Artificial Immune Systems approaches to secure the internet of things: A systematic review of the literature and recommendations for future research

Abstract As the Internet of Things (IoT) recently attains tremendous popularity, this promising technology leads to a variety of security challenges. The traditional solutions do not fit the new challenges brought by the IoT ecosystem. Although the development's area of Artificial Immune Systems (AIS) provides an opportunity to improve security issues and create a fertile and exciting environment for further research and experiments, there is not any systematic and comprehensive study about analyzing its importance for IoT environment. Therefore, this work aims to identify, evaluate, and perform a comprehensive study of empirical research on the studies of AIS approaches to secure the IoT environment. The relevant and high-quality studies are addressing using three research questions about the main research motivations, existing solutions, and future gaps and directions. The AIS approaches have been divided into three main categories based on IoT layers, and detailed classifications have also been included based on different parameters. To achieve this aim, the authors use a systematic literature review (SLR) as a powerful method to collect and critically analyze the research papers. Also, the authors discuss the selected studies and their main techniques, as well as their benefits and drawbacks in general. This research process strives to build a knowledge base for AIS solutions under the umbrella of IoT security and suggest directions for future research.

[1]  Y. S. Kumaraswamy,et al.  Modified Danger Theory based optimized artificial immune network on resiliency in cyber-physical system , 2015, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT).

[2]  Renfa Li,et al.  An Immunity-Based IOT Environment Security Situation Awareness Model , 2017 .

[3]  Yaochu Jin,et al.  Immune-Endocrine System Inspired Hierarchical Coevolutionary Multiobjective Optimization Algorithm for IoT Service , 2020, IEEE Transactions on Cybernetics.

[4]  George C. Hadjichristofi,et al.  Internet of Things: Security vulnerabilities and challenges , 2015, 2015 IEEE Symposium on Computers and Communication (ISCC).

[5]  Jerne Nk Towards a network theory of the immune system. , 1974 .

[6]  Marcus O'Dair Blockchain: The Internet of Value , 2019 .

[7]  Gregg H. Gunsch,et al.  An artificial immune system architecture for computer security applications , 2002, IEEE Trans. Evol. Comput..

[8]  Dipankar Dasgupta,et al.  A Survey of Recent Works in Artificial Immune Systems , 2016 .

[9]  Andreas Pitsillides,et al.  Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures , 2014, IEEE Communications Surveys & Tutorials.

[10]  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.

[11]  Juan Carlos De Martin,et al.  Blockchain for the Internet of Things: A systematic literature review , 2016, 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA).

[12]  Mohsen Guizani,et al.  The rise of ransomware and emerging security challenges in the Internet of Things , 2017, Comput. Networks.

[13]  Meir Shimon,et al.  Self-Calibration of CMB Polarization Experiments , 2012, 1211.5734.

[14]  Maurizio A. Spirito,et al.  Denial-of-Service detection in 6LoWPAN based Internet of Things , 2013, 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[15]  M. Petticrew,et al.  Systematic Reviews in the Social Sciences: A Practical Guide , 2005 .

[16]  Nalini Venkatasubramanian,et al.  A Software Defined Networking architecture for the Internet-of-Things , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).

[17]  Xinzheng Dong,et al.  Application of dynamic variable cipher security certificate in Internet of Things , 2012, 2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems.

[18]  Liping Guo,et al.  Investigation of the effects of surface chemistry on adsorption of albumin by surface-enhanced FTIR spectroscopy , 2013 .

[19]  Qiang Ni,et al.  Application of reinforcement learning for security enhancement in cognitive radio networks , 2015, Appl. Soft Comput..

[20]  Jonathan Timmis,et al.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[21]  Ramjee Prasad,et al.  Proposed Security Model and Threat Taxonomy for the Internet of Things (IoT) , 2010, CNSA.

[22]  Sanguthevar Rajasekaran,et al.  Artificial Immune Systems: Models, Applications, and challenges , 2012, SAC '12.

[23]  Jerome Henry,et al.  IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things , 2017 .

[24]  G W Hoffmann,et al.  A neural network model based on the analogy with the immune system. , 1986, Journal of theoretical biology.

