Machine Learning Based Trust Computational Model for IoT Services

The Internet of Things has facilitated access to a large volume of sensitive information on each participating object in an ecosystem. This imposes many threats ranging from the risks of data management to the potential discrimination enabled by data analytics over delicate information such as locations, interests, and activities. To address these issues, the concept of trust is introduced as an important role in supporting both humans and services to overcome the perception of uncertainty and risks before making any decisions. However, establishing trust in a cyber world is a challenging task due to the volume of diversified influential factors from cyber-physical-systems. Hence, it is essential to have an intelligent trust computation model that is capable of generating accurate and intuitive trust values for prospective actors. Therefore, in this paper, a quantifiable trust assessment model is proposed. Built on this model, individual trust attributes are then calculated numerically. Moreover, a novel algorithm based on machine learning principles is devised to classify the extracted trust features and combine them to produce a final trust value to be used for decision making. Finally, our model's effectiveness is verified through a simulation. The results show that our method has advantages over other aggregation methods.

[1]  Cecile Paris,et al.  STrust: A Trust Model for Social Networks , 2011, 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications.

[2]  Magdy S. El-Soudani,et al.  A Survey on Trust and Reputation Schemes in Ad Hoc Networks , 2008, 2008 Third International Conference on Availability, Reliability and Security.

[3]  Matthew D. Zeiler.  ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.

[4]  Antonio Iera,et al.  A subjective model for trustworthiness evaluation in the social Internet of Things , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[5]  Qiang Ni,et al.  A K-Anonymity Based Schema for Location Privacy Preservation , 2019, IEEE Transactions on Sustainable Computing.

[6]  Joan Feigenbaum,et al.  The KeyNote Trust-Management System Version 2 , 1999, RFC.

[7]  Xiang Li,et al.  AUTrust: A Practical Trust Measurement for Adjacent Users in Social Networks , 2012, 2012 Second International Conference on Cloud and Green Computing.

[8]  Fei-Yue Wang,et al.  The Emergence of Intelligent Enterprises: From CPS to CPSS , 2010, IEEE Intelligent Systems.

[9]  Marianne Winslett,et al.  No Registration Needed: How to Use Declarative Policies and Negotiation to Access Sensitive Resources on the Semantic Web , 2004, ESWS.

[10]  Joan Feigenbaum,et al.  The KeyNote Trust-Management System , 1998 .

[11]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[12]  Ivan Stojmenovic,et al.  Autoregression Models for Trust Management in Wireless Ad Hoc Networks , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[13]  Bernt Schiele,et al.  Smart-Its Friends: A Technique for Users to Easily Establish Connections between Smart Artefacts , 2001, UbiComp.

[14]  Trevor Jim,et al.  SD3: a trust management system with certified evaluation , 2001, Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001.

[15]  Antonio Iera,et al.  The Social Internet of Things (SIoT) - When social networks meet the Internet of Things: Concept, architecture and network characterization , 2012, Comput. Networks.

[16]  Chih-Jen Lin,et al.  A Practical Guide to Support Vector Classication , 2008 .

[17]  George Varghese,et al.  MobiClique: middleware for mobile social networking , 2009, WOSN '09.

[18]  Justin Zhijun Zhan,et al.  A Novel Trust Computing System for Social Networks , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[19]  Sibel Adali,et al.  Measuring behavioral trust in social networks , 2010, 2010 IEEE International Conference on Intelligence and Security Informatics.

[20]  Subhash Challa,et al.  Survey of trust models in different network domains , 2010, ArXiv.

[21]  Yuhong Yang,et al.  Information Theory, Inference, and Learning Algorithms , 2005 .

[22]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[23]  Fali Huang.  Building Social Trust: A Human-Capital Approach , 2007 .

[24]  Guido Möllering,et al.  The Nature of Trust: From Georg Simmel to a Theory of Expectation, Interpretation and Suspension , 2001 .

[25]  Feng Jiang,et al.  Deep Learning Based Multi-Channel Intelligent Attack Detection for Data Security , 2020, IEEE Transactions on Sustainable Computing.

[26]  Huajun Chen,et al.  A Social Network-Based Trust Model for the Semantic Web , 2006, ATC.

[27]  Gyu Myoung Lee,et al.  RpR: A Trust Computation Model for Social Internet of Things , 2016, 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld).

[28]  Gyu Myoung Lee,et al.  A Survey on Trust Computation in the Internet of Things , 2016 .

[29]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[30]  Hyun-Woo Lee,et al.  A computational model to evaluate honesty in social internet of things , 2017, SAC.

[31]  Feng Wu,et al.  SocialTrust: Enabling long-term social cooperation in peer-to-peer services , 2013, Peer-to-Peer Networking and Applications.

[32]  Marianne Winslett,et al.  PeerTrust: Automated Trust Negotiation for Peers on the Semantic Web , 2004, Secure Data Management.

[33]  Stephen Marsh,et al.  Formalising Trust as a Computational Concept , 1994 .

[34]  Fenye Bao,et al.  Dynamic trust management for internet of things applications , 2012, Self-IoT '12.

[35]  Antonio Iera,et al.  From "smart objects" to "social objects": The next evolutionary step of the internet of things , 2014, IEEE Communications Magazine.

[36]  Ling Liu,et al.  A reputation-based trust model for peer-to-peer e-commerce communities , 2003, EEE International Conference on E-Commerce, 2003. CEC 2003..

[37]  Christophe Diot,et al.  CRAWDAD dataset thlab/sigcomm2009 (v.2012-07-15) , 2012 .

[38]  Jorge Nocedal,et al.  On the limited memory BFGS method for large scale optimization , 1989, Math. Program..

[39]  Horace Ho-Shing Ip,et al.  Enhancing collaborative intrusion detection networks against insider attacks using supervised intrusion sensitivity-based trust management model , 2017, J. Netw. Comput. Appl..

[40]  Luigi Atzori,et al.  Trustworthiness Management in the Social Internet of Things , 2014, IEEE Transactions on Knowledge and Data Engineering.

[41]  Ananthram Swami,et al.  LogitTrust : A Logit Regression-based Trust Model for Mobile Ad Hoc Networks , 2014 .

[42]  Cécile Paris,et al.  A survey of trust in social networks , 2013, CSUR.

[43]  Zeinab Movahedi,et al.  A Trust-Based Offloading for Mobile M2M Communications , 2016, 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld).

[44]  Jian Shen,et al.  Algebraic Signatures-Based Data Integrity Auditing for Efficient Data Dynamics in Cloud Computing , 2020, IEEE Transactions on Sustainable Computing.

[45]  Alan Marshall,et al.  Analytical metric weight generation for multi-domain trust in autonomous underwater MANETs , 2016, 2016 IEEE Third Underwater Communications and Networking Conference (UComms).

[46]  Xavier Amatriain,et al.  Data Mining Methods for Recommender Systems , 2011, Recommender Systems Handbook.

[47]  G. Suryanarayana,et al.  A Survey of Trust Management and Resource Discovery Technologies in Peer-to-Peer Applications , 2004 .