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Security Mechanisms for Distributed Computing Systems

2011/12/15. Security Mechanisms for Distributed Computing Systems. A9ID1007, Xu Ling Kobayashi Laboratory GSIS, TOHOKU UNIVERSITY. Background. Distributed computing systems (DCSs) Definition: A system where nodes share their computing power with each other to finish certain goals

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Security Mechanisms for Distributed Computing Systems

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  1. 2011/12/15 Security Mechanisms for Distributed Computing Systems A9ID1007, Xu Ling Kobayashi Laboratory GSIS, TOHOKU UNIVERSITY

  2. Background • Distributed computing systems (DCSs) • Definition: A system where nodes share their computing power with each other to finish certain goals • Example: P2P systems (Skype), volunteer computing systems (SETI@home), Grid

  3. Task 1 Task 1 Task 2 Task 3 Task 4 Result 1 Result 2 Result 3 Result 4 Task 2 Task n Background • Example: Volunteer computing system • A system that utilizes the idling computing resources on the network to finish computing intensive tasks host worker 2 worker 3 worker 4 worker 1 The structure of a typical volunteer computing system

  4. Background • Categorization • Centralized DCSs (e.g., volunteer computing): • Few servers and many clients. • Only have server-client communication • Decentralized DCSs (e.g., P2P) : all nodes are equal and communicate with each other • Hybrid DCSs (e.g., skype) • Most nodes are equal, and communicate with each other • A few servers exist • Authorized DCSs: DCSs that contain trustful authorities (e.g., volunteer computing systems) • Unauthorized DCSs: DCSs that contain no trustful authority (e.g., P2P systems)

  5. Task 1 Task 1 Task 2 Task 3 Task 4 1+1=2 1+1=2 1+1=2 1+1=3 Task 2 Task n Background: Attack to DCSs • False result attack (FRA) (for centralized DCSs) • One host node and multiple worker nodes • Host dispatches tasks to workers. Workers compute tasks and return returns to host • Malicious workers return incorrect results to host host worker 2 worker 3 Malicious worker 4 worker 1

  6. Background: Attack to DCSs • Sybil attack (SA) (For decentralized and hybrid DCSs) • A few malicious users controls many Sybil nodes (malicious nodes) to break the system protocol • Sybil nodes can launch various attacks 1+1=3 1+1=3! 1+1=3 Honest node Sybil node 1+1=3 1+1=2 1+1=? 1+1=? 1+1=? 1+1=? malicious user 1+1=?

  7. Background: Existing solution to the false result attack 11*11=121! v is malicious host • The host dispatches multiple tasks to each worker v • These tasks contains some special tasks called quizzes • The host checks the correctness of the answers of quizzes Node v is honest only if the answers of the quizzes return by v are correct • Problem: • A Quiz should satisfy: the correctness of the answer of a quiz should be easy to check • Unpractical: How to generate quizzes that satisfy this property is an open problem. 1+1=? 1+1=3 1+2=? 1+2=3 11*11=? (quiz) 11*11=3 (quiz) v

  8. Background: Existing solution to the Sybil attack • Social network model based Sybil detecting (SSD) • Social network model: # of attack edges is small • SSD algorithms • Assumption: The network topology of the DCS obeys SNM • Functionality: For each honest node v, enable v to judge the types of other nodes • Basic idea: the # of attack edges is small  communication between nodes of different types is weakened • My idea: attack edge detecting is important in design effective SSD algorithms • Effective: high judging accuracy • Detect the attack edges and cut them  communication between nodes of different types can be stopped! Attack edges Honest cluster Sybil cluster Attack edge

  9. Objective • Motivation: • For FRA: existing solutions are unpractical (Quiz) • For SA: Attack edge detecting technique can be used to design effective SSD algorithms • Objective: Design effective security mechanisms to resist the false result attack and the Sybil attack on DCSs.

  10. workers 1 are honest; worker 4 is malicious • Approach • Design a practical false result attack resisting algorithm  Enable host to detect malicious workers • Design an effective attack edge detecting-based SSD algorithm for authorized DCSs  For each node v, enable v to know the types of other nodes • Design an attack edge detecting algorithm for unauthorized DCSs For each node v and an incident edge e of v, enable v to know whether e is an attack edge or not worker 2 worker 3 worker 4 (Malicious) worker 1 v1 is honest, v2 is Sybil e1 is not AE, e2 is AE v2 v e2 e1 v1 Honest nodes Sybil nodes

  11. Organization • Introduction • MSC: an Practical Spot Checking Mechanism for Resisting False Result Attack • SybilDetector: an Attack Edge Detecting Based Sybil Detecting Algorithm • RSC: an Attack Edge Detecting Algorithm for Sybil Resisting • Conclusion

  12. Comments from Professor Sone • Comment: Clarify the approaches( ‘detect the malicious nodes’ is too broad, there are many way to detect) • Solution: • To detail the models of FRA and SA, respectively • To specify the research approaches • To specify the functionality of each approach • Approach (old) • For false result attack: enable honest nodes to detect malicious nodes • For Sybil attack: enable honest nodes to detect Sybil nodes • Approach (new) • Design an practical and efficient false result attack resisting algorithm. • Design an effective attack edge detecting-based SSD algorithm for authorized DCSs. • Design an attack edge detecting algorithm for unauthorized DCSs.

  13. Comments from Professor Sone • Comment: Clarify the performance metric (Define the performance metric in the first chapter. Define what is ‘effective’.) • Solution: Define the performance metrics of MSC and SSD algorithms in Chapter 1

  14. Comments from Professor Sone • Comment : Clarify the innovational point: • Emphasize on the new idea rather than the algorithm • Solution: • Point out that the attack edge detecting technique is the innovation point in chapter 1. • Change chapter 4 • Old  RSSR: A Random Walk and Attack Edge Detecting Based Sybil Detecting Algorithm (emphasized RSSR (a SSD algorithm)) • New  RSC: an Attack Edge Detecting Algorithm for Sybil Resisting (emphasize RSC (an attack edge detecting algorithm))

  15. Comments from Professor Sone • Comment : The current social network model considers only two clusters. How to deal with the case of more clusters? • Solution : • Discuss this problem in Section Related Work of Chapter 3. • In the case of more clusters, for each cluster, we have to know the type of at least one node this cluster.

  16. Comments from Professor Sone • Comment : How to deal with nodes changing types? • Solution • Reputation system? (will be vulnerable to the Sybil attack)

  17. Comments from Professor Suganuma • Comment : Explain the baseline algorithms (SybilLimit) used for the performance comparison • Solution: Explain the baseline algorithm (SybilLimit, SOHL) in detail in Section Related Work of Chapter 3 of the dissertation, and in the presentation of the next defense.

  18. Comments from Professor Takizawa • Comment: Clarify the model used (Does this system have trustful authority?). • Solution: • Specify the models of FRA and SA • FRA: centralized • SA: decentralized or hybrid

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