[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
research-article

Formal Modelling and Automated Trade-off Analysis of Enforcement Architectures for Cryptographic Access Control in the Cloud

Published: 23 November 2021 Publication History

Abstract

To facilitate the adoption of cloud by organizations, Cryptographic Access Control (CAC) is the obvious solution to control data sharing among users while preventing partially trusted Cloud Service Providers (CSP) from accessing sensitive data. Indeed, several CAC schemes have been proposed in the literature. Despite their differences, available solutions are based on a common set of entities—e.g., a data storage service or a proxy mediating the access of users to encrypted data—that operate in different (security) domains—e.g., on-premise or the CSP. However, the majority of these CAC schemes assumes a fixed assignment of entities to domains; this has security and usability implications that are not made explicit and can make inappropriate the use of a CAC scheme in certain scenarios with specific trust assumptions and requirements. For instance, assuming that the proxy runs at the premises of the organization avoids the vendor lock-in effect but may give rise to other security concerns (e.g., malicious insiders attackers).
To the best of our knowledge, no previous work considers how to select the best possible architecture (i.e., the assignment of entities to domains) to deploy a CAC scheme for the trust assumptions and requirements of a given scenario. In this article, we propose a methodology to assist administrators in exploring different architectures for the enforcement of CAC schemes in a given scenario. We do this by identifying the possible architectures underlying the CAC schemes available in the literature and formalizing them in simple set theory. This allows us to reduce the problem of selecting the most suitable architectures satisfying a heterogeneous set of trust assumptions and requirements arising from the considered scenario to a decidable Multi-objective Combinatorial Optimization Problem (MOCOP) for which state-of-the-art solvers can be invoked. Finally, we show how we use the capability of solving the MOCOP to build a prototype tool assisting administrators to preliminarily perform a “What-if” analysis to explore the trade-offs among the various architectures and then use available standards and tools (such as TOSCA and Cloudify) for automated deployment in multiple CSPs.

