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Author: Mahbod Tavallaee
Publisher:
ISBN:
Category : Anomaly detection (Computer security)
Languages : en
Pages : 338
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Book Description
Author: Mahbod Tavallaee
Publisher:
ISBN:
Category : Anomaly detection (Computer security)
Languages : en
Pages : 338
Get Book Here
Book Description
Author: Álvaro Herrero
Publisher: Springer
ISBN: 3642182992
Category : Technology & Engineering
Languages : en
Pages : 151
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Book Description
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: Yang Xiao
Publisher: Springer Science & Business Media
ISBN: 0387331123
Category : Computers
Languages : en
Pages : 423
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Book Description
This book identifies vulnerabilities in the physical layer, the MAC layer, the IP layer, the transport layer, and the application layer, of wireless networks, and discusses ways to strengthen security mechanisms and services. Topics covered include intrusion detection, secure PHY/MAC/routing protocols, attacks and prevention, immunization, key management, secure group communications and multicast, secure location services, monitoring and surveillance, anonymity, privacy, trust establishment/management, redundancy and security, and dependable wireless networking.
Author: Lv, Zhihan
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 332
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Book Description
The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.
Author: Yihua Liao
Publisher:
ISBN:
Category :
Languages : en
Pages : 230
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Book Description
Detection of anomalies in data is one of the fundamental machine learning tasks. Anomaly detection provides the core technology for a broad spectrum of security-centric applications. In this dissertation, we examine various aspects of anomaly based intrusion detection in computer security. First, we present a new approach to learn program behavior for intrusion detection. Text categorization techniques are adopted to convert each process to a vector and calculate the similarity between two program activities. Then the k-nearest neighbor classifier is employed to classify program behavior as normal or intrusive. We demonstrate that our approach is able to effectively detect intrusive program behavior while a low false positive rate is achieved. Second, we describe an adaptive anomaly detection framework that is de- signed to handle concept drift and online learning for dynamic, changing environments. Through the use of unsupervised evolving connectionist systems, normal behavior changes are efficiently accommodated while anomalous activities can still be recognized. We demonstrate the performance of our adaptive anomaly detection systems and show that the false positive rate can be significantly reduced.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
A real-time intrusion detection system (IDS) has several performance objectives: good detection coverage, economy in resource usage, resilience to stress, and resistance to attacks upon itself. In this thesis, we argue that these objectives are trade-offs that must be considered not only in IDS design and implementation, but also in deployment and in an adaptive manner. A real-time IDS should perform performance adaptation by optimizing its configuration at run-time. We use classical optimization techniques for determining an optimal configuration. We describe an IDS architecture with multiple dynamically configured front-end and back-end detection modules and a monitor. The front-end does the real-time analysis and detection and the less time-critical tasks may be executed at the backend. In order to do performance adaptation, the front-end is modified to have two modules: performance monitoring and dynamic reconfiguration. The IDS run-time performance is measured periodically, and detection strategies and workload are dynamically reconfigured among the detection modules according to the resource constraints and cost-benefit analysis. The back-end also performs scenario (or trend) analysis to recognize on-going attack sequences, so that the predictions of the likely forthcoming attacks can be used to pro-actively and optimally configure the IDS. The adaptive IDS results showed better performance when the operating conditions changed and the IDS was stressed or overloaded. By reconfiguring, the adaptive IDS minimized packet drops and gave priority for critical attacks, with relatively higher damage cost, thereby ensuring maximum value for the IDS. The overheads involved for monitoring as well as reconfiguration was found to be negligible.
Author: Karen Scarfone
Publisher:
ISBN: 9781422312902
Category :
Languages : en
Pages : 127
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Book Description
Intrusion detection is the process of monitoring the events occurring in a computer system or network & analyzing them for signs of possible incidents, which are viol. or imminent threats of viol. of computer security policies, acceptable use policies, or standard security practices. Intrusion prevention is the process of performing intrusion detection to stop detected possible incidents. Intrusion detection & prevention systems (IDPS) record info. related to observed events, notify security admin. of important events, & produce reports. This pub. provides recommend. for designing, implementing, configuring, securing, monitoring, & maintaining IDPS¿s. Discusses 4 types of IDPS¿s: Network-Based; Wireless; Network Behavior Analysis; & Host-Based.
Author: Alfonso Valdes
Publisher: Springer Science & Business Media
ISBN: 3540317783
Category : Business & Economics
Languages : en
Pages : 360
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Book Description
This book constitutes the refereed proceedings of the 8th International Symposium on Recent Advances in Intrusion Detection held in September 2005. The 15 revised full papers and two practical experience reports were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on worm detection and containment, anomaly detection, intrusion prevention and response, intrusion detection based on system calls and network-based, as well as intrusion detection in mobile and wireless networks.
Author: S.G. Poonambalam
Publisher: Springer
ISBN: 3642351972
Category : Computers
Languages : en
Pages : 541
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Book Description
This book constitutes the proceedings of the First International Conference on Intelligent Robotics and Manufacturing, IRAM 2012, held in Kuala Lumpur, Malaysia, in November 2012. The 64 revised full papers included in this volume were carefully reviewed and selected from 102 initial submissions. The papers are organized in topical sections named: mobile robots, intelligent autonomous systems, robot vision and robust, autonomous agents, micro, meso and nano-scale automation and assembly, flexible manufacturing systems, CIM and micro-machining, and fabrication techniques.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The threats and intrusions in IT systems can basically be compared to human diseases with the difference that the human body has an effective way to deal with them, what still need to be designed for IT systems. The human immune system (HIS) can detect and defend against yet unseen intruders, is distributed, adaptive and multilayered to name only a few of its features. Our immune system incorporates a powerful and diverse set of characteristics which are very interesting to use in the design of Intrusion Detection Systems (IDS). The authors propose therefore a hybrid intrusion detection system which combines host based and network based components but giving the focus to the host based intrusion detection as it is similar to the HIS. The proposed intrusion detection system will use the concepts of the artificial immune systems (AIS) which is a promising biologically inspired computing model based on the HIS. This paper presents an intrusion detection system based on the model of the human immune system and which will use the artificial immune systems paradigm. Furthermore the paper will also introduce some yet unused AIS concepts that can be applied to improve the effectiveness of IDS.
