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C-NSA: a hybrid approach based on artificial immune algorithms for anomaly detection in web traffic

IET INFORMATION SECURITY 2020年第6期14卷 683-693页

作者： Dandil, Emre Bilecik Seyh Edebali Univ Fac Engn Dept Comp Engn Bilecik Turkey

Security vulnerabilities in web traffic can directly lead to data leak. Preventing these data leaks to a large extent has become an important problem to solve. Besides, the accurate detection and prevention of abnormal changes in web traffic is of great importance. In this study, a hybrid approach, called C-NSA, based on the negative selection algorithm (NSA) and clonal selection algorithm (CSA) of artificial immune systems for the detection of abnormal web traffic on the network is proposed and a user-friendly application software is developed. The real and synthetic data in the Yahoo Webscope S5 dataset are used for web traffic and the data are split into windows using the window sliding. In the experimental studies, the abnormal web traffic data is detected by monitoring the changes in the number of activated detectors in the C-NSA. It is observed that the average accuracy performance of finding anomalies in real web traffic data is 94.30% and the overall classification accuracy is 98.22% based on proposed approach. In addition, false positive rate of the proposed approach using C-NSA is obtained as 0.029. In addition, the results in synthetic web traffic data using C-NSA are achieved as average 98.57% classification accuracy.

关键词： pattern classification information filtering Internet security of data telecommunication traffic time series artificial immune systems C-NSA hybrid approach artificial immune algorithms shared data data leak rapid detection clonal selection algorithm abnormal web traffic abnormal traffic data synthetic web traffic data

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Evaluating Components of artificial immune algorithms: A Performance-aware Method based on Evolutionary Calibrator

Evaluating Components of Artificial Immune Algorithms: A Per...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Montero, Elizabeth Riff, Maria-Cristina Univ Tecn Federico Santa Maria Casilla 110-V Valparaiso Chile

ISBN: (纸本)9781479938407

We are interested in methods and strategies that allow us to simplify bio-inspired algorithms without reducing their accuracy. These algorithms are usually designed and implemented adding new components incrementally which makes inherently difficult to understand the relation between them and their individual contribution to the algorithm performance. In this paper, the information obtained when using a tuner to identify a set of good parameter values is analyzed and a method to use this tuner in order to help us to take design decisions is proposed. Our results are shown and our approach is validated using an artificial immune algorithm which has been proposed to solve multi-objective problems. The results show that these decisions lead to a code that is shorter than that of the initial algorithm while maintaining its performance.

关键词： artificial immune systems evolutionary computation artificial immune algorithms bio-inspired algorithms design decisions evolutionary calibrator multiobjective problems performance-aware method Algorithm design and analysis Cloning immune system Sociology Statistics Tuners

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Classification of Buildings Energetic Performance Using artificial immune algorithms 2

Classification of Buildings Energetic Performance Using Arti...

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2nd International Conference on Smart Energy Systems and Technologies (SEST)

作者： Alves, Jose Pedro Fidalgo, Jose Nuno Univ Porto FEUP Fac Engn Porto Portugal INESC TEC Inst Syst & Comp Engn Technol & Sci Porto Portugal

ISBN: (纸本)9781728111568

The building sector is responsible for a large share of Europe's energy consumption. Modelling buildings thermal behavior is a key factor for achieving the EU energy efficiency goals. Moreover, it can be used in load forecasting applications, for the prediction of buildings total energy consumption. The first phase of this work is the application of artificial immune Systems (AIS) for clustering buildings with similar physical characteristics and similar thermal efficiency. In the second phase, artificial Neural Networks (ANN) are used to estimate the buildings heating and cooling loads. A final sensitivity test is performed to identify which building features have the most impact on the heating and cooling loads. The results obtained in the first phase revealed very distinct cluster prototypes, which demonstrates the AIS discriminating ability. The good estimation performance obtained in the second phase showed that this approach can be integrated in energy efficiency audits. Finally, the sensitivity analysis provided indications for actions (or legislation directives) in order to promote the design of more efficient buildings.

关键词： artificial immune algorithms Clustering Energy efficiency Residential buildings artificial Neural Networks

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Credit Evaluation for Mobile Customers Using artificial immune algorithms

Credit Evaluation for Mobile Customers Using Artificial Immu...

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7th World Congress on Intelligent Control and Automation

作者： Yang Zong-chang Kuang Hong Hunan Univ Sci & Technol Sch Informat & Elect Engn Xiangtan 411201 Peoples R China Hunan Univ Sci & Technol Sch Arts & Design Xiangtan 411201 Peoples R China

ISBN: (纸本)9781424421138

To the arrears problem that puzzles most mobile A telephone corporations in China, based on artificial immune algorithms, a credit measure on customer's behavior attributes is defined and proposed to mobile telephone customers. The proposed measure gives good results when it is applied to the credit evaluation for the 400,000 customers in a Communication Branch of Guangdong in August and September, the correct evaluation rates for all the customers is about 82.0% and our proposed approach performances better than a BP neural network on the task. Our experimental results show that the management for the arrears problem on the basis of client credit evaluation is a considerable measure for applying, and others could benefit from ours.

关键词： Mobile communications Credit evaluation artificial immune algorithms BP neural networks

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Formalization Description of artificial immune algorithms Based on Intelligent Computation Framework

Formalization Description of Artificial Immune Algorithms Ba...

