An Immunity-Based IOT Environment Security Situation Awareness Model

To effectively perceive network security situation under IOT environment, an Immunity-based IOT Environment Security Situation Awareness (IIESSA) model is proposed. In IIESSA, some formal definitions for self, non-self, antigen and detector are given. According to the relationship between the antibody-concentration of memory detectors and the intensity of network attack activities, the security situation evaluation method under IOT environment based on artificial immune system is presented. And then according to the situation time series obtained by the mentioned evaluation method, the security situation prediction method based on grey prediction theory is presented for forecasting the intensity and security situation of network attack activities that the IOT environment will be suffered in next step. The experimental results show that IIESSA provides a novel and effective model for perceiving security situation of IOT environment.

[1]  Yu Zhang,et al.  An immunity-based time series prediction approach and its application for network security situation , 2015, Intell. Serv. Robotics.

[2]  Wei Bao Method of BX data producing for grey forecast and its application for enviornmental forecast , 2000 .

[3]  Mohammad Shojafar,et al.  FR trust: a fuzzy reputation-based model for trust management in semantic P2P grids , 2014, Int. J. Grid Util. Comput..

[4]  Thiemo Voigt,et al.  SVELTE: Real-time intrusion detection in the Internet of Things , 2013, Ad Hoc Networks.

[5]  Thiemo Voigt,et al.  Routing Attacks and Countermeasures in the RPL-Based Internet of Things , 2013, Int. J. Distributed Sens. Networks.

[6]  Mohammad Shojafar,et al.  A New Meta-heuristic Algorithm for Maximizing Lifetime of Wireless Sensor Networks , 2015, Wirel. Pers. Commun..

[7]  Athanasios V. Vasilakos,et al.  A survey on trust management for Internet of Things , 2014, J. Netw. Comput. Appl..

[8]  Tao Li,et al.  A quantitative model for network security situation awareness based on immunity and grey theory , 2009, 2009 ISECS International Colloquium on Computing, Communication, Control, and Management.

[9]  Tao Li,et al.  An immunity based network security risk estimation , 2005, Science in China Series F: Information Sciences.

[10]  Kenli Li,et al.  Lightweight detecting and resolving algorithm for firewall policy conflict , 2013, 2013 Fifth International Conference on Ubiquitous and Future Networks (ICUFN).

[11]  Ivan Martinovic,et al.  Air Dominance in Sensor Networks: Guarding Sensor Motes using Selective Interference , 2013, ArXiv.

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

[13]  Habtamu Abie Adaptive Security for the Internet of Things: Research, Standards, and Practices , 2017 .

[14]  Habtamu Abie Adaptive security and trust management for autonomic message-oriented middleware , 2009, 2009 IEEE 6th International Conference on Mobile Adhoc and Sensor Systems.

[15]  Dimitris Kiritsis,et al.  Closed-loop PLM for intelligent products in the era of the Internet of things , 2011, Comput. Aided Des..

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

[17]  Lida Xu,et al.  The internet of things: a survey , 2014, Information Systems Frontiers.

[18]  Wang Li-hong,et al.  Sensors Access Scheme Design Based on Internet of Things Gateways , 2014, 2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications.

[19]  Vijay Raghunathan,et al.  AEGIS: A Lightweight Firewall for Wireless Sensor Networks , 2010, DCOSS.

[20]  Shahaboddin Shamshirband,et al.  Diagnosing Tuberculosis With a Novel Support Vector Machine-Based Artificial Immune Recognition System , 2015, Iranian Red Crescent medical journal.

[21]  William J. Buchanan,et al.  Formal security policy implementations in network firewalls , 2012, Comput. Secur..

[22]  Renfa Li,et al.  Network Security Situation Prediction Approach Based on Clonal Selection and SCGM(1,1)c Model , 2016 .

[23]  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.

[24]  Lida Xu,et al.  Internet of Things for Enterprise Systems of Modern Manufacturing , 2014, IEEE Transactions on Industrial Informatics.

[25]  Gail-Joon Ahn,et al.  Detecting and Resolving Firewall Policy Anomalies , 2012, IEEE Transactions on Dependable and Secure Computing.

[26]  Alex R. Pinto,et al.  Integration of Wireless Sensor Networks to the Internet of Things Using a 6LoWPAN Gateway , 2013, 2013 III Brazilian Symposium on Computing Systems Engineering.

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

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

[29]  Qian Zhu,et al.  IOT Gateway: BridgingWireless Sensor Networks into Internet of Things , 2010, 2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing.

[30]  Enzo Baccarelli,et al.  P-SEP: a prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks , 2017, The Journal of Supercomputing.

[31]  Xin Zhou,et al.  Study on security architecture in the Internet of Things , 2011, Proceedings of 2012 International Conference on Measurement, Information and Control.

[32]  Sylvain Kubler,et al.  A standardized approach to deal with firewall and mobility policies in the IoT , 2015, Pervasive Mob. Comput..

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