skip to main content
10.1145/2991561.2991566acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiotConference Proceedingsconference-collections
research-article

Privacy-by-Design Framework for Assessing Internet of Things Applications and Platforms

Published:07 November 2016Publication History

ABSTRACT

The Internet of Things (IoT) systems are designed and developed either as standalone applications from the ground-up or with the help of IoT middleware platforms. They are designed to support different kinds of scenarios, such as smart homes and smart cities. Thus far, privacy concerns have not been explicitly considered by IoT applications and middleware platforms. This is partly due to the lack of systematic methods for designing privacy that can guide the software development process in IoT. In this paper, we propose a set of guidelines, a privacy by-design framework, that can be used to assess privacy capabilities and gaps of existing IoT applications as well as middleware platforms. We have evaluated two open source IoT middleware platforms, namely OpenIoT and Eclipse SmartHome, to demonstrate how our framework can be used in this way.

References

  1. Philip A Bernstein. 1996. Middleware: A Model for Distributed System Services. Commun. ACM 39, 2 (feb 1996), 86--98. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Ljiljana Brankovic and Vladimir Estivill-castro. 1999. Privacy issues in knowledge discovery and data mining. In In Proc. of Australian Institute of Computer Ethics Conference (AICEC99. 89--99.Google ScholarGoogle Scholar
  3. Ann Cavoukian. 2010. Resolution on Privacy by Design. In 32nd International Conference of Data Protection and Privacy Commissioners.Google ScholarGoogle Scholar
  4. Amir Chaudhry, Jon Crowcroft, Heidi Howard, Anil Madhavapeddy, Richard Mortier, Hamed Haddadi, and Derek McAuley. 2015. Personal Data: Thinking Inside the Box. In 5th decennial Aarhus conferences (Aarhus 2015 Critical Alternatives). Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Valentina Ciriani, Sabrina De Capitani Di Vimercati, Sara Foresti, Sushil Jajodia, Stefano Paraboschi, and Pierangela Samarati. 2010. Combining Fragmentation and Encryption to Protect Privacy in Data Storage. ACM Trans. Inf. Syst. Secur. 13, 3 (jul 2010), 22:1----22:33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Chris Clifton, Murat Kantarcio\vglu, AnHai Doan, Gunther Schadow, Jaideep Vaidya, Ahmed Elmagarmid, and Dan Suciu. 2004. Privacy-preserving Data Integration and Sharing. In Proceedings of the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD '04). ACM, New York, NY, USA, 19--26. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. European Commission. 2015. Internet Of Things Iot Governance, Privacy And Security Issues European Research Cluster On The Internet Of Things. Technical Report.Google ScholarGoogle Scholar
  8. Joan Daemen and Vincent Rijmen. 2002. The design of AES- the Advanced Encryption Standard. Spring{\-}er-Ver{\-}lag. 238 pages.Google ScholarGoogle Scholar
  9. George Danezis, Josep Domingo-Ferrer, Marit Hansen, Jaap-Henk Hoepman, Daniel Le Métayer, Rodica Tirtea, and Stefan Schiffner. 2014. Privacy and Data Protection by Design from policy to engineering. Technical Report. European Union Agency for Network and Information Security (ENISA). 1--79 pages.Google ScholarGoogle Scholar
  10. Yves-Alexandre de Montjoye, Erez Shmueli, Samuel S Wang, and Alex Sandy Pentland. 2014. openPDS: Protecting the Privacy of Metadata through SafeAnswers. PLoS ONE 9, 7 (2014), e98790.Google ScholarGoogle ScholarCross RefCross Ref
