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Integrated Social and Quality of Service Trust Management of Mobile Groups in Ad Hoc Networks

Integrated Social and Quality of Service Trust Management of Mobile Groups in Ad Hoc Networks . Ing -Ray Chen, Jia Guo , Fenye Bao , Jin- Hee Cho Communications Surveys & Tutorials , IEEE  13.4 (2011): 562-583. Speaker: Liang Zhao. Outline. 1.Background 2.Trust Management Protocol

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Integrated Social and Quality of Service Trust Management of Mobile Groups in Ad Hoc Networks

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  1. Integrated Social and Quality of Service Trust Management of Mobile Groups in Ad Hoc Networks Ing-Ray Chen, JiaGuo, FenyeBao, Jin-Hee Cho Communications Surveys & Tutorials, IEEE 13.4 (2011): 562-583 Speaker: Liang Zhao

  2. Outline • 1.Background • 2.Trust Management Protocol • 3.Model-based Evaluation Technique. • 4.Evaluation Results • 5.Conclusion and Future Works

  3. Background Trust Management: 1. Abstract system that processes symbolic representations of social trust 2. Aid automated decision-making process. • Mobile Ad Hoc Network (MANETs): A mobile ad hoc network (MANET), sometimes called a mobile mesh network, is a self-configuring network of mobile devices connected by wireless links. 

  4. Problems in MANET trust Management • 1. Traditional QoS Trust Metrics did not consider Social Trust as metric. • 2. Existing trust Metrics lack good aggregation parameter settings. • 3. Effectiveness of Trust Management Protocol is hard to be evaluated due to difficulty of getting labels based on ground truth.

  5. Contributions • 1. Consider social metrics: i.e. intimacy (social ties) and honesty (healthiness). • 2. Identify best trust aggregation parameter settings for each trust metric. • SQTrust • 3. For validating proposed trust management protocol, a novel model-based evaluation technique is leveraged to generate ground truth. • Model-based Evaluation

  6. SQTrust: A New Trust Management Protocol

  7. SQTrust: Preliminary Trust Metrics (trust components) taken into account: 1. Social Ties (Intimacy) 2. Honesty (Healthiness) measure the social trust level of a node as these social properties are considered critical for trustworthy mission execution • 3. Competence (Energy) • 4. Protocol compliance (Cooperativeness) Most important metrics to measure the QoS trust level of a node

  8. SQTrust: A New Trust Management Protocol • What is it for? For inferring the trust belief of each node in the network Subjective trust • How to infer it? By collecting all the observations from other nodes Trust Observations of node j by node i

  9. SQTrust: A New Trust Management Protocol • How to get ? Consider the following trust metrics (namely trust components): 1. Intimacy 2. Healthiness 3. Energy 4. Cooperativeness Social Metrics Qos Metrics Each trust component Weight of each trust component How to determine them?

  10. SQTrust: A New Trust Management Protocol • How to infer each trust component ? Indirect evidences given to node i by a subset of 1-hop neighbors selected. Consider both direct trust and indirect trust. Directly collected by Node i toward node j. Trade-off: How to determine them?

  11. SQTrust: Direct Trust • How to infer the Direct Trust of a node? Well, it depends. - If Node i is 1-hop neighbor of node j exponential trust decay over time. -Otherwise,

  12. SQTrust: indirect trust Inferring Indirect Trust is a little more complex. 1. Selection of Subset of 1-hop neighbors. <threshold <threshold Low trust in healthiness compromised <threshold Threshold-based filtering: only consider trustworthy recommenders Relevance-based trust: only consider trustworthy nodes under current trust component

  13. SQTrust: Indirect Trust 2.Calculation of indirect trust -If there is at least one qualified neighbor: Trust decay over space -Otherwise, Trust decay over time Node i’s trust in node m Node m’s trust in node j

  14. Model-based Evaluation

  15. Model-based Evaluation Purpose: To get the objective trust as an exact global knowledge to evaluate subjective trust : • Schema: • 1. Leverage SPN to build a semi-Markov chain to generate the nodes’ status. • 2. Reward Assignment for each status. • 3. Objective trust calculation. v.s.

  16. a semi-Markov chain for node status • Node Status is of 5 status representations: • 1. Location.(int) • 2. Member.(boolean) • 3. Energy.(boolean) • 4. Healthiness .(boolean) • 5. Cooperativeness.(boolean) To tell the positionproximity of nodes trust components

  17. Location What is it for? Is fired when node moves to another region. 1. Enable the underlying semi-Markov model to give the probability that each node is in a certain region. 2. Thus to tell whether a node is 1-hop neighbor of another. # of tokens depends on the region a node moving into Wireless radio range Transition rate: Initial speed

  18. Intimacy Consider both direct trust and indirect trust. For direct trust: 1. utilize location probability of a node to infer if nodes i and j are 1-hop neighbors. 2. If they are, utilize the equation: Based on the probability node i and node j are in the same region.

  19. Energy To get the probability of current energy level of a node. Initial # of tokens: depends on the initial value initialize different value to different nodes to emphasize the heterogeneity. Transition rate: -lower when node becomes uncooperative to save energy -higher when being compromised

  20. Healthiness (CN) A token goes to CN when a node is compromised A node is compromised when T_COMPRO fires Then, either of below can happen: 1. Good-mouth a bad node with a high trust recommendation 2. Bad-mouth a good node with a low trust recommendation Transition rate: 𝜆_𝑐𝑜𝑚

  21. A token goes to UNCOOP when a node is uncooperative. Cooperativeness (UNCOOP) depends on energy, mission difficulty and neighborhood uncooperativeness degree: Less cooperative 1-hop neighbors, more cooperative Lower energy, less cooperative Harder the mission, more cooperative Group communication interval

  22. Reward Assignment for each status

  23. Objective Trust Calculation Objective trust : by aggregating all the trust components calculated as: (1) For healthiness, energy or cooperativeness: (2) For intimacy: Probability the system is at status s at time t

  24. Evaluation Results

  25. Evaluation Results Parameter Settings Total 150 nodes, initially all are not compromised in MANETs. Initially all are trustworthy Based on ns3 simulation

  26. Evaluation Results Overall trust values from subjective trust v.s. objective trust The value around 85% is the best trade-off

  27. Conclusions and Future Works 1. Purpose of this paper: A protocol which minimizes the trust bias and maximize application performance. 2. Applicability: Based on the optimal protocol settingswe get, we apply it for dynamic trust management with considering the environment changes. Future Works: Consider more sophisticated attacker behaviors, i.e. opportunistic, random and insidious attacks.

  28. Thanks

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