On-off attack detection in trust model using intra-daily variability for the IoT

S Kannan, R Venkataraman… - Bulletin of Electrical …, 2023 - beei.org
The growth of the internet of things (IoT) increases the need to develop the trust
computational model for heterogeneous networks with various IoT devices. Trust models are …

A Survey of Novel Framework of Anomaly-Based Intrusion Detection Systems in Computer Networks Using Ensemble Feature Integration with Deep Learning …

S Akkepalli, SK - Proceedings of the 2024 16th International Conference …, 2024 - dl.acm.org
Today's internet is made up of nearly half a million different networks. In any network
connection, identifying the attacks by their types is a difficult task as different attacks may …

Investigating Routing Protocol Attacks on Low Power and Lossy IoT Networks

U Kiran, P Maurya, H Sharma - SN Computer Science, 2024 - Springer
Abstract Internet-of-things (IoT) networks are distinguished by nodes with limited
computational power and storage capacity, making Low Power and Lossy Networks (LLNs) …

Developing an IoT Adoption Framework for Library Management for Public Tertiary Institutions in Ghana

F Boateng, OJ Aroba, SS Patel - Handbook of Research on …, 2024 - igi-global.com
The chapter presents an IoT adoption framework for improving library management
practices in Ghana's public tertiary institution. The internet of things (IoT) has revolutionized …

Enhancing V2G Network Security: A Novel Cockroach Behavior-Based Machine Learning Classifier to Mitigate MitM and DoS Attacks.

K MEKKAOUI - Advances in Electrical & Computer …, 2024 - search.ebscohost.com
Abstract V2G (Vehicle-to-Grid) is a system that allows an electric vehicle to connect and
exchange energy with the electricity grid. This system is part of the smart-grid, which is an …

Comparative Analysis of Machine Learning Models for Intrusion Detection in Internet of Things Networks Using the RT-IoT2022 Dataset

G Airlangga - MALCOM: Indonesian Journal of Machine Learning …, 2024 - journal.irpi.or.id
This research investigates the performance of various machine learning models in
developing an Intrusion Detection System (IDS) for the complex and evolving security …

Comparative Analysis of Intrusion Detection Systems for Internet of Things

N Nedungadi, AK Subran… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
The expansion of IoT has led to an abundance of interconnected devices that are
susceptible to cyber risks, including malware, ransomware, denial-of-service attacks, and …

Improving the Efficiency of IoMT Using Fuzzy Logic Methods

K Kiran Kumar, S Sivakumar, P Patro… - Advances in Fuzzy …, 2024 - Wiley Online Library
Among all industries, 20% are homes where home energy management systems have
become more feasible with the introduction of smart appliances and clever sensors. When …

Securing Networks: Unleashing the Power of the FT-Transformer for Intrusion Detection

S Saraniya, MV Sowmiya, BN Kalpana… - … Computer, Electrical & …, 2024 - ieeexplore.ieee.org
The amount of sensitive data sent through internet is increased day by day. As a
consequence, it has paved a way for the intruders to breach the network. To address this …

Machine Learning-based Intrusion Detection System using Wireless Sensor Networks

P Pande, H Mathur, LK Gupta - 2024 Fourth International …, 2024 - ieeexplore.ieee.org
Cybersecurity has grown to be a top priority for both businesses and people in today's
networked and digitally driven society. It is essential to put in place efficient security …