult. This study aims determine best model for detecting fraud comparing four commonly used machine learning algorithms: Support Vector Machine (SVM), XGBoost, Decision Tree, and Logistic Regression. Additionally, we utilized Synthetic Minority Over-sampling Technique (SMOTE) address...
The rapid proliferation of Large Language Models (LLMs) across industries such as healthcare, finance, and legal services has revolutionized modern applications. However, their increasing adoption exposes critical vulnerabilities, particularly through adversarial prompt attacks that compromise LLM security. These prompt-based exploit weaknesses in LLMs to manipulate outputs, leading breaches confidentiality, corruption integrity, disruption availability. Despite significance, existing...
Cloudlets are small self maintained clouds, with hotspot like deployment, to enhance the computational capabilities of mobile devices. The limited resources cloudlets can become heavily loaded during peak utilization. Consequently, per user available capacity decreases and at times devices find no execution time benefit for using cloudlet. Researchers have proposed augmenting cloudlet devices; however, approaches do not consider offered service load ratio while device resources. In this...
Hepatitis C virus is a major cause for happening liver disease all over the world. However, many tools have been build that try to reduce influence of this virus. In work, machine learning based model has proposed can classify hepatitis infected patient's stages liver. We gathered instances fibrosis Egyptian patients from UCI repository. To balance multiple categories, synthetic minority oversampling methodology used increases patients. Later, we applied different feature selection methods...