Abstract
In modern distributed systems, an adversary’s limitations when corrupting subsets of a system’s components (e.g., servers) may not necessarily be based on threshold constraints, but rather based on other technical or organizational characteristics. This means that the corruption patterns (and thus protection guarantees) are based on the adversary being limited by what can be captured by a General Adversary Structure (GAS). We consider efficient secure multiparty computation (MPC) under such dynamically-changing GAS settings. In such settings, one desires to protect against and during corruption profile changes; such adaptivity also renders some (secret sharing-based) encoding schemes underlying MPC protocols more efficient than others when operating with the (currently) considered GAS.
One of our contributions is a set of new protocols to efficiently and securely convert back and forth between different MPC schemes for GAS; this process is often called share conversion. We consider two MPC schemes, one based on additive secret sharing and the other based on Monotone Span Programs (MSP). The ability to convert between the secret sharing representations of these MPC schemes enables us to construct the first communication-efficient structure-adaptive proactive MPC protocol for dynamic GAS settings. By structure-adaptive, we mean that the choice of the MPC protocol to execute in future rounds after the GAS is changed (as specified by an administrative entity) is chosen to ensure communication-efficiency (the typical bottleneck in MPC). Furthermore, since such secure “collaborative” computing may be long-lived, we consider the mobile adversary setting, often called the proactive security setting. As our second contribution, we construct communication-efficient MPC protocols that can adapt to the proactive security setting. Proactive security assumes that at each (well defined) period of time the adversary corrupts different parties and may visit the entire system overtime and corrupt all parties, provided that in each period it controls groups obeying the GAS constraints. In our protocol, the shares can be refreshed, meaning that parties receive new shares reconstructing the same secret, and some parties who lost their shares because of the reboot/reset can recover their shares. As our third contribution, we consider another aspect of global long-term computations, namely, that of the dynamic groups. Settings with dynamic groups and GAS were not dealt with in existing literature on (proactive) MPC. In dynamic group settings, parties can be added and eliminated from the computation, under different GAS restrictions. We extend our protocols to this additional dynamic group settings defined by different GAS (see the full version of the paper [18] for formal details of protocols and proofs).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
In our model, rebooting to a clean state includes global information, e.g., circuits to be computed via MPC, identities of parties in the computation, and access to secure point-to-point channels and a broadcast channel.
References
Almansa, J.F., Damgård, I., Nielsen, J.B.: Simplified threshold RSA with adaptive and proactive security. In: Vaudenay, S. (ed.) EUROCRYPT 2006. LNCS, vol. 4004, pp. 593–611. Springer, Heidelberg (2006). https://doi.org/10.1007/11761679_35
Backes, M., Cachin, C., Strobl, R.: Proactive secure message transmission in asynchronous networks. In: Proceedings of the Twenty-Second ACM Symposium on Principles of Distributed Computing, PODC 2003, Boston, Massachusetts, USA, 13–16 July 2003, pp. 223–232 (2003)
Baron, J., Eldefrawy, K., Lampkins, J., Ostrovsky, R.: How to withstand mobile virus attacks, revisited. In: Proceedings of the 2014 ACM Symposium on Principles of Distributed Computing, PODC 2014, pp. 293–302 (2014)
Baron, J., Defrawy, K.E., Lampkins, J., Ostrovsky, R.: Communication-optimal proactive secret sharing for dynamic groups. In: Malkin, T., Kolesnikov, V., Lewko, A.B., Polychronakis, M. (eds.) ACNS 2015. LNCS, vol. 9092, pp. 23–41. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-28166-7_2
Beerliová-Trubíniová, Z., Hirt, M.: Perfectly-secure MPC with linear communication complexity. In: Canetti, R. (ed.) TCC 2008. LNCS, vol. 4948, pp. 213–230. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78524-8_13
Michael Ben-Or, S.G., Wigderson, A.: Completeness theorems for non-cryptographic fault-tolerant distributed computation (extended abstract). In: STOC, pp. 1–10 (1988)
Ben-Sasson, E., Fehr, S., Ostrovsky, R.: Near-linear unconditionally-secure multiparty computation with a dishonest minority. In: Safavi-Naini, R., Canetti, R. (eds.) CRYPTO 2012. LNCS, vol. 7417, pp. 663–680. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32009-5_39
Blakley, G.R.: Safeguarding cryptographic keys. In: Proceedings of AFIPS National Computer Conference, vol. 48, pp. 313–317 (1979)
Canetti, R., Herzberg, A.: Maintaining security in the presence of transient faults. In: Desmedt, Y.G. (ed.) CRYPTO 1994. LNCS, vol. 839, pp. 425–438. Springer, Heidelberg (1994). https://doi.org/10.1007/3-540-48658-5_38
Castro, M., Liskov, B.: Practical byzantine fault tolerance and proactive recovery. ACM Trans. Comput. Syst. 20(4), 398–461 (2002)
