scholarly journals Retraction Note to: Mobile network intrusion detection for IoT system based on transfer learning algorithm

2021 ◽  
Vol 24 (1) ◽  
pp. 589-589
Author(s):  
Lianbing Deng ◽  
Daming Li ◽  
Xiang Yao ◽  
Haoxiang Wang
Keyword(s):  
Intrusion Detection ◽  
Transfer Learning ◽  
Learning Algorithm ◽  
Mobile Network ◽  
Network Intrusion Detection ◽  
Network Intrusion

Mobile network intrusion detection for IoT system based on transfer learning algorithm

2018 ◽  
Vol 22 (S4) ◽  
pp. 9889-9904 ◽  
Author(s):  
Lianbing Deng ◽  
Daming Li ◽  
Xiang Yao ◽  
David Cox ◽  
Haoxiang Wang
Keyword(s):  
Intrusion Detection ◽  
Transfer Learning ◽  
Learning Algorithm ◽  
Mobile Network ◽  
Network Intrusion Detection ◽  
Network Intrusion

A novel wide & deep transfer learning stacked GRU framework for network intrusion detection

2021 ◽  
Vol 61 ◽  
pp. 102899
Author(s):  
Nongmeikapam Brajabidhu Singh ◽  
Moirangthem Marjit Singh ◽  
Arindam Sarkar ◽  
Jyotsna Kumar Mandal
Keyword(s):  
Intrusion Detection ◽  
Transfer Learning ◽  
Network Intrusion Detection ◽  
Network Intrusion

Auditory Feedback for Network Intrusion Detection

2010 ◽  
pp. 94-104
Author(s):  
M. Vargas Martin
Keyword(s):  
Intrusion Detection ◽  
Real Time ◽  
Mesh Networks ◽  
Speech Sound ◽  
Mobile Network ◽  
Multimodal Interfaces ◽  
Network Intrusion Detection ◽  
Auditory Display ◽  
Immediate Feedback ◽  
Network Intrusion

Network intrusion (the unauthorized access to a computer system perpetrated by persons or a piece of software) is a major concern of network administrators. Carrying out network intrusion detection (NID) manually is a tiring, complex and time-consuming task, often overloading the visual sensory channel. To overcome this, real-time auditory alarms and auditory information provide immediate feedback, helping to identify trends or patterns of the attacks in network logs and in real-time network accesses, allowing professionals make rapid decisions, thus representing an interesting alternative to conventional NID. The purpose of this chapter is to describe literature research on the benefits and challenges of Auditory Display (the use of non-speech sound to represent meaningful information at a computer interface) applied to wireless, wired, and mobile network intrusion detection. This chapter also highlights further work on Auditory Display and multimodal interfaces to support intrusion detection in wireless mesh networks.

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