[PDF][PDF] A novel data preprocessing model for lightweight sensory IoT intrusion detection

SA Khanday, H Fatima, N Rakesh - International Journal of …, 2024 - researchgate.net
IoT devices or sensor nodes are essential components of the machine learning (ML)
application workflow because they gather abundant information for building models with …

Multi-scale object detection and classification using machine learning and image processing

N Yuvaraj, K Rajput, K Suganyadevi… - … Conference on Data …, 2024 - ieeexplore.ieee.org
Multi-scale object detection and category has grown to be important duties in numerous
domain names, including laptop imaginative and prescient, autonomous driving, and …

Utilizing Cloud Computing for Distributed Training of Deep Learning Models

S Dhanasekaran, K Rajput, N Yuvaraj… - … Conference on Data …, 2024 - ieeexplore.ieee.org
Cloud computing has emerged as a powerful solution for lots of computational
responsibilities, including system studying and deep getting to know. Deep knowledge of …

Secure Decentralization: Examining the Role of Blockchain in Network Security

S Monga, P Gupta, J Logeshwaran… - 2024 2nd World …, 2024 - ieeexplore.ieee.org
Blockchain generation has emerged as a novel answer for securing decentralized networks.
This technology, which was first created for use in crypto currencies, has received enormous …

IP-MCCLSTM: A Network Intrusion Detection Model Based on IP Filtering

Q Feng, Z Lin, L Bing - 2023 20th International Computer …, 2023 - ieeexplore.ieee.org
The network intrusion detection system capably safeguards our network environment from
attacks. Yet, the relentless surge in bandwidth and inherent constraints within these systems …

Machine Learning and AI in Tele-Communication Networks and Iota for Predictive Maintenance

S Ponnambili, K Suganyadevi, K Rajput… - … Conference on Data …, 2024 - ieeexplore.ieee.org
This has emerge as important tools in the field of tile-communication networks and the net of
factors (IoT). These technologies have the ability to analyze large amounts of statistics and …

A comprehensive analysis of machine learning-based intrusion detection systems: evaluating datasets and algorithms for internet of things

S Saif, AA Ansari, S Biswas, D Giri - Journal of Cyber Security …, 2024 - Taylor & Francis
With the recent advancement of the Internet of Things (IoT) in various sectors, security has
become an essential requirement. Any IoT application or device may be compromised by …

SoK: Identifying Limitations and Bridging Gaps of Cybersecurity Capability Maturity Models (CCMMs)

L Liyanage, NAG Arachchilage, G Russello - arxiv preprint arxiv …, 2024 - arxiv.org
In the rapidly evolving digital landscape, where organisations are increasingly vulnerable to
cybersecurity threats, Cybersecurity Capability Maturity Models (CCMMs) emerge as pivotal …

High-performance network attack detection in unknown scenarios based on improved vertical model

S Hou, G **ao, H Zhou - Cluster Computing, 2025 - Springer
In the field of cybersecurity, most research on unknown attack detection still faces
challenges such as low detection accuracy, slow detection speed, and imprecise category …

Applying Machine Learning to Enhance Intrusion Detection Systems

A Garg, N Ramya, R Gupta… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Gadget up to date has shown its effectiveness in several packages, identifying styles and
detecting anomalies. One such software enhances intrusion detection structures (IDS) …