References

[1]
Assad Abbas and Samee U. Khan. 2014. A review on the state-of-the-art privacy-preserving approaches in the e-health clouds. IEEE J. Biomed. Health Inform. 18, 4 (July 2014), 1431–1441. https://doi.org/10.1109/JBHI.2014.2300846
[2]
Mikhail J. Atallah, Marina Blanton, Nelly Fazio, and Keith B. Frikken. 2009. Dynamic and efficient key management for access hierarchies. ACM Trans. Info. Syst. Secur. 12, 3, Article 18 (Jan. 2009), 43 pages. https://doi.org/10.1145/1455526.1455531
[3]
Stefano Berlato, Roberto Carbone, Silvio Ranise, and Adam J. Lee. 2020. Exploring architectures for cryptographic access control enforcement in the cloud for fun and optimization. In Proceedings of the 15th ACM ASIA Conference on Computer and Communications Security (ASIACCS’20). ACM. https://doi.org/10.1145/3320269.3384767
[4]
John Bethencourt, Amit Sahai, and Brent Waters. 2007. Ciphertext-policy attribute-based encryption. In Proceedings of the IEEE Symposium on Security and Privacy (SP’07). https://doi.org/10.1109/SP.2007.11
[5]
Arnar Birgisson, Joe Gibbs Politz, Ulfar Erlingsson, Ankur Taly, Michael Vrable, and Mark Lentczner. 2014. Macaroons: Cookies with contextual caveats for decentralized authorization in the cloud. In Proceedings of the 2014 Network and Distributed System Security Symposium. DOI:https://doi.org/10.14722/ndss.2014.23212
[6]
Ning Cao, Cong Wang, Ming Li, Kui Ren, and Wenjing Lou. 2014. Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 25, 1 (Jan. 2014), 222–233. https://doi.org/10.1109/TPDS.2013.45
[7]
Marios D. Dikaiakos, Dimitrios Katsaros, Pankaj Mehra, George Pallis, and Athena Vakali. 2009. Cloud computing: Distributed internet computing for IT and scientific research. IEEE Internet Comput. 13, 5 (Sept. 2009), 10–13. https://doi.org/10.1109/MIC.2009.103
[8]
Judicael B. Djoko, Jack Lange, and Adam J. Lee. NeXUS: Practical and secure access control on untrusted storage platforms using client-side SGX. In Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN’19). IEEE, 401–413. https://doi.org/10.1109/DSN.2019.00049
[9]
Josep Domingo-Ferrer, Oriol Farras, Jordi Ribes-Gonzalez, and David Sanchez. 2019. Privacy-preserving cloud computing on sensitive data: A survey of methods, products and challenges. Comput. Commun. 140-141 (May 2019), 38–60. https://doi.org/10.1016/j.comcom.2019.04.011
[10]
Anna Lisa Ferrara, Georg Fachsbauer, Bin Liu, and Bogdan Warinschi. 2015. Policy privacy in cryptographic access control. In Proceedings of the IEEE 28th Computer Security Foundations Symposium. IEEE, 46–60. https://doi.org/10.1109/CSF.2015.11
[11]
Sara Foresti, Sushil Jajodia, Stefano Paraboschi, and Pierangela Samarati. 2010. Encryption policies for regulating access to outsourced data. ACM Trans. Database Syst. 35 (Apr. 2010), 12. https://doi.org/10.1145/1735886.1735891
[12]
William C. Garrison, Adam Shull, Steven Myers, and Adam J. Lee. 2016. On the practicality of cryptographically enforcing dynamic access control policies in the cloud. In Proceedings of the IEEE Symposium on Security and Privacy (SP’16). IEEE, 819–838. https://doi.org/10.1109/SP.2016.54
[13]
Valentin Ghita, Sergiu Costea, and Nicolae Tapus. 2017. Implementation of cryptographically enforced RBAC. Sci. Bull. Univ. Politech. Bucharest 79, 2 (2017), 9–3–102.
[14]
Parke Godfrey, Ryan Shipley, and Jarek Gryz. 2007. Algorithms and analyses for maximal vector computation. VLDB J. 16 (01 2007), 5–28. https://doi.org/10.1007/s00778-006-0029-7
[15]
S. Goel and V. Chen. 2005. Information security risk analysis—A matrix-based approach. Retrieved on 08 September, 2021 from https://www.albany.edu/goel/publications/goelchen2005.pdf.
[16]
Vipul Goyal, Abhishek Jain, Omkant Pandey, and Amit Sahai. 2008. Bounded ciphertext policy attribute based encryption. In Proceedings of the 35th International Colloquium on Automata, Languages and Programming (ICALP’08). 579–591. https://doi.org/10.1007/978-3-540-70583-3_47
[17]
Vipul Goyal, Omkant Pandey, Amit Sahai, and Brent Waters. 2006. Attribute-based encryption for fine-grained access control of encrypted data. In Proceedings of the ACM Conference on Computer and Communications Security. 89–98. https://doi.org/10.1145/1180405.1180418
[18]
Horst W. Hamacher, Christian Roed Pedersen, and Stefan Ruzika. 2007. Multiple objective minimum cost flow problems: A review. Eur. J. Operation. Res. 176, 3 (Feb. 2007), 1404–1422. https://doi.org/10.1016/j.ejor.2005.09.033
[19]
Felix Horandner, Stephan Krenn, Andrea Migliavacca, Florian Thiemer, and Bernd Zwattendorfer. 2016. CREDENTIAL: A framework for privacy-preserving cloud-based data sharing. In Proceedings of the 11th International Conference on Availability, Reliability and Security (ARES’16). IEEE, 742–749. https://doi.org/10.1109/ARES.2016.79
[20]
Jeremy Horwitz and Ben Lynn. 2002. Toward hierarchical identity-based encryption. In Proceedings of the International Conference on the Theory and Applications of Cryptographic Techniques (EUROCRYPT’02). 466–481. https://doi.org/10.1007/3-540-46035-7_31
[21]
Yashpalsinh Jadeja and Kirit Modi. 2012. Cloud computing—Concepts, architecture and challenges. In Proceedings of the International Conference on Computing, Electronics and Electrical Technologies (ICCEET’12). IEEE, 877–880. https://doi.org/10.1109/ICCEET.2012.6203873
[22]
Julian Jang-Jaccard. 2018. A practical client application based on attribute based access control for untrusted cloud storage. In Computer Science & Information Technology. Academy & Industry Research Collaboration Center (AIRCC), 1–15. https://doi.org/10.5121/csit.2018.80101
[23]
Md. Tanzim Khorshed, A. B. M. Shawkat Ali, and Saleh A. Wasimi. 2012. A survey on gaps, threat remediation challenges and some thoughts for proactive attack detection in cloud computing. Future Gen. Comput. Syst. 28, 6 (June 2012), 833–851. https://doi.org/10.1016/j.future.2012.01.006
