Negative Selection Algorithm Research and Applications in the Last Decade: A Review

The Negative selection Algorithm (NSA) is one of the important methods in the field of Immunological Computation (or Artificial Immune Systems). Over the years, some progress was made which turns this algorithm (NSA) into an efficient approach to solve problems in different domain. This review takes into account these signs of progress during the last decade and categorizes those based on different characteristics and performances. Our study shows that NSA's evolution can be labeled in four ways highlighting the most notable NSA variations and their limitations in different application domains. We also present alternative approaches to NSA for comparison and analysis. It is evident that NSA performs better for nonlinear representation than most of the other methods, and it can outperform neural-based models in computation time. We summarize NSA's development and highlight challenges in NSA research in comparison with other similar models.

[1]  Tao Li,et al.  A negative selection algorithm based on hierarchical clustering of self set , 2011, Science China Information Sciences.

[2]  Hans-Peter Kriegel,et al.  Angle-based outlier detection in high-dimensional data , 2008, KDD.

[3]  Fabio A. González,et al.  A Randomized Real-Valued Negative Selection Algorithm , 2003, ICARIS.

[4]  Li Sun,et al.  A new Trojan horse detection method based on negative selection algorithm , 2012 .

[5]  Rubita Sudirman,et al.  EEG Signals Classification Using a Hybrid Method Based on Negative Selection and Particle Swarm Optimization , 2012, MLDM.

[6]  Stephanie Forrest,et al.  A sense of self for Unix processes , 1996, Proceedings 1996 IEEE Symposium on Security and Privacy.

[7]  Paul Helman,et al.  Negative representations of information , 2009, International Journal of Information Security.

[8]  Rozaida Ghazali,et al.  Application of Real-Valued Negative Selection Algorithm to Improve Medical Diagnosis , 2016 .

[9]  Esma Bendiab,et al.  The Negative Selection Algorithm: a Supervised Learning Approach for Skin Detection and Classification. , 2010 .

[10]  Mo-Yuen Chow,et al.  Multi-Level Optimization Of Negative Selection Algorithm Detectors With Application In Motor Fault Detection , 2010, Intell. Autom. Soft Comput..

[11]  Pan Yong-xiang An Improved Intrusion Detection Negative Selection Immune Algorithm , 2005 .

[12]  Guang-Zhong Yang,et al.  Body sensor networks , 2006 .

[13]  Fabio A. González,et al.  An Imunogenetic Technique To Detect Anomalies In Network Traffic , 2002, GECCO.

[14]  Mo-Yuen Chow,et al.  A neural networks-based negative selection algorithm in fault diagnosis , 2007, Neural Computing and Applications.

[15]  Michael I. Jordan,et al.  Variational inference for Dirichlet process mixtures , 2006 .

[16]  Hao Jiang,et al.  Authentication by Encrypted Negative Password , 2019, IEEE Transactions on Information Forensics and Security.

[17]  Ali Selamat,et al.  Improved email spam detection model with negative selection algorithm and particle swarm optimization , 2014, Appl. Soft Comput..

[18]  Zhou Ji,et al.  Real-Valued Negative Selection Algorithm with Variable-Sized Detectors , 2004, GECCO.

[19]  Seyedeh Negin Seyed Fakhari,et al.  NSSAC: Negative selection-based self adaptive classifier , 2011, 2011 International Symposium on Innovations in Intelligent Systems and Applications.

[20]  Dipankar Dasgupta,et al.  Novelty detection in time series data using ideas from immunology , 1996 .

[21]  Weijian Ren,et al.  Research of Pump-Jack Fault Diagnosis Method Based on the Negative Selection Algorithm , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[22]  Vipin Kumar,et al.  Feature bagging for outlier detection , 2005, KDD '05.

[23]  ShimKyuseok,et al.  Efficient algorithms for mining outliers from large data sets , 2000 .

[24]  Rozaida Ghazali,et al.  Negative Selection Algorithm: A Survey on the Epistemology of Generating Detectors , 2013, DaEng.

