Security mechanisms for distributed computing systems
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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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Security mechanisms for distributed computing systems

2011/12/15

Security Mechanisms for Distributed Computing Systems

A9ID1007, Xu Ling

Kobayashi Laboratory

GSIS, TOHOKU UNIVERSITY


Background

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 ([email protected]), Grid


Background1

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


Background2

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)


Background attack to dcss

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


Background attack to dcss1

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=?


Background existing solution to the false result attack

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


Background existing solution to the sybil attack

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


Objective

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.


Security mechanisms for distributed computing systems

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


Organization

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


Comments from professor sone

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.


Comments from professor sone1

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


Comments from professor sone2

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))


Comments from professor sone3

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.


Comments from professor sone4

Comments from Professor Sone

  • Comment : How to deal with nodes changing types?

  • Solution

    • Reputation system? (will be vulnerable to the Sybil attack)


Comments from professor suganuma

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.


Comments from professor takizawa

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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