  11. Mina Deng, Kim Wuyts, Riccardo Scandariato, Bart Preneel, and Wouter Joosen. 2011. A privacy threat analysis framework: supporting the elicitation and fulfillment of privacy requirements. Requirements Engineering 16, 1 (2011), 3--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. C Efthymiou and G Kalogridis. 2010. Smart Grid Privacy via Anonymization of Smart Metering Data. In Smart Grid Communications (SmartGridComm), 2010 First IEEE International Conference on. 238--243.Google ScholarGoogle ScholarCross RefCross Ref
  13. Federal Trade Commission. 2015. Internet of Things: Privacy and Security in a Connected World. Ftc staff report. Federal Trade Commission.Google ScholarGoogle Scholar
  14. Caroline Fontaine and Fabien Galand. 2007. A Survey of Homomorphic Encryption for Nonspecialists. EURASIP J. Inf. Secur. 15 (jan 2007), 1--15.Google ScholarGoogle Scholar
  15. Carl S French. 1996. Data Processing and Information Technology. Cengage Learning Business Press.Google ScholarGoogle Scholar
  16. David Gascon. 2015. IoT Security Infographic Privacy, Authenticity, Confidentiality and Integrity of the Sensor Data. The Invisible Asset. Technical Report. Libelium.Google ScholarGoogle Scholar
  17. Craig Gentry. 2009. Fully Homomorphic Encryption Using Ideal Lattices. In Proceedings of the 41 Annual ACM Symposium on Theory of Computing (STOC '09). ACM, NY, USA, 169--178. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Joao Girao, Dirk Westhoff, Einar Mykletun, and Toshinori Araki. 2007. TinyPEDS: Tiny Persistent Encrypted Data Storage in Asynchronous Wireless Sensor Networks. Ad Hoc Netw. 5, 7 (sep 2007), 1073--1089. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Yuri Gurevich, Efim Hudis, and Jeannette Wing. 2014. Inverse Privacy. Technical Report MSR-TR-2014-100.Google ScholarGoogle Scholar
  20. Jaap-Henk Hoepman. 2014. Privacy Design Strategies. In ICT Systems Security and Privacy Protection, Nora Cuppens-Boulahia, Frédéric Cuppens, Sushil Jajodia, Anas Abou El Kalam, and Thierry Sans (Eds.). IFIP Advances in Information and Communication Technology, Vol. 428. Springer Berlin Heidelberg, 446--459.Google ScholarGoogle Scholar
  21. Michael Howard and Steve Lipner. 2006. The security development lifecycle: SDL, a process for developing demonstrably more secure software. Microsoft Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Prem Prakash Jayaraman, Charith Perera, Dimitrios Georgakopoulos, Schahram Dustdar, Dhavalkumar Thakker, and Rajiv Ranjan. 2016. Analytics-as-a-service in a multi-cloud environment through semantically-enabled hierarchical data processing. Software: Practice and Experience (aug 2016).Google ScholarGoogle Scholar
  23. P Kotzanikolaou. 2008. Data Retention and Privacy in Electronic Communications. Security Privacy, IEEE 6, 5 (sep 2008), 46--52. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Bingdong Li, Esra Erdin, Mehmet Hadi Güne\cs, George Bebis, and Todd Shipley. 2011. Traffic Monitoring and Analysis: Third International Workshop, TMA 2011, Vienna, Austria, April 27, 2011. Proceedings. Springer Berlin Heidelberg, Berlin, Heidelberg, Chapter An Analysi, 108--121.Google ScholarGoogle Scholar
  25. S Lindsey, C Raghavendra, and K M Sivalingam. 2002. Data gathering algorithms in sensor networks using energy metrics. Parallel and Distributed Systems, IEEE Transactions on 13, 9 (sep 2002), 924--935. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. William Lowrance. 2003. Learning from experience: privacy and the secondary use of data in health research. Journal of Health Services Research & Policy 8, suppl 1 (2003), 2--7.Google ScholarGoogle ScholarCross RefCross Ref
  27. Y Ma, Y Guo, X Tian, and M Ghanem. 2011. Distributed Clustering-Based Aggregation Algorithm for Spatial Correlated Sensor Networks. IEEE Sensors Journal 11, 3 (mar 2011), 641--648.Google ScholarGoogle ScholarCross RefCross Ref
  28. Joe Oates, Chuck Kelley, and Les Barbusinski. 2002. What does granularity mean in the context of a data warehouse and what are the various levels of granularity? information-management.com. SourceMedia.Google ScholarGoogle Scholar
