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Agenda

Motivation & Goals. Background. Bio-inspired trust models. Trust models taxonomy. Security threats. Trust models simulator. Conclusions & future work. Agenda. Motivation. Internet and WWW have changed our lives. Despite their several advantages, there are also many security risks.

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Agenda

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  1. Motivation & Goals Background Bio-inspired trust models Trust models taxonomy Security threats Trust models simulator Conclusions & future work Agenda

  2. Motivation • Internet and WWW have changed our lives • Despite their several advantages, there are also many security risks • Traditional security solutions are very effective but not always applicable • Trust and reputation management has been proposed as an accurate alternative • Oneself can make his/her own opinion about how trustworthy or reputable another member of the community is • Increases the probability of a successful transaction while reducing the opportunities of being defrauded • European Union supported this research field in several projects

  3. Goals • Analyse the current state of the art • Identify possible deficiencies • Design and suggest innovative and original alternatives • Propose and develop our own trust models • Make an analysis of the intrinsic nature of these models • Study those threats specifically applicable in these systems • Develop a tool to implement trust and reputation models • Compare our alternatives with other representative models • Survey some real and final scenarios

  4. Background • Lack of mature bio-inspired approaches • Lack of taxonomy analysis • Lack of security threats study • Lack of generic testing tools

  5. Trust and Reputation Management in Distributed and Heterogeneous Systems Bio-inspired TRM Trust Models Taxonomy Security Threats Simulator Application Scenarios

  6. Bio-inspired Trust and Reputation Models • TACS • META-TACS • BTRM-WSN Bio-inspired TRM Trust Models Taxonomy Security Threats Simulator Application Scenarios

  7. Ant Colony System • Optimisation algorithm • Problems represented as graphs (like TSP) • Quite accurate and efficient  Stop condition  Ants transition  Pheromone updating  Path quality evaluation  Reward/punish

  8. TACS, Trust Model for P2P Networks • Aimed to work in P2P networks • A client applies for a certain service • There are benevolent and malicious service providers • Ants find the most trustworthy server offering the requested service • Pheromone traces represent the credibility of finding such server

  9. TACS, Trust Model for P2P Networks • TACS adaptation • Pheromone updating • Path quality evaluation • Ants transition and stop condition • Reward • Punishment

  10. Static networks Dynamic networks Oscillating networks TACS, Trust Model for P2P Networks • Experiments carried out • Over static networks • Over dynamic networks • Over oscillating networks • Capability of managing multi-service networks • Sourceforge project

  11. META-TACS: a Trust Model Demonstration of Robustness through a Genetic Algorithm • TACS had several parameters • Was it too complex? • Was it too dependent?

  12. META-TACS: a Trust Model Demonstration of Robustness through a Genetic Algorithm • Search for the optimal parameters configuration • Genetic algorithm CHC

  13. META-TACS: a Trust Model Demonstration of Robustness through a Genetic Algorithm • Not one unique optimal parameters configuration • Each parameter had a wide range of values • Demonstration of robustness against parameters initialisation

  14. BTRM-WSN, Bio-inspired Trust and Reputation Model for Wireless Sensor Networks • Application to WSNs • Enhancements with regard to TACS • Several clients management • Enhanced pheromone updating • Enhanced punish & reward • Two proposed models • Multi-service • Not multi-service

  15. BTRM-WSN, Bio-inspired Trust and Reputation Model for Wireless Sensor Networks • Experiments Static Networks Dynamic Networks Oscillating Networks Collusion Networks Accuracy Path length

  16. Trust Models Taxonomy Bio-inspired TRM Trust Models Taxonomy Security Threats Simulator Application Scenarios

  17. Trust Models Taxonomy • Generic steps • Generic interfaces • Generic data structures

  18. Trust Models Taxonomy • 10 design advices • Anonymous recommendations • Higher weight to more recent transactions • Recommendations subjectivity • Redemption of past malicious entities • Opportunity to participate for benevolent newcomers • Avoid abuse of a high achieved reputation • Benevolent nodes should have more opportunities than newcomers • Different trust/reputation scores for different services • Take into account bandwidth, energy consumption, scalability... • Consider the importance or associated risk of a transaction

  19. Trust Models Security Threats Bio-inspired TRM Trust Models Taxonomy Security Threats Simulator Application Scenarios

  20. Trust Models Security Threats • Commonly neglected issue • Lack of a comprehensive analysis • 9 studied threats • Malicious spies • Spies may achieve a high reputation • Manage recommenders reliability • More difficult to distinguish malicious peers and malicious spies • Sybil attack • Underestimated but great risk • One single entity generates a disproportionate number of identities • Associate a cost to the generation of new identities • Malicious collectives with camouflage • Resilience mostly depends on malicious peers behavioral patterns • Not always considered as a threat • Manage recommenders reliability • Keep a transactions history to detect and punish variable behavior