[25]  Yasushi Makihara,et al.  The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication , 2014, Pattern Recognit..

[26]  Cai Zhenhua Negative selection algorithm of fault diagnosis for hydroelectric generating set , 2006 .

[27]  Mia Hubert,et al.  Minimum covariance determinant and extensions , 2017, 1709.07045.

[28]  Zhou Ji,et al.  Applicability issues of the real-valued negative selection algorithms , 2006, GECCO '06.

[29]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[30]  Khashayar Khorasani,et al.  A Dendritic Cell Immune System Inspired Scheme for Sensor Fault Detection and Isolation of Wind Turbines , 2018, IEEE Transactions on Industrial Informatics.

[31]  Georg Langs,et al.  Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery , 2017, IPMI.

[32]  Jie Chen,et al.  Fault Detection of Aircraft Control System Based on Negative Selection Algorithm , 2020 .

[33]  Prabhakar Raghavan,et al.  A Linear Method for Deviation Detection in Large Databases , 1996, KDD.

[34]  D. Dasgupta,et al.  Immunity-based systems: a survey , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[35]  Li Tao,et al.  An Antigen Space Triangulation Coverage Based Real-Value Negative Selection Algorithm , 2019, IEEE Access.

[36]  Meng Wang,et al.  Generative Adversarial Active Learning for Unsupervised Outlier Detection , 2018, IEEE Transactions on Knowledge and Data Engineering.

[37]  Li Tao,et al.  Parameter analysis of negative selection algorithm , 2017, Inf. Sci..

[38]  Dipankar Dasgupta,et al.  Immunological Computation: Theory and Applications , 2008 .

[39]  Norita Md Norwawi,et al.  An Early Warning System for Reservoir Water Release Operation Using Agent-Based Negative Selection Model , 2020 .

[40]  Qi Jin,et al.  A method to construct self set for IDS based on negative selection algorithm , 2011, 2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC).

[41]  Ngoc Thanh Nguyen,et al.  A combined negative selection algorithm-particle swarm optimization for an email spam detection system , 2015, Eng. Appl. Artif. Intell..

[42]  Izhar ul Haq,et al.  An Improved Negative Selection Algorithm-Based Fault Detection Method , 2020, IETE Journal of Research.

[43]  See-Kiong Ng,et al.  Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series , 2018, ArXiv.

[44]  Amod Kumar,et al.  Improved thresholding based on negative selection algorithm (NSA) , 2014, Evol. Intell..

[45]  D. Dasgupta,et al.  Advances in artificial immune systems , 2006, IEEE Computational Intelligence Magazine.

[46]  Dong Li,et al.  A negative selection algorithm with online adaptive learning under small samples for anomaly detection , 2015, Neurocomputing.

[47]  Zengyou He,et al.  Discovering cluster-based local outliers , 2003, Pattern Recognit. Lett..

[48]  Tao Li,et al.  An antigen space density based real-value negative selection algorithm , 2017, Appl. Soft Comput..

[49]  Dong Li,et al.  A boundary-fixed negative selection algorithm with online adaptive learning under small samples for anomaly detection , 2016, Eng. Appl. Artif. Intell..

[50]  Tarek N. Saadawi,et al.  Distributed Network Intrusion Detection Systems: An Artificial Immune System Approach , 2016, 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

[51]  Sridhar Ramaswamy,et al.  Efficient algorithms for mining outliers from large data sets , 2000, SIGMOD '00.

[52]  Ying Tan,et al.  A malware detection model based on a negative selection algorithm with penalty factor , 2010, Science China Information Sciences.

[53]  Fuyong Zhang,et al.  Integrated Negative Selection Algorithm and Positive Selection Algorithm for malware detection , 2016, 2016 International Conference on Progress in Informatics and Computing (PIC).

[54]  Henri Pierreval,et al.  Fault detection, diagnosis and recovery using Artificial Immune Systems: A review , 2015, Eng. Appl. Artif. Intell..