[24]
Kathrin Klamroth. Discrete multiobjective optimization. In Evolutionary Multi-Criterion Optimization, Matthias Ehrgott, Carlos M. Fonseca, Xavier Gandibleux, Jin-Kao Hao, and Marc Sevaux (Eds.). Vol. 5467. Springer, Berlin, 4–4. https://doi.org/10.1007/978-3-642-01020-0_4Series Title: Lecture Notes in Computer Science.
[25]
Rakesh Kumar and Rinkaj Goyal. 2019. On cloud security requirements, threats, vulnerabilities and countermeasures: A survey. Comput. Sci. Rev. 33 (Aug. 2019), 1–48. https://doi.org/10.1016/j.cosrev.2019.05.002
[26]
Arseny Kurnikov, Andrew Paverd, Mohammad Mannan, and N. Asokan. Keys in the clouds: Auditable multi-device access to cryptographic credentials. In Proceedings of the 13th International Conference on Availability, Reliability and Security (ARES’18). ACM Press, 1–10. https://doi.org/10.1145/3230833.3234518
[27]
Thomas Loruenser, Daniel Slamanig, Thomas Langer, and Henrich C. Pohls. 2016. PRISMACLOUD tools: A cryptographic toolbox for increasing security in cloud services. In Proceedings of the 11th International Conference on Availability, Reliability and Security (ARES’16). IEEE, Salzburg, Austria, 733–741. https://doi.org/10.1109/ARES.2016.62
[28]
Sascha Muller and Stefan Katzenbeisser. 2012. Hiding the policy in cryptographic access control. In Security and Trust Management. 90–105. https://doi.org/10.1007/978-3-642-29963-6_8
[29]
Rafail Ostrovsky, Amit Sahai, and Brent Waters. 2007. Attribute-based encryption with non-monotonic access structures. In Proceedings of the 14th ACM Conference on Computer and Communications Security (CCS’07). 195–203. https://doi.org/10.1145/1315245.1315270
[30]
Kumar P. Praveen, Kumar P. Syan, and P. J. A. Alphonse.2018. Attribute based encryption in cloud computing: A survey, gap analysis, and future directions. J. Netw. Comput. Appl. 108 (Apr. 2018), 37–52. https://doi.org/10.1016/j.jnca.2018.02.009
[31]
David W. Pentico. 2007. Assignment problems: A golden anniversary survey. Eur. J. Operation. Res. 176, 2 (Jan. 2007), 774–793. https://doi.org/10.1016/j.ejor.2005.09.014
[32]
R. Perlman. 2005. File system design with assured delete. In Proceedings of the 3rd IEEE International Security in Storage Workshop (SISW’05). IEEE, San Francisco, CA, 83–88. https://doi.org/10.1109/SISW.2005.5
[33]
Uthpala Premarathne, Alsharif Abuadbba, Abdulatif Alabdulatif, Ibrahim Khalil, Zahir Tari, Albert Zomaya, and Rajkumar Buyya. 2016. Hybrid cryptographic access control for cloud-based EHR systems. IEEE Cloud Comput. 3, 4 (July 2016), 58–64. https://doi.org/10.1109/MCC.2016.76
[34]
Saiyu Qi and Yuanqing Zheng. 2019. Crypt-DAC: Cryptographically enforced dynamic access control in the cloud. IEEE Trans. Depend. Secure Comput. (2019), 1–1. https://doi.org/10.1109/TDSC.2019.2908164
[35]
Gururaj Ramachandra, Mohsin Iftikhar, and Farrukh Aslam Khan. 2017. A comprehensive survey on security in cloud computing. Procedia Comput. Sci. 110 (2017), 465–472. https://doi.org/10.1016/j.procs.2017.06.124
[36]
E. Ramirez, J. Brill, M. K. Ohlhausen, J. D. Wright, and T. McSweeny. 2014. Data brokers: A call for transparency and accountability. In Data Brokers: A Call for Transparency and Accountability. CreateSpace Independent Publishing Platform, 1–101.
[37]
Fatemeh Rezaeibagha and Yi Mu. 2016. Distributed clinical data sharing via dynamic access-control policy transformation. Int. J. Med. Info. 89 (May 2016), 25–31. https://doi.org/10.1016/j.ijmedinf.2016.02.002
[38]
R. L. Rivest, A. Shamir, and L. Adleman. 1978. A method for obtaining digital signatures and public-key cryptosystems. Commun. ACM 21, 2 (Feb. 1978), 120–126. https://doi.org/10.1145/359340.359342
[39]
Pierangela Samarati and Sabrina de Capitani di Vimercati. 2000. Access control: Policies, models, and mechanisms. In Foundations of Security Analysis and Design, Riccardo Focardi and Roberto Gorrieri (Eds.). Vol. 2171. Springer, Berlin, 137–196. https://doi.org/10.1007/3-540-45608-2_3
[40]
Ravi Sandhu. 1998. Access control: Principle and practice. Adv. Comput. 46 (10 1998), 237–286. https://doi.org/10.1016/S0065-2458(08)60206-5
[41]
Hiroyuk Sato and Somchart Fugkeaw. 2015. Design and implementation of collaborative ciphertext-policy attribute-role based encryption for data access control in cloud. J. Info. Secur. Res. 6, 3 (Sept. 2015), 71–84.
[42]
Adi Shamir. 1979. How to share a secret. Commun. ACM 22, 11 (Nov. 1979), 612–613. https://doi.org/10.1145/359168.359176
[43]
Enrico Signoretti. GigaOm Radar for File-Based Cloud Storage. Retrieved from https://gigaom.com/report/gigaom-radar-for-file-based-cloud-storage/.
[44]
Ashish Singh and Kakali Chatterjee. 2017. Cloud security issues and challenges: A survey. J. Netw. Comput. Appl. 79 (Feb. 2017), 88–115. https://doi.org/10.1016/j.jnca.2016.11.027
[45]
Yang Tang, Patrick P. C. Lee, John C. S. Lui, and Radia Perlman. 2012. FADE: Secure overlay cloud storage with file assured deletion. IEEE Trans. Depend. Secure Comput. 9, 6 (Nov. 2012), 903–916. https://doi.org/10.1109/TDSC.2012.49
[46]
Saman Zarandioon, Danfeng Yao, and Vinod Ganapathy. 2012. K2C: Cryptographic cloud storage with lazy revocation and anonymous access. In Security and Privacy in Communication Networks, Muttukrishnan Rajarajan, Fred Piper, Haining Wang, and George Kesidis (Eds.). Vol. 96. Springer, Berlin, 59–76. https://doi.org/10.1007/978-3-642-31909-9_4
[47]
Lan Zhou, Vijay Varadharajan, and Michael Hitchens. 2013. Achieving secure role-based access control on encrypted data in cloud storage. IEEE Trans. Info. Forensics Secur. 8, 12 (Dec. 2013), 1947–1960. https://doi.org/10.1109/TIFS.2013.2286456