[25]  Feng Wang,et al.  A Survey of Artificial Immune System Based Intrusion Detection , 2014, TheScientificWorldJournal.

[26]  Jonathan Timmis,et al.  A resource limited artificial immune system for data analysis , 2001, Knowl. Based Syst..

[27]  Alan S. Perelson,et al.  The immune system, adaptation, and machine learning , 1986 .

[28]  P. Matzinger The Danger Model: A Renewed Sense of Self , 2002, Science.

[29]  Maciej Brzozowski,et al.  Immune Approach to the Protection of IoT Devices , 2016, FDSE.

[30]  Honghua Dai,et al.  Constructing Detectors in Schema Complementary Space for Anomaly Detection , 2004, GECCO.

[31]  Jean-Gabriel Ganascia,et al.  The Artificial Immune Systems Domain: Identifying Progress and Main Contributors Using Publication and Co-Authorship Analyses , 2013, ECAL.

[32]  P. Balamuralidhar,et al.  A graph theory based generic risk assessment framework for internet of things (IoT) , 2017, 2017 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS).

[33]  Rafal Drezewski,et al.  The application of social network analysis algorithms in a system supporting money laundering detection , 2015, Inf. Sci..

[34]  Peng Jiang,et al.  A Survey on the Security of Blockchain Systems , 2017, Future Gener. Comput. Syst..

[35]  Yoshiki Uchikawa,et al.  Emergent construction of artificial immune networks for autonomous mobile robots , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[36]  Alex Alves Freitas,et al.  Revisiting the Foundations of Artificial Immune Systems for Data Mining , 2007, IEEE Transactions on Evolutionary Computation.

[37]  Sudipta Mahapatra,et al.  A comparative analysis of machine learning techniques for botnet detection , 2017, SIN.

[38]  Ying Tan,et al.  An Intelligent Multifeature Statistical Approach for the Discrimination of Driving Conditions of a Hybrid Electric Vehicle , 2011, IEEE Transactions on Intelligent Transportation Systems.

[39]  Sayan Kumar Ray,et al.  Secure routing for internet of things: A survey , 2016, J. Netw. Comput. Appl..

[40]  Kim-Kwang Raymond Choo,et al.  Blockchain-Based Security Layer for Identification and Isolation of Malicious Things in IoT: A Conceptual Design , 2018, 2018 27th International Conference on Computer Communication and Networks (ICCCN).

[41]  AirehrourDavid,et al.  Secure routing for internet of things , 2016 .

[42]  Miroslav Vujić,et al.  Classification of Security Risks in the IoT Environment , 2016 .

[43]  Dana Kulic,et al.  Data augmentation of wearable sensor data for parkinson’s disease monitoring using convolutional neural networks , 2017, ICMI.

[44]  Luigi Atzori,et al.  Friendship Selection in the Social Internet of Things: Challenges and Possible Strategies , 2015, IEEE Internet of Things Journal.

[45]  Rongfang Bie,et al.  Artificial Immune Networks: Models and Applications , 2006 .

[46]  F. Agakov,et al.  Application of high-dimensional feature selection: evaluation for genomic prediction in man , 2015, Scientific Reports.

[47]  K. P. Singh,et al.  Support vector machines in water quality management. , 2011, Analytica chimica acta.

[48]  Julie Greensmith,et al.  Sensing Danger: Innate Immunology for Intrusion Detection , 2007, Inf. Secur. Tech. Rep..

[49]  Stephanie Forrest,et al.  Infect Recognize Destroy , 1996 .

[50]  P. Richter,et al.  A network theory of the immune system , 1975, European journal of immunology.

[51]  Carlos A. Coello Coello,et al.  Solving Multiobjective Optimization Problems Using an Artificial Immune System , 2005, Genetic Programming and Evolvable Machines.

[52]  Anthony Skjellum,et al.  Using machine learning to secure IoT systems , 2016, 2016 14th Annual Conference on Privacy, Security and Trust (PST).

[53]  Heena Rathore Bio-inspired Software-Defined Networking , 2016 .

[54]  Peter Stone,et al.  Transfer Learning for Reinforcement Learning Domains: A Survey , 2009, J. Mach. Learn. Res..

