Mobile Hybrid Intrusion Detection
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Author | : Álvaro Herrero |
Publisher | : Springer Science & Business Media |
Total Pages | : 151 |
Release | : 2011-01-19 |
Genre | : Computers |
ISBN | : 3642182984 |
This monograph comprises work on network-based Intrusion Detection (ID) that is grounded in visualisation and hybrid Artificial Intelligence (AI). It has led to the design of MOVICAB-IDS (MObile VIsualisation Connectionist Agent-Based IDS), a novel Intrusion Detection System (IDS), which is comprehensively described in this book. This novel IDS combines different AI paradigms to visualise network traffic for ID at packet level. It is based on a dynamic Multiagent System (MAS), which integrates an unsupervised neural projection model and the Case-Based Reasoning (CBR) paradigm through the use of deliberative agents that are capable of learning and evolving with the environment. The proposed novel hybrid IDS provides security personnel with a synthetic, intuitive snapshot of network traffic and protocol interactions. This visualisation interface supports the straightforward detection of anomalous situations and their subsequent identification. The performance of MOVICAB-IDS was tested through a novel mutation-based testing method in different real domains which entailed several attacks and anomalous situations.
Author | : Ãlvaro Herrero |
Publisher | : |
Total Pages | : 158 |
Release | : 2011-03-13 |
Genre | : |
ISBN | : 9783642183003 |
Author | : Álvaro Herrero |
Publisher | : |
Total Pages | : 240 |
Release | : 2009 |
Genre | : |
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Author | : Georgios Kambourakis |
Publisher | : CRC Press |
Total Pages | : 559 |
Release | : 2017-09-06 |
Genre | : Computers |
ISBN | : 1315305828 |
This book presents state-of-the-art contributions from both scientists and practitioners working in intrusion detection and prevention for mobile networks, services, and devices. It covers fundamental theory, techniques, applications, as well as practical experiences concerning intrusion detection and prevention for the mobile ecosystem. It also includes surveys, simulations, practical results and case studies.
Author | : Georgios Kambourakis |
Publisher | : CRC Press |
Total Pages | : 477 |
Release | : 2017-09-06 |
Genre | : Computers |
ISBN | : 131530581X |
This book presents state-of-the-art contributions from both scientists and practitioners working in intrusion detection and prevention for mobile networks, services, and devices. It covers fundamental theory, techniques, applications, as well as practical experiences concerning intrusion detection and prevention for the mobile ecosystem. It also includes surveys, simulations, practical results and case studies.
Author | : 廖證模 |
Publisher | : |
Total Pages | : |
Release | : 2017 |
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ISBN | : |
Author | : Kayvan Atefi |
Publisher | : |
Total Pages | : |
Release | : 2013 |
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Author | : Zhenwei Yu |
Publisher | : World Scientific |
Total Pages | : 185 |
Release | : 2011 |
Genre | : Computers |
ISBN | : 1848164475 |
Introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. This title also includes the performance comparison of various IDS via simulation.
Author | : Mahbod Tavallaee |
Publisher | : |
Total Pages | : 338 |
Release | : 2011 |
Genre | : Anomaly detection (Computer security) |
ISBN | : |
Author | : Varsha Sainani |
Publisher | : |
Total Pages | : |
Release | : 2009 |
Genre | : |
ISBN | : |
The increasing number of network security related incidents has made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). Detecting intrusion in a distributed network from outside network segment as well as from inside is a difficult problem. IDSs are expected to analyze a large volume of data while not placing a significant added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel hybrid layered multiagent-based intrusion detection system is created, particularly with the support of a multi-class supervised classification technique. In agent-based IDS, there is no central control and therefore no central point of failure. Agents can detect and take predefined actions against malicious activities, which can be detected with the help of data mining techniques. The proposed IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDSs with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on a multiagent platform along with a supervised classification technique. Applying multiagent technology to the management of network security is a challenging task since it requires the management on different time instances and has many interactions. To facilitate information exchange between different agents in the proposed hybrid layered multiagent architecture, a low cost and low response time agent communication protocol is developed to tackle the issues typically associated with a distributed multiagent system, such as poor system performance, excessive processing power requirement, and long delays. The bandwidth and response time performance of the proposed end-to-end system is investigated through the simulation of the proposed agent communication protocol on our private LAN testbed called Hierarchical Agent Network for Intrusion Detection Systems (HAN-IDS). The simulation results show that this system is efficient and extensible since it consumes negligible bandwidth with low cost and low response time on the network.