IEEE CRS 2014 - Secure Distributed Data Structures for Peer-to-Peer-based Social Networks
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The document describes research into secure distributed data structures for peer-to-peer social networks. It proposes using distributed lists to store social media content like guestbook entries or photos, partitioned into buckets stored on different nodes. Remote operations are introduced to allow efficient list manipulation with less network traffic than retrieving full buckets. Access control is implemented cryptographically by encrypting or signing list elements and buckets. Evaluation shows the approach reduces network traffic compared to naïve distributed list implementations.
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IEEE CRS 2014 - Secure Distributed Data Structures for Peer-to-Peer-based Social Networks
- 1. HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks P2PCS as part of CTS 2014 May 21, 2014 Jens Janiuk Alexander Mäcker Kalman Graffi Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 1
- 2. 1 Introduction 2 Distributed List Concept 3 Access Control in Distributed List Read and Write Access Key Distribution 4 Evaluation HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 2
- 3. Introduction Online Social Networks (OSNs) Facebook, Google+, Twitter, . . .heavily used nowadays HEINZ NIXDORF INSTITUTE (semi-) public user profiles communication collaboration: sharing and searching user generated content University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 3
- 4. Introduction Online Social Networks (OSNs) Facebook, Google+, Twitter, . . .heavily used nowadays HEINZ NIXDORF INSTITUTE (semi-) public user profiles communication collaboration: sharing and searching user generated content Current approaches are centralized full access to data: massive data-mining censorship single point of failure, scalability high operational costs University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 3
- 5. Introduction Decentralized Approaches For OSNs Peer-to-Peer based OSNs address drawbacks DHT-based solution (e.g. PeerSoN, LifeSocial) users build a structured P2P overlay key-based routing DHT: get, put joining and leaving replication HEINZ NIXDORF INSTITUTE University of Paderborn 0x11 0x1A 0x53 0xCB 0xA1 0x13 0xD1 Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 4
- 6. 1 Introduction 2 Distributed List Concept 3 Access Control in Distributed List Read and Write Access Key Distribution 4 Evaluation HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 5
- 7. Distributed List Concept Motivation For Distributed Data Structures HEINZ NIXDORF INSTITUTE University of Paderborn DHT operations (get, put) on single items do not match OSN applications Functionalities operate on collection of items guestbooks/ wall entries photo albums message history, . . . Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 6
- 8. 0x11 HEINZ NIXDORF INSTITUTE University of Paderborn 0x1A 0x53 0xCB 0xA1 0xD1 Distributed List Concept Storage Organization Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 7
- 9. A) List ^= DHT item + single get to retrieve list - overloaded peers - no parallelization 0x11 HEINZ NIXDORF INSTITUTE University of Paderborn 0x1A 0x53 0xCB 0xA1 0xD1 Distributed List Concept Storage Organization Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 7
- 10. A) List ^= DHT item + single get to retrieve list - overloaded peers - no parallelization B) List element ^= DHT item + parallelization + overloading less probable - many messages HEINZ NIXDORF INSTITUTE University of Paderborn 0x11 0x1A 0x53 0xCB 0xA1 0xD1 Distributed List Concept Storage Organization Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 7
- 11. Distributed List Concept Storage Organization A) List ^= DHT item + single get to retrieve list - overloaded peers - no parallelization B) List element ^= DHT item + parallelization + overloading less probable - many messages HEINZ NIXDORF INSTITUTE University of Paderborn 0x11 0x1A 0x53 0xCB 0xA1 0xD1 C) Partition list into buckets, store buckets in DHT + splitsize gives tradeoff between A) and B) i-th element has id=hash(listname + bi=splitsizec) Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 7
- 12. Distributed List Concept Remote Operations Operations on list by put/get functionalities inefficient whole buckets are sent through network, e.g., set(i): retrieve bucket, send back bucket contains(item): retrieve (several) bucket(s) HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 8
- 13. Distributed List Concept Remote Operations Operations on list by put/get functionalities inefficient whole buckets are sent through network, e.g., set(i): retrieve bucket, send back bucket contains(item): retrieve (several) bucket(s) Introduce Remote Operations use lookup function to issue commands message contains request, possibly some data + less traffic HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 8
- 14. 1 Introduction 2 Distributed List Concept 3 Access Control in Distributed List Read and Write Access Key Distribution 4 Evaluation HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 9
- 15. Access Control in Distributed List Example User Alice has friends Bob and Carol Alice Bob Carol HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 10
- 16. Access Control in Distributed List Example User Alice has friends Bob and Carol Alice has guestbook/ wall for friends (distributed list) Alice Bob Carol HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 10
- 17. User Alice has friends Bob and Carol Alice has guestbook/ wall for friends (distributed list) Only Alice and friends can read wall Alice HEINZ NIXDORF INSTITUTE University of Paderborn Dave Access Control in Distributed List Example Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 10
- 18. Access Control in Distributed List Example User Alice has friends Bob and Carol Alice has guestbook/ wall for friends (distributed list) Only Alice and friends can read wall Only Alice and friends may create new entries Alice Bob Carol HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 10
- 19. Access Control in Distributed List Example User Alice has friends Bob and Carol Alice has guestbook/ wall for friends (distributed list) Only Alice and friends can read wall Only Alice and friends may create new entries Alice HEINZ NIXDORF INSTITUTE University of Paderborn Dave Bob Carol Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 10
- 20. Access Control in Distributed List Example User Alice has friends Bob and Carol Alice has guestbook/ wall for friends (distributed list) Only Alice and friends can read wall Only Alice and friends may create new entries Only author can modify existing entry Alice HEINZ NIXDORF INSTITUTE University of Paderborn Dave Bob Carol Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 10
- 21. Access Control in Distributed List Using Cryptographic Means Restrict read access encrypt elements with common symmetric key Restrict changing elements HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 11
- 22. Access Control in Distributed List Using Cryptographic Means Restrict read access encrypt elements with common symmetric key Restrict changing elements sign elements with author’s private key (+nonce) storing peer verifies signatures Restrict adding elements HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 11
- 23. Access Control in Distributed List Using Cryptographic Means Restrict read access encrypt elements with common symmetric key Restrict changing elements sign elements with author’s private key (+nonce) storing peer verifies signatures Restrict adding elements bucket signed with common key of Alice and friends HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 11
- 24. 1 Introduction 2 Distributed List Concept 3 Access Control in Distributed List Read and Write Access Key Distribution 4 Evaluation HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 12
- 25. Access Control in Distributed List Key Distribution by Groups Bootstrap security (Graffi et al. IEEE LCN 2009) derive private key from user name and password derive public key = identifier of user HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 13
- 26. Access Control in Distributed List Key Distribution by Groups Bootstrap security (Graffi et al. IEEE LCN 2009) derive private key from user name and password derive public key = identifier of user Create and store a group item asymmetric key pair (eG; dG), symmetric key SG stored encrypted for each member HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 13
- 27. 1 Introduction 2 Distributed List Concept 3 Access Control in Distributed List Read and Write Access Key Distribution 4 Evaluation HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 14
- 28. Evaluation Impact on Traffic Simulation of 1000 list operations each bucket stored at different node elements of size 1 kB Operation A B get(i) 0:5 0:93 add(item) 0:375 0:053 remove(i) 0:125 0:017 HEINZ NIXDORF INSTITUTE University of Paderborn Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 15
- 29. Simulation of 1000 list operations each bucket stored at different node elements of size 1 kB traffic considerably reduced Operation A B get(i) 0:5 0:93 add(item) 0:375 0:053 remove(i) 0:125 0:017 HEINZ NIXDORF INSTITUTE University of Paderborn 0 200 400 600 800 1000 0 50000 150000 250000 operations traffic (kB) remote ops, splitsize=10, consolidation remote ops, splitsize=inf remote ops, splitsize=10 no remote ops, splitsize=inf 0 200 400 600 800 1000 0 2000 6000 10000 operations traffic (kB) remote ops, splitsize=10, consolidation remote ops, splitsize=inf remote ops, splitsize=10 no remote ops, splitsize=inf Evaluation Impact on Traffic Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 15
- 30. Simulation of 1000 list operations each bucket stored at different node elements of size 1 kB traffic considerably reduced traffic depends on splitsize Operation A B get(i) 0:5 0:93 add(item) 0:375 0:053 remove(i) 0:125 0:017 HEINZ NIXDORF INSTITUTE University of Paderborn 0 200 400 600 800 1000 0 10000 30000 operations traffic (kB) splitsize=1, no consolidation splitsize=5, no consolidation splitsize=20, no consolidation splitsize=100, no consolidation 0 200 400 600 800 1000 0 2000 4000 6000 operations traffic (kB) splitsize=1, no consolidation splitsize=5, no consolidation splitsize=20, no consolidation splitsize=100, no consolidation Evaluation Impact on Traffic Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 15
- 31. Summary HEINZ NIXDORF INSTITUTE University of Paderborn Distributed datastructures are useful for OSNs Buckets and remote operations allow flexible, efficient list functionalities Access control fundamental in OSNs Cryptographic approaches and groups to control access to list Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 16
- 32. Thank you for your attention! HEINZ NIXDORF INSTITUTE University of Paderborn Alexander Mäcker Heinz Nixdorf Institute & Department of Computer Science University of Paderborn Address: Fürstenallee 11 33102 Paderborn Germany E-mail: amaecker@upb.de Web: http://www.p2pframework.com Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 17
- 33. Remote Write Access HEINZ NIXDORF INSTITUTE University of Paderborn 1) C requests item from S; possibly sends hash of its own version of item 2) S replies with current version of item or ACK 3) C performs following steps perform change locally compute signature send back signature, command and old hash 4) C compares hashes; either performs changes locally and stores or back to step 2 Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 18
- 34. Consolidation of Distributed List 1) Initiating node computes B0k and B0k +1 and signatures Sig(B0k HEINZ NIXDORF INSTITUTE University of Paderborn ), Sig(B0k +1). Signatures sent to nodes Sk and Sk+1 storing Bk and Bk+1. Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 19
- 35. Consolidation of Distributed List 1) Initiating node computes B0k and B0k +1 and signatures Sig(B0k HEINZ NIXDORF INSTITUTE University of Paderborn ), Sig(B0k +1). k k 00Signatures sent to nodes Sk and Sk1 storing Bk and Bk1. ++2) Sk and Sk1 compute Band B++1. Cancel if differ from received ones. Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 19
- 36. Consolidation of Distributed List 1) Initiating node computes B0k and B0k +1 and signatures Sig(B0k HEINZ NIXDORF INSTITUTE University of Paderborn ), Sig(B0k +1). k k 00Signatures sent to nodes Sk and Sk1 storing Bk and Bk1. ++2) Sk and Sk1 compute Band B++1. Cancel if differ from received ones. 3) Sk+1 notifies Sk . Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 19
- 37. 1) Initiating node computes B0k and B0k +1 and signatures Sig(B0k HEINZ NIXDORF INSTITUTE University of Paderborn ), Sig(B0k +1). k k 00Signatures sent to nodes Sk and Sk1 storing Bk and Bk1. ++2) Sk and Sk1 compute Band B++1. Cancel if differ from received ones. 3) Sk+1 notifies Sk . 4) On reception of notification, Sk+1 stores B0k and notifies Sk+1. Consolidation of Distributed List Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 19
- 38. Consolidation of Distributed List 1) Initiating node computes B0k and B0k +1 and signatures Sig(B0k HEINZ NIXDORF INSTITUTE University of Paderborn ), Sig(B0k +1). k k 00Signatures sent to nodes Sk and Sk1 storing Bk and Bk1. ++2) Sk and Sk1 compute Band B++1. Cancel if differ from received ones. 3) Sk+1 notifies Sk . 4) On reception of notification, Sk+1 stores B0k and notifies Sk+1. 5) On reception of notification, Sk stores B0k +1 after checking that B0k is stored as expected. Secure Distributed Data Structures for Peer-to-Peer-based Social Networks Alexander Mäcker 19