[55]  Stephanie Forrest,et al.  A Relational Algebra for Negative Databases , 2007 .

[56]  Rogério de Lemos,et al.  Negative Selection: How to Generate Detectors , 2002 .

[57]  Clayton D. Scott,et al.  Robust kernel density estimation , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[58]  Salim Chikhi,et al.  A New Negative Selection Algorithm for Adaptive Network Intrusion Detection System , 2014, Int. J. Inf. Secur. Priv..

[59]  D. Wong,et al.  Negative Selection Algorithm for Aircraft Fault Detection , 2004, ICARIS.

[60]  John R. Williams,et al.  G-NAS: A grid-based approach for negative authentication , 2014, 2014 IEEE Symposium on Computational Intelligence in Cyber Security (CICS).

[61]  Hongli Deng,et al.  A negative selection algorithm based on adaptive immunoregulation , 2020, 2020 5th International Conference on Computational Intelligence and Applications (ICCIA).

[62]  Ali Selamat,et al.  Hybrid email spam detection model with negative selection algorithm and differential evolution , 2014, Eng. Appl. Artif. Intell..

[63]  Tomás Pevný,et al.  Loda: Lightweight on-line detector of anomalies , 2016, Machine Learning.

[64]  Hans-Peter Kriegel,et al.  LOF: identifying density-based local outliers , 2000, SIGMOD '00.

[65]  Yang Chunying,et al.  Optimization and Application of Real-Valued Negative Selection Algorithm , 2011 .

[66]  Dechang Pi,et al.  BIORV-NSA: Bidirectional inhibition optimization r-variable negative selection algorithm and its application , 2015, Appl. Soft Comput..

[67]  Vladimir Poulkov,et al.  Multiple negative selection algorithm: Improving detection error rates in IoT intrusion detection systems , 2017, 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS).

[68]  Charu C. Aggarwal,et al.  Outlier Analysis , 2013, Springer New York.

[69]  Xiao Zhi Gao,et al.  Particle Swarm Optimization of detectors in Negative Selection Algorithm , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[70]  Daniel Jung,et al.  A Combined Data-Driven and Model-Based Residual Selection Algorithm for Fault Detection and Isolation , 2019, IEEE Transactions on Control Systems Technology.

[71]  Bharanidharan Shanmugam,et al.  An Intelligent Spam Detection Model Based on Artificial Immune System , 2019, Inf..

[73]  Abdelouahid Derhab,et al.  NSNAD: negative selection-based network anomaly detection approach with relevant feature subset , 2019, Neural Computing and Applications.

[74]  Zhou Ji,et al.  V-detector: An efficient negative selection algorithm with "probably adequate" detector coverage , 2009, Inf. Sci..

[75]  Jian Tang,et al.  Enhancing Effectiveness of Outlier Detections for Low Density Patterns , 2002, PAKDD.

[76]  Mo-Yuen Chow,et al.  Clonal Optimization of Negative Selection Algorithm with Applications in Motor Fault Detection , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[77]  Dipankar Dasgupta,et al.  Password Security through Negative Filtering , 2010, 2010 International Conference on Emerging Security Technologies.

[78]  Utpal Garain,et al.  Recognition of Handwritten Indic Script Using Clonal Selection Algorithm , 2006, ICARIS.

[79]  Yue Zhao,et al.  XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning , 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

[80]  Paul Helman,et al.  Enhancing Privacy through Negative Representations of Data , 2004 .

[81]  Moon,et al.  Estimation of mutual information using kernel density estimators. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[82]  Fabio A. González,et al.  An immunity-based technique to characterize intrusions in computer networks , 2002, IEEE Trans. Evol. Comput..

[83]  Alan S. Perelson,et al.  Self-nonself discrimination in a computer , 1994, Proceedings of 1994 IEEE Computer Society Symposium on Research in Security and Privacy.

