A Review of Intrusion Detection Technology Based on Deep Rein-forcement Learning

With the rapid development of modern science and technology, all kinds of network attacks are updated constantly. Therefore, the traditional network security defense mechanism needs to be further improved. Through extensive investigation, this paper presents the latest work of network intrusion detection technology based on deep learning. Firstly, this paper introduces the related concepts of network intrusion detection technology. On this basis, we further evaluate the performance of three common deep learning models in intrusion detection, and conclude that DBN algorithm has some strong advantages. Afterwards, it also puts forward several improvement strategies of intrusion detection models

Tree-based Intelligent Intrusion Detection System in Internet of Vehicles

The use of autonomous vehicles (AVs) is a promising technology in Intelligent Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything (V2X) technology enables communication among vehicles and other infrastructures. However, AVs and Internet of Vehicles (IoV) are vulnerable to different types of cyber-attacks such as denial of service, spoofing, and sniffing attacks. In this paper, an intelligent intrusion detection system (IDS) is proposed based on tree-structure machine learning models. The results from the implementation of the proposed intrusion detection system on standard data sets indicate that the system has the ability to identify various cyber-attacks in the AV networks. Furthermore, the proposed ensemble learning and feature selection approaches enable the proposed system to achieve high detection rate and low computational cost simultaneously.Comment: Accepted in IEEE Global Communications Conference (GLOBECOM) 201

Blockchain Technology in the Intrusion Detection Domain

The ability of blockchain technology to improve security and transparency across a range of industries has receivedA great deal of attention has been garnered lately in correcting the sentence.. In the domain of intrusion detection, where the identification and mitigation of cyber threats are paramount, blockchain has emerged as a promising solution. This abstract examines how blockchain is used in intrusion detection systems and emphasizes its advantages. Blockchain technology improves the security and integrity of intrusion detection systems by using a decentralized and immutable ledger. It provides an immutable audit trail, distributed consensus, and increased resilience to attacks. Moreover, blockchain fosters trust, transparency, and collaboration among stakeholders, enabling faster threat detection and response. This research can explore novel approaches to integrating blockchain into intrusion detection systems, providing stronger protection against cyber threats.Immutable Audit Trail: In the context of intrusion detection, the capacity of blockchain to produce an unalterable and transparent audit trail is of enormous value. Research in this area can focus on developing techniques to leverage the blockchain's audit trail for effective incident response, forensic investigations, and attribution of cyberattacks. We will use theweighted product model in this study, which is a research approach that gives weights to various factors and combines them to make conclusions based on their relative relevance in a weighted way. Taken as alternative is“IDS1, IDS2, IDS3, IDS4, IDS5, IDS6, IDS7, and IDS8”.Detection Quality, Performance, Stability, User Interface, Profile update, ConvenienceThe By this we can see that IDS4 has 1 RANK and IDS5 has the 8th RANK.In conclusion, blockchain technology holds great potential in the intrusion detection domain. Its decentralized and immutable nature can enhance the security and reliability of intrusion detection systems by providing transparent and tamper-proof logs of network activity. Blockchain-based solutions can improve threat detection, facilitate secure information sharing among entities, and enhance the overall resilience of intrusion detection systems. As the technology continues to evolve, further research and development in integrating blockchain with intrusion detection will unlock new possibilities for combating cyber threats

State of the Art Intrusion Detection System for Cloud Computing

The term Cloud computing is not new anymore in computing technology. This form of computing technology previously considered only as marketing term, but today Cloud computing not only provides innovative improvements in resource utilisation but it also creates a new opportunities in data protection mechanisms where the advancement of intrusion detection technologies  are blooming rapidly. From the perspective of security, Cloud computing also introduces concerns about data protection and intrusion detection mechanism. This paper surveys, explores and informs researchers about the latest developed Cloud Intrusion Detection Systems by providing a comprehensive taxonomy and investigating possible solutions to detect intrusions in cloud computing systems. As a result, we provide a comprehensive review of Cloud Intrusion Detection System research, while highlighting the specific properties of Cloud Intrusion Detection System. We also present taxonomy on the key issues in Cloud Intrusion Detection System area and discuss the different approaches taken to solve the issues. We conclude the paper with a critical analysis of challenges that have not fully solved

Classification, testing and optimization of intrusion detection systems

Modem network security products vary greatly in their underlying technology and architecture. Since the introduction of intrusion detection decades ago, intrusion detection technologies have continued to evolve rapidly. This rapid change has led to the introduction of a wealth of security devices, technologies and algorithms that perform functions originally associated with intrusion detection systems. This thesis offers an analysis of intrusion detection technologies, proposing a new classification system for intrusion detection systems. Working closely with the development of a new intrusion detection product, this thesis introduces a method of testing related technologies in a production environment by outlining and executing a series of denial of service and scan and probe attacks. Based on the findings of these experiments, a series of enhancements to the core intrusion detection product is introduced to improve its capabilities and adapt to modem needs of security products