Chaum, D., Crépeau, C., Damgard, I.: Multiparty unconditionally secure protocols. In: Proceedings of the Twentieth Annual ACM Symposium on Theory of Computing, STOC 1988, pp. 11–19 (1988)
Cramer, R., Damgård, I., Maurer, U.: Span programs and general secure multi-party computation. BRICS Rep. Ser. 4(28) (1997)
Damgård, I., Ishai, Y., Krøigaard, M.: Perfectly secure multiparty computation and the computational overhead of cryptography. In: Gilbert, H. (ed.) EUROCRYPT 2010. LNCS, vol. 6110, pp. 445–465. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13190-5_23
Damgård, I., Ishai, Y., Krøigaard, M., Nielsen, J.B., Smith, A.: Scalable multiparty computation with nearly optimal work and resilience. In: Wagner, D. (ed.) CRYPTO 2008. LNCS, vol. 5157, pp. 241–261. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85174-5_14
Dolev, S., Garay, J., Gilboa, N., Kolesnikov, V.: Swarming secrets. In: 47th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2009, pp. 1438–1445, September 2009
Dolev, S., Garay, J.A., Gilboa, N., Kolesnikov, V.: Secret sharing Krohn-Rhodes: private and perennial distributed computation. In: Innovations in Computer Science - ICS 2010, Tsinghua University, Beijing, China, 7–9 January 2011. Proceedings, pp. 32–44 (2011)
Dolev, S., Garay, J.A., Gilboa, N., Kolesnikov, V., Yuditsky, Y.: Towards efficient private distributed computation on unbounded input streams. J. Mathe. Cryptol. 9(2), 79–94 (2015)
Eldefrawy, K., Hwang, S., Ostrovsky, R., Yung, M.: Communication-efficient (proactive) secure computation for dynamic general adversary structures and dynamic groups. Cryptology ePrint Archive, Report 2020/747 (2020). https://eprint.iacr.org/2020/747.pdf
Eldefrawy, K., Ostrovsky, R., Park, S., Yung, M.: Proactive secure multiparty computation with a dishonest majority. In: Catalano, D., De Prisco, R. (eds.) SCN 2018. LNCS, vol. 11035, pp. 200–215. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98113-0_11
Frankel, Y., Gemmell, P., MacKenzie, P.D., Yung, M.: Proactive RSA. In: Kaliski, B.S. (ed.) CRYPTO 1997. LNCS, vol. 1294, pp. 440–454. Springer, Heidelberg (1997). https://doi.org/10.1007/BFb0052254
Goldreich, O., Micali, S., Wigderson, A.: How to play any mental game. In: Proceedings of the Nineteenth Annual ACM Symposium on Theory of Computing, STOC 1987, pp. 218–229 (1987)
Herzberg, A., Jarecki, S., Krawczyk, H., Yung, M.: Proactive secret sharing or: how to cope with perpetual leakage. In: Coppersmith, D. (ed.) CRYPTO 1995. LNCS, vol. 963, pp. 339–352. Springer, Heidelberg (1995). https://doi.org/10.1007/3-540-44750-4_27
Hirt, M., Maurer, U., Lucas, C.: A dynamic tradeoff between active and passive corruptions in secure multi-party computation. In: Canetti, R., Garay, J.A. (eds.) CRYPTO 2013. LNCS, vol. 8043, pp. 203–219. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40084-1_12
Hirt, M., Tschudi, D.: Efficient general-adversary multi-party computation. In: Sako, K., Sarkar, P. (eds.) ASIACRYPT 2013. LNCS, vol. 8270, pp. 181–200. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-42045-0_10
Ishai, Y., Kushilevitz, E., Ostrovsky, R., Sahai, A.: Cryptography with constant computational overhead. In: STOC, pp. 433–442 (2008)
Lampkins, J., Ostrovsky, R.: Communication-efficient MPC for general adversary structures. In: Abdalla, M., De Prisco, R. (eds.) SCN 2014. LNCS, vol. 8642, pp. 155–174. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10879-7_10
Maurer, U.: Secure multi-party computation made simple. In: Cimato, S., Persiano, G., Galdi, C. (eds.) SCN 2002. LNCS, vol. 2576, pp. 14–28. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-36413-7_2
Ostrovsky, R., Yung, M.: How to withstand mobile virus attacks (extended abstract). In: PODC, pp. 51–59 (1991)
Rabin, T., Ben-Or, M.: Verifiable secret sharing and multiparty protocols with honest majority. In: Proceedings of the Twenty-First Annual ACM Symposium on Theory of Computing, STOC 1989, pp. 73–85 (1989)
Shamir, A.: How to share a secret. Commun. ACM 22(11), 612–613 (1979)
Yao, A.C.: Protocols for secure computations. In: Proceedings of the 23rd Annual Symposium on Foundations of Computer Science, FOCS 1982, pp. 160–164 (1982)
Acknowledgements
Rafail Ostrovsky is supported in part by DARPA and NIWC Pacific under contract N66001-15-C-4065, DARPA under Cooperative Agreement No: HR0011-20-2-0025, the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via 2019-1902070008, NSF-BSF Grant 1619348, US-Israel BSF grant 2012366, Google Faculty Award, JP Morgan Faculty Award, IBM Faculty Research Award, Xerox Faculty Research Award, OKAWA Foundation Research Award, B. John Garrick Foundation Award, Teradata Research Award, and Lockheed-Martin Corporation Research Award. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, the Department of Defense, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Eldefrawy, K., Hwang, S., Ostrovsky, R., Yung, M. (2020). Communication-Efficient (Proactive) Secure Computation for Dynamic General Adversary Structures and Dynamic Groups. In: Galdi, C., Kolesnikov, V. (eds) Security and Cryptography for Networks. SCN 2020. Lecture Notes in Computer Science(), vol 12238. Springer, Cham. https://doi.org/10.1007/978-3-030-57990-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-57990-6_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57989-0
Online ISBN: 978-3-030-57990-6
eBook Packages: Computer ScienceComputer Science (R0)