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7th World Congress on Intelligent Control and Automation

作者： Kang, Qi Lin, Xiaoqing Yan, Yong Wang, Lei Wu, Qidi Tongji Univ Shanghai 200092 Peoples R China

ISBN: (纸本)9781424421138

In the study of all kinds of intelligent algorithms, we find that different computation modes of agents take on relative uniform characteristic in all kinds of intelligent algorithms, though they usually have different extrinsic forms. In this paper, a kind of novel intelligent computation mode-artificial immune algorithms is adopted to validate this idea. Firstly, formalization description of artificial immune algorithms is proposed;and then the general framework description of artificial immune algorithms is discussed based on the uniform framework description of intelligent computation.

关键词： artificial immune algorithms intelligent computation general framework model formalization description

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Formalization Description of artificial immune algorithms Based on Intelligent Computation Framework

Formalization Description of Artificial Immune Algorithms Ba...

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7th World Congress on Intelligent Control and Automation (WCICA 2008), vol.2

作者： Qi Kang Xiaoqing Lin Yong Yan Lei Wang Qidi Wu University of Tongji Shanghai China Ministry of Education of China Beijing China

关键词： artificial immune algorithms Intelligent computation General framework model Formalization description

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Reducing calibration effort for clonal selection based algorithms: A reinforcement learning approach

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KNOWLEDGE-BASED SYSTEMS 2013年第Mar.期41卷 54-67页

作者： Cristina Riff, Maria Montero, Elizabeth Neveu, Bertrand Univ Tecn Federico Santa Maria Dept Informat Valparaiso Chile Ecole Ponts ParisTech Project Imagine Paris France

In this paper we introduce (C, n)-strategy which improves the former C-strategy for on-line calibration of Clonal Selection based algorithms. In this approach, we are focused on a trade-off between the intensification and the diversification of the algorithm search. By using our approach, it allows us to reduce the number of the parameters of the algorithm respecting both the original design of the algorithm and its performance. The number of selected cells and the number of clones are dynamically controlled on-line, according to the algorithm's behavior. We report statistical comparisons using well-known clonalg based algorithms for solving combinatorial optimization problems. From the tests, we conclude that the tuning effort for Clonalg based algorithms is strongly reduced using our technique. Moreover, the dynamic control does not decrease the performance of the original version of the algorithm. On the contrary, it has shown to improve it. (C) 2013 Elsevier B.V. All rights reserved.

关键词： On-line calibration Parameter control Tuning artificial immune algorithms Metaheuristics

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immune response-based algorithm for optimization of dynamic environments

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Journal of Central South University 2011年第5期18卷 1563-1571页

作者：史旭华钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology College of Information Science and Engineering Ningbo University

A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response *** dynamic process of artificial immune response with operators such as immune cloning,multi-scale variation and gradient-based diversity was *** the immune cloning operator was derived from a stimulation and suppression effect between antibodies and antigens,a sigmoid model that can clearly describe clonal proliferation was *** addition,with the introduction of multiple populations and multi-scale variation,the algorithm can well maintain the population diversity during the dynamic searching *** traditional artificial immune algorithms,which require randomly generated cells added to the current population to explore its fitness landscape,AIDE uses a gradient-based diversity operator to speed up the optimization in the dynamic *** reported algorithms were compared with AIDE by using Moving Peaks *** experiments show that AIDE can maintain high population diversity during the search process,simultaneously can speed up the ***,AIDE is useful for the optimization of dynamic environments.

关键词： dynamic optimization artificial immune algorithms immune response multi-scale variation

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An improved real-valued negative selection algorithm based on the constant detector for anomaly detection

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021年第5期40卷 8793-8806页

作者： Li, Dong Sun, Xin Gao, Furong Liu, Shulin Changzhou Univ Sch Petr Engn Changzhou Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai Peoples R China Hong Kong Univ Sci & Technol Dept Chem & Biol Engn Hong Kong Peoples R China

Compared with the traditional negative selection algorithms produce detectors randomly in whole state space, the boundary-fixed negative selection algorithm (FB-NSA) non-randomly produces a layer of detectors closely surrounding the self space. However, the false alarm rate of FB-NSA is higher than many anomaly detection methods. Its detection rate is very low when normal data close to the boundary of state space. This paper proposed an improved FB-NSA (IFB-NSA) to solve these problems. IFB-NSA enlarges the state space and adds auxiliary detectors in appropriate places to improve the detection rate, and uses variable-sized training samples to reduce the false alarm rate. We present experiments on synthetic datasets and the UCI Iris dataset to demonstrate the effectiveness of this approach. The results show that IFB-NSA outperforms FB-NSA and the other anomaly detection methods in most of the cases.

关键词： Negative selection algorithm anomaly detection artificial immune algorithms machine learning

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A Dynamic Adaptive Calibration of the CLONALG immune Algorithm

A Dynamic Adaptive Calibration of the CLONALG Immune Algorit...

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International Conference on Adaptive and Intelligent SystemsInternational Conference of Advances in Environmental Forensics

作者： Cristina Riff, Maria Montero, Elizabeth Univ Tecn Federico Santa Maria Dept Comp Sci Valparaiso Chile

ISBN: (纸本)9780769538273

The control of parameters during the execution of bio-inspired algorithms is an open research area. In this paper, we propose a new parameter control strategy for the immune algorithm CLONALG. Our approach is based on reinforcement learning ideas. We focus our attention on controlling the number of clones and the number of selected cells which follow a mutation process for improvement. Their values allow a trade-off between intensification and diversification of the search. Our approach provides an efficient and low cost adaptive technique for parameter control. We use instances of the Travelling Salesman Problem that has been tackled before by using CLONALG. The results obtained are very encouraging.

关键词： parameter control artificial immune algorithms

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