Cited By

View all
  • (2024)Multi-Objective Microservice Orchestration: Balancing Security and Performance in CCAM2024 27th Conference on Innovation in Clouds, Internet and Networks (ICIN)10.1109/ICIN60470.2024.10494482(88-90)Online publication date: 11-Mar-2024
  • (2024)Work-in-Progress: A Sidecar Proxy for Usable and Performance-Adaptable End-to-End Protection of Communications in Cloud Native Applications2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)10.1109/EuroSPW61312.2024.00086(706-711)Online publication date: 8-Jul-2024
  • (2024)Secure Cryptography Usage in Software Development: A Systematic Literature Review2024 12th International Conference in Software Engineering Research and Innovation (CONISOFT)10.1109/CONISOFT63288.2024.00036(218-227)Online publication date: 28-Oct-2024

Index Terms

  1. Formal Modelling and Automated Trade-off Analysis of Enforcement Architectures for Cryptographic Access Control in the Cloud

      Recommendations

      Comments

      Please enable JavaScript to view thecomments powered by Disqus.

      Information & Contributors

      Information

      Published In

      cover image ACM Transactions on Privacy and Security
      ACM Transactions on Privacy and Security  Volume 25, Issue 1
      February 2022
      219 pages
      ISSN:2471-2566
      EISSN:2471-2574
      DOI:10.1145/3485162
      Issue’s Table of Contents

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 23 November 2021
      Accepted: 01 July 2021
      Revised: 01 May 2021
      Received: 01 November 2020
      Published in TOPS Volume 25, Issue 1

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. Cryptographic access control
      2. architecture
      3. optimization

      Qualifiers

      • Research-article
      • Refereed

      Funding Sources

      • Integrated Framework for Predictive and Collaborative Security of Financial Infrastructures (FINSEC)
      • European Union’s Horizon 2020 Research
      • National Science Foundation

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)90
      • Downloads (Last 6 weeks)11
      Reflects downloads up to 16 Dec 2024

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)Multi-Objective Microservice Orchestration: Balancing Security and Performance in CCAM2024 27th Conference on Innovation in Clouds, Internet and Networks (ICIN)10.1109/ICIN60470.2024.10494482(88-90)Online publication date: 11-Mar-2024
      • (2024)Work-in-Progress: A Sidecar Proxy for Usable and Performance-Adaptable End-to-End Protection of Communications in Cloud Native Applications2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)10.1109/EuroSPW61312.2024.00086(706-711)Online publication date: 8-Jul-2024
      • (2024)Secure Cryptography Usage in Software Development: A Systematic Literature Review2024 12th International Conference in Software Engineering Research and Innovation (CONISOFT)10.1109/CONISOFT63288.2024.00036(218-227)Online publication date: 28-Oct-2024
      • (2024)Formal Methods and Access ControlEncyclopedia of Cryptography, Security and Privacy10.1007/978-3-642-27739-9_854-2(1-3)Online publication date: 12-May-2024
      • (2023)Credential-Based Access ControlEncyclopedia of Cryptography, Security and Privacy10.1007/978-3-642-27739-9_898-2(1-3)Online publication date: 29-Jul-2023

      View Options

      Login options

      Full Access

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Full Text

      View this article in Full Text.

      Full Text

      HTML Format

      View this article in HTML Format.

      HTML Format

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media