[84]  Peng Zhao,et al.  A matrix negative selection algorithm for anomaly detection , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[85]  Mehmet Karaköse,et al.  Chaotic-based hybrid negative selection algorithm and its applications in fault and anomaly detection , 2010, Expert Syst. Appl..

[86]  Tuan Dinh Le,et al.  A Combination of Negative Selection Algorithm and Artificial Immune Network for Virus Detection , 2014, FDSE.

[87]  Zhi-Hua Zhou,et al.  Isolation Forest , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[88]  Leandro Nunes de Castro,et al.  ARTIFICIAL IMMUNE SYSTEMS: PART II - A SURVEY OF APPLICATIONS , 2000 .

[89]  Cezar Ionescu,et al.  COPOD: Copula-Based Outlier Detection , 2020, 2020 IEEE International Conference on Data Mining (ICDM).

[90]  Muhammad Tahir Khan,et al.  Multidomain Features-Based GA Optimized Artificial Immune System for Bearing Fault Detection , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[91]  Geoffrey E. Hinton,et al.  Reducing the Dimensionality of Data with Neural Networks , 2006, Science.

[92]  Andreas Dengel,et al.  Histogram-based Outlier Score (HBOS): A fast Unsupervised Anomaly Detection Algorithm , 2012 .

[93]  Hamid Jazayeriy,et al.  Intrusion Detection systems using Real-Valued Negative Selection Algorithm with Optimized Detectors , 2019, 2019 5th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS).

[94]  Zhou Ji,et al.  Revisiting Negative Selection Algorithms , 2007, Evolutionary Computation.

[95]  Walmir M. Caminhas,et al.  Design of an Artificial Immune System for fault detection: A Negative Selection Approach , 2010, Expert Syst. Appl..

[96]  Zhou Ji,et al.  A BOUNDARY-AWARE NEGATIVE SELECTION ALGORITHM , 2005 .

[97]  Max Welling,et al.  Auto-Encoding Variational Bayes , 2013, ICLR.

[98]  Raja Chiky,et al.  Anomaly Detection for Data Streams Based on Isolation Forest Using Scikit-Multiflow , 2020, ICCSA.

[99]  Abbas Z. Kouzani,et al.  Applications and Evaluations of Bio-Inspired Approaches in Cloud Security: A Review , 2020, IEEE Access.

[100]  David M. Rocke,et al.  Outlier detection in the multiple cluster setting using the minimum covariance determinant estimator , 2004, Comput. Stat. Data Anal..

[101]  Xu Min-qiang Fault diagnosis for gas valve based on negative selection algorithm , 2006 .

[102]  Dimitar Kazakov,et al.  Modeling the behavior of the stock market with an Artificial Immune System , 2010, IEEE Congress on Evolutionary Computation.

[103]  S. Chikhi,et al.  Negative Selection Algorithm : Recent Improvements and Its Application in Intrusion Detection System , 2017 .

[104]  Chen Xi Application of negative selection mutation algorithm in E-mail filter , 2006 .

[105]  Zhe Wang,et al.  GF-NSA: A Negative Selection Algorithm Based on Self Grid File , 2010 .

[106]  Honghua Dai,et al.  An Extended Negative Selection Algorithm for Anomaly Detection , 2004, PAKDD.

[107]  Wang Xu,et al.  An Artificial Immune Method for Stock Market Avoiding Control of Hedge Fund , 2007, Third International Conference on Natural Computation (ICNC 2007).

[108]  Heiko Hoffmann,et al.  Kernel PCA for novelty detection , 2007, Pattern Recognit..

[109]  Zhou Ji,et al.  Artificial immune system (AIS) research in the last five years , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[110]  Zhou Ji,et al.  Analysis of Dental Images using Artificial Immune Systems , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[111]  S.J. Ovaska,et al.  Genetic Algorithms-based Detector Generation in Negative Selection Algorithm , 2006, 2006 IEEE Mountain Workshop on Adaptive and Learning Systems.

[112]  Xianghua Wang,et al.  A Novel Fault Diagnosis Method Based on Improved Negative Selection Algorithm , 2021, IEEE Transactions on Instrumentation and Measurement.