  21. Trust Models Security Threats • Security threats taxonomy • Attack intent • Targets • Required knowledge • Cost • Algorithm dependence • Detectability • Tackling summary • EigenTrust • PeerTrust • BTRM-WSN • PowerTrust • ATSN • DWTrust

  22. Simulator Bio-inspired TRM Trust Models Taxonomy Security Threats Simulator Application Scenarios

  23. Simulator • Generic tool • Easy to implement and add new models • V0.4 includes 5 models • BTRM-WSN • EigenTrust • PeerTrust • PowerTrust • LFTM • Sourceforge project • + 2300 downloads • World wide interest • Models comparison

  24. Conclusions • Distributed and heterogeneous systems are nowadays developing very quickly, leading to new unresolved security risks • Trust and reputation management has been proposed in this PhD Thesis as an effective solution in certain environments • Our original bio-inspired trust and reputation models have been proved to have a high performance, while solving some of the previous issues • Taxonomy and design advices & security threats analysis might be quite helpful for future researchers • Extensible and easy to use simulator, enabling models comparison • Appealing field with much more to do

  25. Future Work • Ongoing work • Trust and reputation models comparison • Real scenarios • Identity Management Systems • Wireless Sensors and Actuators Networks • Fuzzy logic, fuzzy sets and linguistic labels • Future work • Improve TRMSim-WSN • New Trust & Reputation models • New security threats • Vehicular-to-Vehicular (V2V) • Internet of Things (IoT)

  26. Publications derived from the PhD Thesis

  27. Publications derived from the PhD Thesis • Book chapters • Félix Gómez Mármol, Gregorio Martínez Pérez, “State of the art in trust and reputation models in P2P networks”, Handbook of Peer-to-Peer Networking, Eds: X. Shen, H. Yu, J. Buford, M. Akon, Publisher: Springer, ISBN: 978-0-387-09750-3, pp 761-784, 2010 http://dx.doi.org/10.1007/978-0-387-09751-0 26

  28. Publications derived from the PhD Thesis • International conferences • Félix Gómez Mármol, Gregorio Martínez Pérez, "Providing Trust in Wireless Sensor Networks using a Bio-inspired Technique", Networking and Electronic Commerce Research Conference (NAEC 08), pp. 415-430, ISBN: 978-0-9820958-0-5, Lake Garda, Italy, 25-28 September 2008 • Journals with impact factor (included in the JCR) • Félix Gómez Mármol, Gregorio Martínez Pérez, Antonio F. Gómez Skarmeta, “TACS, a Trust Model for P2P Networks”, Wireless Personal Communications, vol. 51, no. 1, pp 153-164, 2009 http://dx.doi.org/10.1007/s11277-008-9596-9 • Félix Gómez Mármol, Gregorio Martínez Pérez, Javier Gómez Marín-Blázquez, “META-TACS: a Trust Model Demonstration of Robustness through a Genetic Algorithm”, Intelligent Automation and Soft Computing (Autosoft) Journal, 2010 (in press) • Félix Gómez Mármol, Gregorio Martínez Pérez, “Providing Trust in Wireless Sensor Networks using a Bio-Inspired Technique”, Telecommunication Systems Journal, vol. 46, no. 2, 2010 (in press) http://dx.doi.org/10.1007/s11235-010-9281-7

  29. Publications derived from the PhD Thesis • Journals with impact factor (included in the JCR) • Félix Gómez Mármol, Gregorio Martínez Pérez, “Towards Pre-Standardization of Trust and Reputation Models for Distributed and Heterogeneous Systems”, Computer Standards & Interfaces, Special Issue on Information and Communications Security, Privacy and Trust: Standards and Regulations, vol. 32, no. 4, pp. 185-196, 2010 http://dx.doi.org/10.1016/j.csi.2010.01.003

  30. Publications derived from the PhD Thesis • Journals with impact factor (included in the JCR) • Félix Gómez Mármol, Gregorio Martínez Pérez, “Security Threats Scenarios in Trust and Reputation Models for Distributed Systems”, Elsevier Computers & Security, vol. 28, no. 7, pp. 545-556, 2009 http://dx.doi.org/10.1016/j.cose.2009.05.005

  31. Publications derived from the PhD Thesis • International conferences • Félix Gómez Mármol, Gregorio Martínez Pérez, “TRMSim-WSN, Trust and Reputation Models Simulator for Wireless Sensor Networks”, IEEE International Conference on Communications (IEEE ICC 2009), Communication and Information Systems Security Symposium, Dresden, Germany, 14-18 June 2009 http://dx.doi.org/10.1109/ICC.2009.5199545

