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[PDF][PDF] A novel data preprocessing model for lightweight sensory IoT intrusion detection
IoT devices or sensor nodes are essential components of the machine learning (ML)
application workflow because they gather abundant information for building models with …
application workflow because they gather abundant information for building models with …
Multi-scale object detection and classification using machine learning and image processing
Multi-scale object detection and category has grown to be important duties in numerous
domain names, including laptop imaginative and prescient, autonomous driving, and …
domain names, including laptop imaginative and prescient, autonomous driving, and …
Utilizing Cloud Computing for Distributed Training of Deep Learning Models
Cloud computing has emerged as a powerful solution for lots of computational
responsibilities, including system studying and deep getting to know. Deep knowledge of …
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 …
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 …
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
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 …
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
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 …
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)
In the rapidly evolving digital landscape, where organisations are increasingly vulnerable to
cybersecurity threats, Cybersecurity Capability Maturity Models (CCMMs) emerge as pivotal …
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 …
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) …
detecting anomalies. One such software enhances intrusion detection structures (IDS) …