[55]  Aris S. Lalos,et al.  Secure and Safe IIoT Systems via Machine and Deep Learning Approaches , 2019, Security and Quality in Cyber-Physical Systems Engineering.

[56]  Omair Ahmad Khan,et al.  Software Defined Network (SDN) Based Internet of Things (IoT): A Road Ahead , 2017, ICFNDS.

[57]  Hong Liu,et al.  Cyber-Physical-Social Based Security Architecture for Future Internet of Things , 2012, IOT 2012.

[58]  Muddassar Farooq,et al.  BeeAIS: Artificial Immune System Security for Nature Inspired, MANET Routing Protocol, BeeAdHoc , 2007, ICARIS.

[59]  Timo D. Hämäläinen,et al.  Artificial Immune System Based Intrusion Detection: Innate Immunity using an Unsupervised Learning Approach , 2014 .

[60]  Melody Moh,et al.  Machine Learning Techniques for Security of Internet of Things (IoT) and Fog Computing Systems , 2018, 2018 International Conference on High Performance Computing & Simulation (HPCS).

[61]  Georgios Kambourakis,et al.  DDoS in the IoT: Mirai and Other Botnets , 2017, Computer.

[62]  Mark Weiser The computer for the 21st century , 1991 .

[63]  Tore Dybå,et al.  Evidence-Based Software Engineering for Practitioners , 2005, IEEE Softw..

[64]  Jaime Lloret,et al.  Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things , 2017, IEEE Access.

[65]  Danai Chasaki,et al.  Security challenges in the internet of things , 2015, Int. J. Space Based Situated Comput..

[66]  Michele Nogueira Lima,et al.  Detection of sinkhole attacks for supporting secure routing on 6LoWPAN for Internet of Things , 2015, 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM).

[67]  Marin Emilov Pamukov,et al.  Negative Selection and Neural Network Based Algorithm for Intrusion Detection in IoT , 2018, 2018 41st International Conference on Telecommunications and Signal Processing (TSP).

[68]  Rodrigo Roman,et al.  Immune System for the Internet of Things Using Edge Technologies , 2019, IEEE Internet of Things Journal.

[69]  Claudia Eckert,et al.  On the appropriateness of negative selection defined over Hamming shape-space as a network intrusion detection system , 2005, 2005 IEEE Congress on Evolutionary Computation.

[70]  Ying Tan,et al.  Recentness biased learning for time series forecasting , 2013, Inf. Sci..

[71]  Mukta Bhatele,et al.  Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE 2012) , 2013 .

[72]  Alan Fern,et al.  Reinforcement Learning for Vulnerability Assessment in Peer-to-Peer Networks , 2008, AAAI.

[73]  Michael Devetsikiotis,et al.  Blockchains and Smart Contracts for the Internet of Things , 2016, IEEE Access.

[74]  Joonsang Baek,et al.  Lightweight Encryption for Smart Home , 2016, 2016 11th International Conference on Availability, Reliability and Security (ARES).

[75]  Julie Greensmith,et al.  Immune system approaches to intrusion detection – a review , 2004, Natural Computing.

[76]  Jonathan Timmis,et al.  Artificial immune systems—today and tomorrow , 2007, Natural Computing.

[77]  Ruben E. Perez,et al.  Coupled Optimization of Aircraft Families and Fleet Allocation for Multiple Markets , 2016 .

[78]  Reshma Banu,et al.  A review on biologically inspired approaches to security for Internet of Things (IoT) , 2016, 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT).

[79]  Chen Jun,et al.  Design of Complex Event-Processing IDS in Internet of Things , 2014, 2014 Sixth International Conference on Measuring Technology and Mechatronics Automation.

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

[81]  Muddassar Farooq,et al.  A sense of danger: dendritic cells inspired artificial immune system for manet security , 2008, GECCO '08.

[82]  Jinquan Zeng,et al.  Research on immunity-based intrusion detection technology for the Internet of Things , 2011, 2011 Seventh International Conference on Natural Computation.

[83]  Fabio A. González,et al.  A comparative analysis of artificial immune network models , 2005, GECCO '05.