[113]  Dipankar Dasgupta,et al.  An immunogenetic approach in chemical spectrum recognition , 2003 .

[114]  Mo-Yuen Chow,et al.  Neural networks-based negative selection algorithm with applications in fault diagnosis , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[115]  Tao Li,et al.  An Outlier Robust Negative Selection Algorithm Inspired by Immune Suppression , 2010, J. Comput..

[116]  Wu Bin,et al.  Smartphone malware detection model based on artificial immune system , 2014, China Communications.

[117]  James Brown,et al.  Detection of Mobile Malware: An Artificial Immunity Approach , 2016, 2016 IEEE Security and Privacy Workshops (SPW).

[118]  Tao Yang,et al.  A Quick Negative Selection Algorithm for One-Class Classification in Big Data Era , 2017 .

[119]  U. JothiLakshmi A Novel Method to Detect False Financial Statement using Negative Selection Algorithm , 2014 .

[120]  Tao Li,et al.  Negative selection algorithm based on grid file of the feature space , 2014, Knowledge-Based Systems.

[121]  Dipankar Dasgupta,et al.  Artificial immune systems in industrial applications , 1999, Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296).

[122]  Douglas A. Reynolds,et al.  Gaussian Mixture Models , 2018, Encyclopedia of Biometrics.

[123]  Salau-Ibrahim Taofeekat Tosin,et al.  Negative Selection Algorithm Based Intrusion Detection Model , 2020, 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON).

[124]  Yue Zhao,et al.  PyOD: A Python Toolbox for Scalable Outlier Detection , 2019, J. Mach. Learn. Res..

[125]  R. O. Canham,et al.  A MULTILAYERED IMMUNE SYSTEM FOR HARDWARE FAULT TOLERANCE WITHIN AN EMBRYONIC ARRAY , 2002 .

[126]  Shi Wengang,et al.  Negative-selection algorithm based approach for fault diagnosis of rotary machinery , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[127]  Martin Mozina,et al.  Orange: data mining toolbox in python , 2013, J. Mach. Learn. Res..

[128]  Alireza Nowroozi,et al.  A novel sophisticated hybrid method for intrusion detection using the artificial immune system , 2021, J. Inf. Secur. Appl..

[129]  D. Dasgupta,et al.  Combining negative selection and classification techniques for anomaly detection , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[130]  Wu Ze-jun,et al.  An Artificial Immune Model for Abnormal Fluctuation of Stock Price , 2008, 2008 International Symposium on Computational Intelligence and Design.

[131]  Kwee-Bo Sim,et al.  Modeling of Positive Selection for the Development of a Computer Immune System and a Self-Recognition Algorithm , 2003 .

[132]  Kwee-Bo Sim,et al.  Negative Selection Algorithm for DNA Sequence Classification , 2004, Int. J. Fuzzy Log. Intell. Syst..

[133]  Fabio A. González,et al.  The Effect of Binary Matching Rules in Negative Selection , 2003, GECCO.

[134]  Datong Liu,et al.  UAV Sensor Fault Detection Using a Classifier without Negative Samples: A Local Density Regulated Optimization Algorithm† , 2019, Sensors.

[135]  Max H. Garzon,et al.  A DNA based artificial immune system for self-nonself discrimination , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[136]  Thomas S. Huang,et al.  One-class SVM for learning in image retrieval , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[137]  Zhao Jian-feng Negative selection algorithm based on fuzzy control theory and genetic algorithm , 2007 .

[138]  Andrew Mor-Yaroslavtsev,et al.  Rolling stock location data analysis using an immune algorithm on an intelligent embedded device , 2011, 2011 19thTelecommunications Forum (TELFOR) Proceedings of Papers.

[139]  Steffen Heber,et al.  Using a Novel Negative Selection Inspired Anomaly Detection Algorithm to Identify Corrupted Ribo-seq and RNA-seq Samples , 2019, BCB.