  32. Publications derived from the PhD Thesis • International conferences • Félix Gómez Mármol, Javier Gómez Marín-Blázquez, Gregorio Martínez Pérez, "Linguistic Fuzzy Logic Enhancement of a Trust Mechanism for Distributed Networks", Third IEEE International Symposium on Trust, Security and Privacy for Emerging Applications (TSP-10), Bradford, UK, June 29-July 1, 2010 • Journals with impact factor (included in the JCR), under review • Félix Gómez Mármol, Gregorio Martínez Pérez, “Trust and Reputation Models Comparison”, submitted to Emerald Internet Research on the 16th of August, 2009 • Félix Gómez Mármol, Joao Girao , Gregorio Martínez Pérez, “TRIMS, a Privacy-aware Trust and Reputation Model for Identity Management Systems”, submitted to Elsevier Computer Networks on the 15th of December, 2009(currently in a 2nd revision) • Félix Gómez Mármol, Joao Girao , Gregorio Martínez Pérez, “Identity Management: In privacy we trust”, submitted to IEEE Internet Computing Magazine on the 15th of February, 2010 • Félix Gómez Mármol, Christoph Sorge, Osman Ugus, Gregorio Martínez Pérez, “WSANRep, WSAN Reputation-Based Selection in Open Environments”, submitted to IEEE Wireless Communications Magazine on the 21st of January, 2010

  33. Publications derived from the PhD Thesis • Summary • Book chapters: 1 • Journals with impact factor: 9 (5 published and 4 under current review) • International conferences: 3 • Open-source software projects protected with IPR: 2 • Patent applications: 1

  34. Static networks Dynamic networks Oscillating networks TACS, Trust Model for P2P Networks • Experiments carried out • Over static networks • Over dynamic networks • Over oscillating networks • Capability of managing multi-service networks

  35. TACS, Trust Model for P2P Networks 1. Client C executes TACS in order to find the most trustworthy server S offering the service s 2. TACS launches the ACS algorithm and ants modify the pheromone traces of the network 3. TACS finishes, having selected the “optimum” path to server S' 4. TACS informs the client C that the most trustworthy server found is S' 5. Client C requests service s to the server S' 6. Server S' provides service s' to the client C 7. Client C evaluates his satisfaction with the received service s' 8. If client C is not satisfied with the received service s', he punishes the server S' evaporating the pheromone of the edges that lead from C to S'

  36. Trust Models Taxonomy • Anonymous recommendations • Hiding real-world identities behind pseudonyms • Cryptographically generated unique identifiers • Secure hardware modules • Higher weight to more recent transactions • Redemption of past malicious entities • Recommendations subjectivity

  37. Trust Models Taxonomy • Opportunity to participate for benevolent newcomers • Avoid abuse of a high achieved reputation • Benevolent nodes should have more opportunities than newcomers

  38. Trust Models Taxonomy • Different trust/reputation scores for different services • Take into account bandwidth, energy consumption, scalability... • Wireless Sensor Networks • Consider the importance or associated risk of a transaction • Transaction importance  Punish/Reward

  39. Trust Models Security Threats • Individual malicious peers • Simplest threat • Decrease trust in malicious peers • Malicious collectives • Collusion is often an important risk • Manage recommenders reliability • Malicious collectives with camouflage • Resilience mostly depends on malicious peers behavioral patterns • Not always considered as a threat • Manage recommenders reliability • Keep a transactions history to detect and punish variable behavior

  40. Trust Models Security Threats • Malicious spies • Spies may achieve a high reputation • Manage recommenders reliability • More difficult to distinguish malicious peers and malicious spies • Sybil attack • Underestimated but great risk • One single entity generates a disproportionate number of identities • Associate a cost to the generation of new identities • Man in the middle attack • Traditionally not associated with trust and reputation management • Authenticate each peer through cryptographic mechanisms • Solution not always feasible

  41. Trust Models Security Threats • Driving down the reputation of a reliable peer • A benevolent peer may be isolated forever • Manage recommenders reliability • Partially malicious collectives • One peer might be benevolent providing a certain service, but malicious provisioning a different service • Different trust scores for different services • Malicious pre-trusted peers • Only applicable in some trust models • Not always easy to find peers to be pre-trusted • Dynamically select the set of pre-trusted peers

  42. Trust models comparison Static networks Dynamic networks Oscillating networks Collusion networks

  43. TRIMS, a Privacy-aware Trust and Reputation Model for Identity Management Systems • Several domains • Users identity information exchange • Application of a reputation mechanism • Preservation of recommenders privacy • WSC provides the requested service • WSP provides user identity information • IdPs act as recommendation aggregators • Developed during 1st NEC internship • Led to an international patent

  44. WSANRep, WSAN Reputation-Based Selection in Open Environments • Mobile users looking for services • Several WSAN offering such services • Application of a reputation mechanism • Users form groups to preserve their privacy • FP acts as recommendations aggregator • One RP per group storing recommendations • Developed during 2nd NEC internship

  45. Linguistic Fuzzy Logic Enhancement of a Trust Mechanism for Distributed Networks • Fuzzy sets, fuzzy logic and linguistic labels • Enhanced interpretability • Improved accuracy

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