  29. Ernesto Damiani; Francesco Pagano; Davide Pagano. 2011. iPrivacy: A Distributed Approach to Privacy on the Cloud. International Journal on Advances in Security 4, 3 (2011).Google ScholarGoogle Scholar
  30. Charith Perera, Chi Harold Liu, and Srimal Jayawardena. 2015a. The Emerging Internet of Things Marketplace from an Industrial Perspective: A Survey. IEEE Transactions on Emerging Topics in Computing 3, 4 (2015), 585--598. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Charith Perera, Rajiv Ranjan, and Lizhe Wang. 2015b. End-to-End Privacy for Open Big Data Markets. IEEE Cloud Computing 2, 4 (jul 2015), 44--53.Google ScholarGoogle ScholarCross RefCross Ref
  32. Charith Perera, Rajiv Ranjan, Lizhe Wang, Samee U. Khan, and Albert Y. Zomaya. 2015c. Big data privacy in the internet of things era. IT Professional 17, 3 (2015), 32--39.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Charith Perera, Dumidu Talagala, Chi Harold Liu, and Julio C. Estrella. 2015d. Energy-Efficient Location and Activity-Aware On-Demand Mobile Distributed Sensing Platform for Sensing as a Service in IoT Clouds. IEEE Transactions on Computational Social Systems 2, 4 (dec 2015), 171--181.Google ScholarGoogle ScholarCross RefCross Ref
  34. Charith Perera, Arkady Zaslavsky, Peter Christen, and Dimitrios Georgakopoulos. 2014. Context Aware Computing for The Internet of Things: A Survey. Communications Surveys Tutorials, IEEE 16, 1 (2014), 414--454.Google ScholarGoogle Scholar
  35. Shauna Michelle Policicchio and Attila A Yavuz. 2015. Preventing Memory Access Pattern Leakage in Searchable Encryption. In iConference 2015 Proceedings. iSchools.Google ScholarGoogle Scholar
  36. Dorian Pyle. 1999. Data preparation for data mining. Morgan Kaufmann Publishers, San Francisco, Calif. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. R Rajagopalan and P K Varshney. 2006. Data-aggregation techniques in sensor networks: A survey. Communications Surveys Tutorials, IEEE 8, 4 (2006), 48--63. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Rodrigo Roman, Jianying Zhou, and Javier Lopez. 2013. On the features and challenges of security and privacy in distributed internet of things. Computer Networks 57, 10 (2013), 2266--2279. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. S. Spiekermann and L.F. Cranor. 2009. Engineering Privacy. IEEE Transactions on Software Engineering 35, 1 (jan 2009), 67--82. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Mark Stanislav and Tod Beardsley. 2015. HACKING IoT: A Case Study on Baby Monitor Exposures and Vulnerabilities. Technical Report. Rapid7.Google ScholarGoogle Scholar
  41. Jun-Zhao Sun. 2009. Adaptive Determination of Data Granularity for QoS-Constraint Data Gathering in Wireless Sensor Networks. In Ubiquitous, Autonomic and Trusted Computing, 2009. UIC-ATC '09. Symposia and Workshops on. 401--405. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. TRUSTe. 2016. Privacy Assessments & Certifications Overview. Datasheets.Google ScholarGoogle Scholar

Index Terms

  1. Privacy-by-Design Framework for Assessing Internet of Things Applications and Platforms

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          IoT '16: Proceedings of the 6th International Conference on the Internet of Things
          November 2016
          186 pages
          ISBN:9781450348140
          DOI:10.1145/2991561

          Copyright © 2016 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 7 November 2016

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article
          • Research
          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate28of84submissions,33%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader