End-to-end Secure Data Aggregation in Wireless Sensor Networks Keyur Parmar 1 Devesh Jinwala 2 1 Ph.D Scholar & Senior Research Fellow Department of Computer Engineering SVNIT, Surat, India 2 Professor Department of Computer Engineering SVNIT, Surat, India December 18, 2014 Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 1/34
Outline 1 Introduction 2 Preliminaries 3 MR-CDA 4 Conclusions Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 2/34
Outline 1 Introduction 2 Preliminaries 3 MR-CDA 4 Conclusions Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 3/34
Introduction Wireless Sensor Nodes Equipped with Sensing and Actuation Capability Self-organizing Self-healing Highly Constrained Resources Processor Bandwidth Memory and Storage Space Communication and Computation Power Sensor Node = Sensing + Processing + Communication Akyildiz et al. Wireless Sensor Networks: A Survey. Computer Networks, Elsevier, 38(4), 393422, (2002). Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 4/34
In-network Processing (Data Aggregation) Reduces Data Transmission Improves Energy Efficiency Fasolo et al. In-network Aggregation Techniques for Wireless Sensor Networks: A Survey. Wireless Communications, IEEE 14(2), 70-87, (2007). Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 5/34
Secure Data Aggregation Types of Secure Data Aggregation Hop-by-Hop Secure Data Aggregation End-to-End Secure Data Aggregation (CDA) Ozdemir et al. Secure Data Aggregation in Wireless Sensor Networks: A Comprehensive Overview. Computer Networks, 53(12), 2022 2037, (2009). Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 6/34
Concealed Data Aggregation Security Requirements Integrity/Message Authentication Confidentiality/Privacy Replay Protection Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 7/34
Outline 1 Introduction 2 Preliminaries 3 MR-CDA 4 Conclusions Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 8/34
Privacy Homomorphism Homomorphic Primitives Homomorphic Encryption Homomorphic Message Authentication Codes Rivest et al. On Data Banks and Privacy Homomorphisms. Foundations of Secure Computation 4(11), 169 180, (1978) Agrawal, S. et al. Homomorphic MACs: MAC-based Integrity for Network Coding. In: Proceedings of the 7th ACNS, pp. 292 305. Springer, Berlin, Heidelberg, (2009). Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 9/34
Privacy Homomorphism - Example Castelluccia et al. Efficient and provably secure aggregation of encrypted data in wireless sensor networks. ACM Transactions on Sensor Networks, 5(3), 20:1-20:36, 2009. Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 10/34
Privacy Homomorphism - Example Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 11/34
Privacy Homomorphism - Example Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 12/34
Privacy Homomorphism - Example Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 13/34
Privacy Homomorphism - Example Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 14/34
Privacy Homomorphism - Example Castelluccia et al. Efficient and provably secure aggregation of encrypted data in wireless sensor networks. ACM Transactions on Sensor Networks, 5(3), 20:1-20:36, 2009. Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 15/34
Privacy Homomorphism - Tradeoffs Malleability Non-Malleability Security Level Non-Malleability Adaptive Chosen Ciphertext Attack Malleability Chosen Ciphertext attack Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 16/34
Outline 1 Introduction 2 Preliminaries 3 MR-CDA 4 Conclusions Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 17/34
MR-CDA - Example Node 1 computes, C 1 = E BS (M 1 ) T 1 = MAC(C 1 ) E 1,3 (T 1 ) E 1,5 (T 1 ) Node 1 transmits, 1 3 C 1 E 1,3 (T 1 ) E 1,5 (T 1 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 18/34
MR-CDA - Example Node 2 computes, C 2 = E BS (M 2 ) T 2 = MAC(C 2 ) E 2,3 (T 2 ) E 2,5 (T 2 ) Node 2 transmits, 2 3 C 2 E 2,3 (T 2 ) E 2,5 (T 2 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 19/34
MR-CDA - Example 1 Node 3 decrypts, T 1 = D 1,3 (T 1 ) 2 Node 3 generates, T 1 = MAC(C 1) 3 Node 3 compares, T 1 = T 1? 4 Node 3 decrypts, T 2 = D 2,3 (T 2 ) 5 Node 3 generates, T 2 = MAC(C 2) 6 Node 3 compares, T 2 = T 2? Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 20/34
MR-CDA - Example Node 3 computes, C 3 = C 1 C 2 T 3 = T 1 T 2 E 3,5 (T 3 ) E 3,7 (T 3 ) Node 3 transmits, 3 5 C 3 E 3,5 (T 3 ) E 3,7 (T 3 ) E 1,5 (T 1 ) E 2,5 (T 2 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 21/34
MR-CDA - Example Node 5 receives, 3 5 C 3 E 3,5 (T 3 ) E 3,7 (T 3 ) E 1,5 (T 1 ) E 2,5 (T 2 ) Node 5 receives, 4 5 C 4 E 4,5 (T 4 ) E 4,7 (T 4 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 22/34
MR-CDA - Example 1 Node 5 decrypts, T 1 = D 1,5 (T 1 ) T 2 = D 2,5 (T 2 ) T 3 = D 3,5 (T 3 ) T 4 = D 4,5 (T 4 ) 2 Node 5 generates, T T 3 = MAC(C 3) 4 = MAC(C 4) 3 Node 5 compares, T 3 = T 3? T 4 = T 4? 4 Node 5 compares, T 3 = T 1 T 2 Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 23/34
MR-CDA - Example Node 5 computes, C 5 = C 3 C 4 T 5 = T 3 T 4 E 5,7 (T 5 ) E 5,8 (T 5 ) Node 5 transmits, 5 7 C 5 E 5,7 (T 5 ) E 5,8 (T 5 ) E 3,7 (T 3 ) E 4,7 (T 4 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 24/34
MR-CDA - Example Node 7 receives, 5 7 C 5 E 5,7 (T 5 ) E 5,8 (T 5 ) E 3,7 (T 3 ) E 4,7 (T 4 ) Node 7 receives, 6 7 C 6 E 6,7 (T 6 ) E 6,8 (T 6 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 25/34
MR-CDA - Example 1 Node 7 decrypts, T 3 = D 3,7 (T 3 ) T 4 = D 4,7 (T 4 ) T 5 = D 5,7 (T 5 ) T 6 = D 6,7 (T 6 ) 2 Node 7 generates, T T 5 = MAC(C 5) 6 = MAC(C 6) 3 Node 5 compares, T 5 = T 5? T 6 = T 6? 4 Node 7 compares, T 5 = T 3 T 4 Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 26/34
MR-CDA - Example Node 7 computes, C 7 = C 5 C 6 T 7 = T 5 T 6 E 7,8 (T 7 ) Node 7 transmits, 7 8 C 7 E 5,8 (T 5 ) E 6,8 (T 6 ) E 7,8 (T 7 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 27/34
MR-CDA - Example Node 8 receives, 7 8 C 7 E 5,8 (T 5 ) E 6,8 (T 6 ) E 7,8 (T 7 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 28/34
MR-CDA - Example 1 Node 8 decrypts, T 5 = D 5,8 (T 5 ) T 6 = D 6,8 (T 6 ) T 7 = D 7,8 (T 7 ) 2 Node 8 generates, T 7 = MAC(C 7) 3 Node 8 compares, T 7 = T 7? 4 Node 8 compares, T 7 = T 5 T 6 5 Node 8 decrypts, D BS (C 7 ) = M 1 M 2 M 4 M 6 Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 29/34
MR-CDA - Example D 7,8 (T 7 ) = MAC(C 7 )? 1 : 0 D 5,8 (T 5 ) D 6,8 (T 6 ) = D 7,8 (T 7 )? 1 : 0 8 D 5,7 (T 5 ) = MAC(C 5 )? 1 : 0 D 6,7 (T 4 ) = MAC(C 6 )? 1 : 0 D 3,7 (T 3 ) D 4,7 (T 4 ) = D 5,7 (T 5 )? 1 : 0 C 7 =C 5 C 6 & T 7 =T 5 T 6 C 7, E 7,8 (T 7 ), E 5,8 (T 5 ), E 6,8 (T 6 ) D 3,5 (T 3 ) = MAC(C 3 )? 1 : 0 D 4,5 (T 4 ) = MAC(C 4 )? 1 : 0 D 1,5 (T 1 ) D 2,5 (T 2 ) = D 3,5 (T 3 )? 1 : 0 C 5 =C 3 C 4 & T 5 =T 3 T 4 C 5, E 5,7 (T 5 ), E 5,8 (T 5 ), E 3,7 (T 3 ), E 4,7 (T 4 ) 7 5 6 C 6, E 6,7 (T 6 ), E 6,8 (T 6 ) D 1,3 (T 1 ) = MAC(C 1 )? 1 : 0 D 2,3 (T 2 ) = MAC(C 2 )? 1 : 0 C 3 =C 1 C 2 & T 3 =T 1 T 2 C 3, E 3,5 (T 3 ), E 3,7 (T 3 ), E 1,5 (T 1 ), E 2,5 (T 2 ) 3 4 C 4, E 4,5 (T 4 ), E 4,7 (T 4 ) C 1, E 1,3 (T 1 ), E 1,5 (T 1 ) 1 2 C 2, E 2,3 (T 2 ), E 2,5 (T 2 ) Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 30/34
Outline 1 Introduction 2 Preliminaries 3 MR-CDA 4 Conclusions Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 31/34
Conclusions Data Aggregation and Privacy Data aggregation - Plaintext data Privacy - Encrypted data Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 32/34
Conclusions Data Aggregation and Privacy Data aggregation - Plaintext data Privacy - Encrypted data Data Aggregation and Message Authentication Data aggregation modifies the original data Message authentication requires the original data Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 32/34
Conclusions Data Aggregation and Privacy Data aggregation - Plaintext data Privacy - Encrypted data Data Aggregation and Message Authentication Data aggregation modifies the original data Message authentication requires the original data Privacy and Message Authentication Privacy - Encrypted data Authentication - Plaintext data Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 32/34
Publication/Acknowledgement Publication Keyur Parmar and Devesh C. Jinwala, Malleability Resilient Concealed Data Aggregation, in Proceedings of the 20th EUNICE/IFIP WG 6.2, 6.6 Workshop on Advances in Communication Networking, France, ser. EUNICE 14. Lecture Notes in Computer Science (LNCS), pp. 160 172, Springer-Verlag, Berlin, Heidelberg, 2014. Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 33/34
Publication/Acknowledgement Publication Keyur Parmar and Devesh C. Jinwala, Malleability Resilient Concealed Data Aggregation, in Proceedings of the 20th EUNICE/IFIP WG 6.2, 6.6 Workshop on Advances in Communication Networking, France, ser. EUNICE 14. Lecture Notes in Computer Science (LNCS), pp. 160 172, Springer-Verlag, Berlin, Heidelberg, 2014. Acknowledgement This research is a part of the project A Secure Data Aggregation System and An Intrusion Detection System for Wireless Sensor Networks. It is supported by the Department of Electronics and Information Technology, Ministry of Communications and Information Technology, Government of India. Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 33/34
Get your facts first, then you can distort them as you please. Mark Twain Thank You... Keyur Parmar keyur.mtech@gmail.com The Tenth ICISS-2014 34/34