[84]  A. C. Zambroni de Souza,et al.  Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration , 2015, IEEE Transactions on Power Systems.

[85]  Tony Jan,et al.  Ada-Boosted Locally Enhanced Probabilistic Neural Network for IoT Intrusion Detection , 2018, CISIS.

[86]  Jong-Hyouk Lee,et al.  Blockchain-based secure firmware update for embedded devices in an Internet of Things environment , 2016, The Journal of Supercomputing.

[87]  Marin Emilov Pamukov,et al.  Application of artificial immune systems for the creation of IoT intrusion detection systems , 2017, 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS).

[88]  Pascal Bouvry,et al.  Anomaly detection in TCP/IP networks using immune systems paradigm , 2007, Comput. Commun..

[89]  Mohammad Al-Rubaie,et al.  Privacy-Preserving Machine Learning: Threats and Solutions , 2018, IEEE Security & Privacy.

[90]  Alex Alves Freitas,et al.  An Artificial Immune System for Fuzzy-Rule Induction in Data Mining , 2004, PPSN.

[91]  Caiming Liu,et al.  A Novel Approach to IoT Security Based on Immunology , 2013, 2013 Ninth International Conference on Computational Intelligence and Security.

[92]  Amarsinh Vidhate,et al.  Security attacks in IoT: A survey , 2017, 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC).

[93]  Uwe Aickelin,et al.  Danger Theory: The Link between AIS and IDS? , 2003, ICARIS.

[94]  Katia P. Sycara,et al.  Distributed Intelligent Agents , 1996, IEEE Expert.

[95]  Albert C. Esterline,et al.  Behavioral Modeling Intrusion Detection System (BMIDS) Using Internet of Things (IoT) Behavior-Based Anomaly Detection via Immunity-Inspired Algorithms , 2016, 2016 25th International Conference on Computer Communication and Networks (ICCCN).

[96]  Pietro Tedeschi,et al.  Edge and Fog Computing in Critical Infrastructures: Analysis, Security Threats, and Research Challenges , 2019, 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW).

[97]  Peter J. Bentley,et al.  An evaluation of negative selection in an artificial immune system for network intrusion detection , 2001 .

[98]  Kim-Kwang Raymond Choo,et al.  Challenges of Connecting Edge and Cloud Computing: A Security and Forensic Perspective , 2017, IEEE Cloud Computing.

[99]  Yongsheng Ding,et al.  An Intelligent Self-Organization Scheme for the Internet of Things , 2013, IEEE Computational Intelligence Magazine.

[100]  Hugues Bersini,et al.  Hints for Adaptive Problem Solving Gleaned from Immune Networks , 1990, PPSN.

[101]  Wei Zhang,et al.  A Survey of artificial immune applications , 2010, Artificial Intelligence Review.

[102]  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).

[103]  Vernon Scannell,et al.  A sense of danger , 1962 .

[104]  Kashif Saleem,et al.  An Intelligent Information Security Mechanism for the Network Layer of WSN: BIOSARP , 2011, CISIS.

[105]  Run Chen,et al.  A Security Situation Sense Model Based on Artificial Immune System in the Internet of Things , 2011 .

[106]  R. Dearden Controversial Issues and the Curriculum. , 1981 .

[107]  Edward David Moreno,et al.  An Architecture for Self-healing in Internet of Things , 2015 .

[108]  Ala I. Al-Fuqaha,et al.  Artificial Immune System Inspired Algorithm for Flow-Based Internet Traffic Classification , 2014, 2014 IEEE 6th International Conference on Cloud Computing Technology and Science.

[109]  Caiming Liu,et al.  Artificial Immunity-based Security Response Model for the Internet of Things , 2013, J. Comput..

[110]  Fabio Roli,et al.  Poisoning Adaptive Biometric Systems , 2012, SSPR/SPR.

[111]  Mário M. Freire,et al.  Applications of artificial immune systems to computer security: A survey , 2017, J. Inf. Secur. Appl..

[112]  Peter Ross,et al.  Producing robust schedules via an artificial immune system , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[113]  Nir Kshetri,et al.  Can Blockchain Strengthen the Internet of Things? , 2017, IT Professional.