[140]  Dipankar Dasgupta,et al.  Tool Breakage Detection in Milling Operations using a Negative-Selection Algorithm , 1995 .

[141]  Cecilia Surace,et al.  Novelty detection in a changing environment: A negative selection approach , 2010 .

[142]  Qi Gong,et al.  Ransomware detection based on V-detector negative selection algorithm , 2017, 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC).

[143]  Yue Zhao,et al.  LSCP: Locally Selective Combination in Parallel Outlier Ensembles , 2018, SDM.

[144]  Dong Li,et al.  Negative selection algorithm with constant detectors for anomaly detection , 2015, Appl. Soft Comput..

[145]  Rongshuai Li,et al.  Hybrid immune algorithm for structural health monitoring using acceleration data , 2011 .

[146]  Xufei Zheng,et al.  The Dual Negative Selection Algorithm Based on Pattern Recognition Receptor Theory and Its Application in Two-class Data Classification , 2013, J. Comput..

[147]  Peter J. Bentley,et al.  Negative selection and niching by an artificial immune system for network intrusion detection , 1999 .

[148]  Xin Wang,et al.  A Novel Fast Negative Selection Algorithm Enhanced by State Graphs , 2007, ICARIS.

[149]  Hans-Peter Kriegel,et al.  Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data , 2009, PAKDD.

[150]  J. McInerney,et al.  An algorithm for detecting directional and non-directional positive selection, neutrality and negative selection in protein coding DNA sequences. , 2002, Gene.

[151]  Fernando Niño,et al.  A Framework for Evolving Multi-Shaped Detectors in Negative Selection , 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

[152]  Paulo B. Lourenço,et al.  Deterministically generated negative selection algorithm for damage detection in civil engineering systems , 2019, Engineering Structures.

[153]  Mohammad Kazem Akbari,et al.  Credit cards fraud detection by negative selection algorithm on hadoop (To reduce the training time) , 2013, The 5th Conference on Information and Knowledge Technology.

[154]  Dipankar Dasgupta,et al.  A study of artificial immune systems applied to anomaly detection , 2003 .

[155]  Jinquan Zeng,et al.  An Extended Negative Selection Algorithm for Unknown Malware Detection , 2016 .

[156]  Wenjing Liu,et al.  A Negative Selection Algorithm-Based Identification Framework for Distribution Network Faults With High Resistance , 2019, IEEE Access.

[157]  Azuraliza Abu Bakar,et al.  Negative selection algorithm for dengue outbreak detection , 2013 .

[158]  Zhou Ji,et al.  Estimating the detector coverage in a negative selection algorithm , 2005, GECCO '05.

[159]  Li Tao,et al.  A self-adaptive negative selection algorithm used for anomaly detection , 2009 .

[160]  Paulo B. Lourenço,et al.  Negative selection algorithm based methodology for online structural health monitoring , 2021 .

[161]  Yuan Gao,et al.  Shape-space based negative selection algorithm and its application on power transformer fault diagnosis , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[162]  Stephen R. Marsland,et al.  A self-organising network that grows when required , 2002, Neural Networks.

[163]  M. Hassan,et al.  Negative database authentication using SAT a like method , 2012, 2012 8th International Conference on Informatics and Systems (INFOS).

[164]  Tao Li,et al.  An immune optimization based real-valued negative selection algorithm , 2014, Applied Intelligence.

[165]  Fabio A. González,et al.  Anomaly Detection Using Real-Valued Negative Selection , 2003, Genetic Programming and Evolvable Machines.

[166]  Salim Chikhi,et al.  Clustered negative selection algorithm and fruit fly optimization for email spam detection , 2019, J. Ambient Intell. Humaniz. Comput..

[167]  Jie Zhang,et al.  EvoSeedRNSAII: An improved evolutionary algorithm for generating detectors in the real-valued Negative Selection Algorithms , 2014, Appl. Soft Comput..

[168]  H. von Boehmer,et al.  Self-nonself discrimination by T cells. , 1990, Science.