1 / 14

An Architecture for Dynamic Trust Monitoring in Mobile Networks

An Architecture for Dynamic Trust Monitoring in Mobile Networks. Onolaja Olufunmilola, Rami Bahsoon, Georgios Theodoropoulos School of Computer Science The University of Birmingham, UK. Outline. Introduction Definitions Motivation Review of current research and problems

wayde
Download Presentation

An Architecture for Dynamic Trust Monitoring in Mobile Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. An Architecture for Dynamic Trust Monitoringin Mobile Networks Onolaja Olufunmilola, Rami Bahsoon, Georgios Theodoropoulos School of Computer Science The University of Birmingham, UK

  2. Outline • Introduction • Definitions • Motivation • Review of current research and problems • Collusion attack • Proposed solution • Possible real life applications • Summary Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  3. Introduction • Ad hoc and wireless sensor networks have gained popularity in recent years and have been used in critical applications. • Applications such as • Military and security monitoring, • Traffic regulation, • Human tracking and monitoring, • Battlefield surveillance etc Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  4. Introduction • The use of the networks in the applications leads to the misbehaviour among nodes. • Misbehaviour makes the differentiating between normal and malicious network operations difficult. • Problem further complicated due to nature of these networks • Mobility • Limited transmission power • Dynamic formulation Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  5. Definitions Trust • Gambetta (1988) stated that when a node is trusted, it implicitly means that the probability that it will perform an action that is beneficial or at least not detrimental in the network is high enough to consider engaging in some form of cooperation with the node. • Each node has a Trust Value. Reputation • The opinion of an entity about another; it is the trustworthiness of a node. • Synonymous to trust? Misbehaviour • Behavioural expectation ↔ Social perspective • The deviation from the expected behaviour of nodes in a network. • For example, in a network, a node is said to be misbehaving when it deviates from the regular routing and forwarding of packets. • Collusion attack. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  6. Motivation • Despite the existing security paradigms, such as • Public Key Infrastructure (PKI): inadequate • Reputation and Trust Based Systems (RTBSs): collusion attacks the assurance of security still remains a problem. • The problems that arise due to the dynamic nature of ad hoc and sensor (dynamic) networks, calls for an equally dynamic approach to identifying and isolating misbehaving nodes. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  7. Node Cooperation Enforcement: CORE, CONFIDANT - Michiardi et al (IFIP 2002), Buchegger et al (MOBIHOC 2002) Incentive Based Scheme: SORI - He et al (WCNC 2004) Trust Enhanced Model: SMRTI - Balakrishnan at al (AINA 2007) High Integrity Networks Framework: RFSN - Ganeriwal et al (ACM TSN 2008) Reputation and Trust Based Systems Recommendations provided by individual nodes in the network are used in deciding the reputation of other nodes. Watchdog is resident on each node that monitors and gathers information based on promiscuous observation. Marti et al (MOBICOM 2000) Promiscuous observation: each node overhears the transmission of neighbouring nodes to detect misbehaviour. This mechanism has a weakness of failing to detect misbehaving nodes in the case of collusion. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  8. Suppose node A forwards a packet P through B to D. Node C can decide to misbehave and B colludes with C. With the watchdog mechanism, it is possible that B does not report to A when C modifies the packet to P#. The problem of collusion is very important because its effects can considerably affect network performance and may hinder communication vital to fulfilling of the mission of ad hoc and sensor networks.Liu et al (IEEE 2004) A B C Collusion Attack P P P# D Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  9. Real life Simulation Proposal -DDDAS • DDDAS (Dynamic Data-Driven Application Systems – www.dddas.org) is a paradigm whereby applications and measurements become a symbiotic feedback control system. • The paradigm promises to provide more accurate analysis and prediction, more precise controls, and more reliable outcomes. This entails the ability to dynamically incorporateadditional datainto an executing application, and in reverse, the ability of an application todynamicallysteer themeasurementprocess. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  10. Proposal -DDDAS • Why DDDAS? • The dynamic nature of mobile and sensor networks require a dynamic approach to identifying and isolating misbehaving or malicious nodes. Which DDDAS provides. • How? • The concepts of the paradigm are applied in building a dynamic reputation system. This paper proposes the use of the DDDAS components: measurement, simulation, feedback, control. • The online data obtained is used to gain a better understanding and more accurate prediction of node behaviour: Simulation. • The simulation continually incorporates new measurements at runtime for the system to accurately determine and update the trust values. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  11. Proposed Solution High-level diagram of architecture • Online and historical behaviour • Simulation • Feedback • Prediction Solution addresses collusion attacks because nodes do not directly determine the reputation of other nodes in the network. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  12. Applications • Criminal and terrorist monitoring; • Military applications; • Femtocells deployment. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  13. Summary • Discussed a pending problem of reputation and trust based models and how the DDDAS approach can fill the gaps. • A dynamic architecture for addressing the problem of collusion among nodes. Model provides a high level of dynamism to reputation systems by updating the trust values of nodes at runtime. • Not only useful at the network level but at a higher level and will allow for making informed decisions. • Future Work • Real life application of model – combating crime and criminal monitoring; • Tests through simulation of model to ascertain its effectiveness in addressing collusion; • Ensuring identity persistence. Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

  14. Thank you. Questions??? ‘Funmi Onolaja o.o.onolaja@cs.bham.ac.uk Olufunmilola Onolaja, Rami Bahsoon, Georgios Theodoropoulos MONET, Algarve, Portugal Nov-09

More Related