[114]  Michele Banko,et al.  Scaling to Very Very Large Corpora for Natural Language Disambiguation , 2001, ACL.

[115]  Jeffrey O. Kephart,et al.  Biologically Inspired Defenses Against Computer Viruses , 1995, IJCAI.

[116]  Ying Tan,et al.  Artificial Immune System: Applications in Computer Security , 2016 .

[117]  Shahaboddin Shamshirband,et al.  Co-FAIS: Cooperative fuzzy artificial immune system for detecting intrusion in wireless sensor networks , 2014, J. Netw. Comput. Appl..

[118]  Anurag Agarwal,et al.  The Internet of Things—A survey of topics and trends , 2014, Information Systems Frontiers.

[119]  Safaai Deris,et al.  An artificial immune system for solving production scheduling problems: a review , 2013, Artificial Intelligence Review.

[120]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[121]  Aditya Trivedi,et al.  Anti-jamming in cognitive radio networks using reinforcement learning algorithms , 2012, 2012 Ninth International Conference on Wireless and Optical Communications Networks (WOCN).

[122]  Jonathan Timmis,et al.  Theoretical advances in artificial immune systems , 2008, Theor. Comput. Sci..

[123]  Alper Döyen,et al.  A new approach to solve hybrid flow shop scheduling problems by artificial immune system , 2004, Future Gener. Comput. Syst..

[124]  Isabelle Guyon,et al.  An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..

[125]  Julie Greensmith,et al.  Introducing Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomoly Detection , 2005, ICARIS.

[126]  Pearl Brereton,et al.  Performing systematic literature reviews in software engineering , 2006, ICSE.

[127]  Yoshiteru Ishida Fully distributed diagnosis by PDP learning algorithm: towards immune network PDP model , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[128]  Wei Cai,et al.  A Survey on Security Threats and Defensive Techniques of Machine Learning: A Data Driven View , 2018, IEEE Access.

[129]  Luigi Alfredo Grieco,et al.  Security, privacy and trust in Internet of Things: The road ahead , 2015, Comput. Networks.

[130]  Mehmet A. Orgun,et al.  A bio-inspired secure IPv6 communication protocol for Internet of Things , 2017, 2017 Eleventh International Conference on Sensing Technology (ICST).

[131]  Robert C. Atkinson,et al.  Threat analysis of IoT networks using artificial neural network intrusion detection system , 2016, 2016 International Symposium on Networks, Computers and Communications (ISNCC).

[132]  Azad M. Madni,et al.  Towards a Conceptual Framework for Resilience Engineering , 2009, IEEE Systems Journal.

[133]  Jinquan Zeng,et al.  Research on Dynamical Security Risk Assessment for the Internet of Things inspired by immunology , 2012, 2012 8th International Conference on Natural Computation.

[134]  Leandro Nunes de Castro,et al.  The Clonal Selection Algorithm with Engineering Applications 1 , 2000 .

[135]  João Paulo Papa,et al.  Internet of Things: A survey on machine learning-based intrusion detection approaches , 2019, Comput. Networks.

[136]  P. Matzinger Tolerance, danger, and the extended family. , 1994, Annual review of immunology.

[137]  Munam Ali Shah,et al.  IoT based ransomware growth rate evaluation and detection using command and control blacklisting , 2017, 2017 23rd International Conference on Automation and Computing (ICAC).

[138]  R. W. Peterson,et al.  OPTICAL INTERFEROMETRY OF SURFACES , 1991 .

[139]  Uwe Aickelin,et al.  The Danger Theory and Its Application to Artificial Immune Systems , 2008, ArXiv.

[140]  Changguang Wang,et al.  The Research of Security Technology in the Internet of Things , 2011, CSISE.

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

[142]  Khaled Salah,et al.  IoT security: Review, blockchain solutions, and open challenges , 2017, Future Gener. Comput. Syst..

[143]  Pearl Brereton,et al.  Lessons from applying the systematic literature review process within the software engineering domain , 2007, J. Syst. Softw..

[144]  Pierre Parrend,et al.  The AWA Artificial emergent aWareness Architecture model for Artificial Immune Ecosystems , 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).