A survey of distance and similarity measures used within network intrusion anomaly detection

DJ Weller-Fahy, BJ Borghetti… - … Surveys & Tutorials, 2014 - ieeexplore.ieee.org
Anomaly detection (AD) use within the network intrusion detection field of research, or
network intrusion AD (NIAD), is dependent on the proper use of similarity and distance …

Intrusion detection using machine learning for risk mitigation in IoT‐enabled smart irrigation in smart farming

A Raghuvanshi, UK Singh, GS Sajja… - Journal of Food …, 2022 - Wiley Online Library
The majority of countries rely largely on agriculture for employment. Irrigation accounts for a
sizable amount of water use. Crop irrigation is an important step in crop yield prediction …

Various Soft Computing Based Techniques for Developing Intrusion Detection Management System

GS Sajjaa, H Pallathadka, M Naved… - ECS …, 2022 - iopscience.iop.org
Protecting networks and data requires an effective Intrusion Detection System (IDS).
Contextual knowledge processing may be used to identify attacks that are specific to certain …

[HTML][HTML] PCA and PSO based optimized support vector machine for efficient intrusion detection in internet of things

MP Raghunath, S Deshmukh, P Chaudhari… - Measurement …, 2025 - Elsevier
Abstract The Internet of Things (IoT) is a network that interconnects many everyday objects,
including computers, televisions, washing machines, and even whole urban areas. These …

Intrusion detection in RFID system using computational intelligence approach for underground mines

SK Gautam, H Om - International Journal of Communication …, 2018 - Wiley Online Library
The radio frequency identification technology (RFID) is commonly used for object tracking
and monitoring. In this paper, we discuss a model for intrusion detection system based on …

Machine Learning Enabled Framework for Classification and Detection of Intrusion in MANET

V Trivedi, M Dubey, P Naysk - 2023 14th International …, 2023 - ieeexplore.ieee.org
An Intrusion Detection System is a necessity in order to ensure the security of the existing
network and user data which is travelling across in the network. Because of the rapid …

Machine Learning and Artificial Intelligence for Detecting Cyber Security Threats in IoT Environmment

R Bhardwaj, S Gogula, B Bhabani… - Natural Language …, 2025 - Wiley Online Library
Summary The Internet of Things (IoT) refers to the increasing connectivity of many human‐
made entities, such as healthcare systems, smart homes, and smart grids, through the …

A survey on security issues in ad hoc routing protocols and their mitigation techniques

H Kayarkar - arXiv preprint arXiv:1203.3729, 2012 - arxiv.org
Mobile Ad hoc Networks (MANETS) are transient networks of mobile nodes, connected
through wireless links, without any fixed infrastructure or central management. Due to the …

[PDF][PDF] An improved knn classifier for anomaly intrusion detection system using cluster optimization

OP Akomolafe, AI Adegboyega - An Improved KNN Classifier for Anomaly …, 2017 - ijcst.org
With the emergence of anomaly intrusion detection system, varieties of unknown intrusions
that were not detected by the misuse or signature based intrusion detection system can now …

[PDF][PDF] Enhanced Intrusion Detection System for Detecting Rare Class Attacks using Correlation based Dimensionality Reduction Technique

S Bahl, D Dahiya - Indian Journal of Science …, 2016 - sciresol.s3.us-east-2.amazonaws …
Abstract Background/Objective: With Fast growing internet world the risk of intrusion has
also increased, as a result Intrusion Detection System (IDS) is the admired key research …