Security and Communication Networks

Anomaly Detection Technologies for Securing the Emerging Resource-constrained Networking Scenarios


Publishing date
01 Mar 2023
Status
Closed
Submission deadline
11 Nov 2022

Lead Editor

1Harbin Institute of Technology, Weihai, China

2University of Exeter, Exeter, UK

3City University of Hong Kong, Hong Kong

4Jiangxi Normal University, Nanchang, China

5Ocean University of China, Qingdao, China

This issue is now closed for submissions.

Anomaly Detection Technologies for Securing the Emerging Resource-constrained Networking Scenarios

This issue is now closed for submissions.

Description

Driven by the new digital revolution represented by the Internet of Things (IoT) and cyber-physical system (CPS) technologies, the traditional Internet architecture dominated by a static backbone structure is facing the challenge of emerging network application scenarios such as heterogeneous vehicle-to-everything (V2X) communications and delay-sensitive industrial control system (ICS). Numerous resource-constrained devices (e.g., intelligent connected cars with high moving speed, industrial wireless sensors scattered in harsh production environments) are gradually becoming first-class network entities, rather than personal computers and cloud servers equipped with plenty of computing resources.

Intrusion detection technology is one of the most famous security protection technologies in the traditional Internet area. However, with the advent of a new era of digital society featuring the Internet of everything, it becomes very difficult for mainstream intrusion detection technologies to exert their usual effectiveness as done before. On the one hand, network security boundaries become more blurred and complex, which contradicts the conventional assumption of the boundary-based network security strategy, although it has been used for decades as an established rule. On the other hand, these emerging resource-constrained networking entities generally have a limited computing capacity or inadequate power supply to achieve an acceptable detection performance.

This Special Issue will focus on cutting-edge original research and review articles from academia and solicit implementations from industry, with a particular emphasis on intelligent and lightweight intrusion detection technologies that can directly apply to resource-constrained networking scenarios to achieve a more secure digital society.

Potential topics include but are not limited to the following:

  • New opportunities for typical classification techniques in intrusion detection
  • Novel intrusion detection architecture with emerging learning models
  • Lightweight neural network designs for lightweight intrusion detection
  • Accurate feature selection techniques for lightweight intrusion detection
  • Efficient intrusion detection technologies with limited labeled datasets
  • Intrusion detection for industrial process control with strict sequential logic
  • Practical intrusion detection techniques for resource-constrained CPS devices
  • Learning-based intrusion detection for delay-sensitive ICS scenarios
  • Learning-based intrusion detection for in-vehicle networks
  • Learning-based intrusion detection for V2X communications
  • New use cases for intrusion detection in ICS or V2X or beyond
  • Other methods of security and privacy for securing promising network application scenarios

Articles

  • Special Issue
  • - Volume 2023
  • - Article ID 8903980
  • - Research Article

An Anomaly Detection Approach Based on Integrated LSTM for IoT Big Data

Chao Li | Yuhan Fu | ... | Junjian Li
  • Special Issue
  • - Volume 2022
  • - Article ID 6546004
  • - Research Article

IoV-SDCM: An IoV Secure Data Communication Model Based on Network Encoding and Relay Collaboration

Yan Sun | Lihua Yin | ... | Chonghua Wang
  • Special Issue
  • - Volume 2022
  • - Article ID 8188977
  • - Research Article

A Blockchain-Enabled Trusted Protocol Based on Whole-Process User Behavior in 6G Network

Zhe Tu | Huachun Zhou | ... | Yuzheng Yang
  • Special Issue
  • - Volume 2022
  • - Article ID 1761655
  • - Research Article

LGBM: An Intrusion Detection Scheme for Resource-Constrained End Devices in Internet of Things

Yong-Quan Cong | Ting Guan | ... | Xiang-Guo Cheng
  • Special Issue
  • - Volume 2022
  • - Article ID 4996427
  • - Research Article

Privacy-Enhanced Intrusion Detection and Defense for Cyber-Physical Systems: A Deep Reinforcement Learning Approach

Qingyuan Lin | Rui Ming | ... | Haibo Luo
  • Special Issue
  • - Volume 2022
  • - Article ID 4748946
  • - Research Article

Web-Cloud Collaborative Mobile Online 3D Rendering System

Chang Liu | Huilin Song | ... | Ming Ying
  • Special Issue
  • - Volume 2022
  • - Article ID 1812273
  • - Research Article

Attention-Based LSTM Model for IFA Detection in Named Data Networking

Xin Zhang | Ru Li | Wenhan Hou
  • Special Issue
  • - Volume 2022
  • - Article ID 1028251
  • - Research Article

Detection of Packet Dropping Attack Based on Evidence Fusion in IoT Networks

Weichen Ding | Wenbin Zhai | ... | Hang Gao
Security and Communication Networks
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Acceptance rate10%
Submission to final decision143 days
Acceptance to publication35 days
CiteScore2.600
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