Security and privacy controls for streaming data in extended intelligent environments

Journal of Ambient Intelligence and Smart Environments

Volumn 8, Issue 4, 2016, Pages 467-483

  Preuveneers, Davy ^a   Joosen, Wouter ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Access control; intelligent environment; privacy; streaming data

Indexed keywords

ACCESS CONTROL; AUTOMATION; BIG DATA; DATA HANDLING; INTELLIGENT AGENTS; INTELLIGENT BUILDINGS; INTERNET OF THINGS; LAWS AND LEGISLATION; SECURITY OF DATA;

ACCEPTABLE PERFORMANCE; DATA PROTECTION SAFEGUARD; GENERAL DATA PROTECTION REGULATIONS; INTELLIGENT ENVIRONMENT; INTERNET OF THING (IOT); PROCESSING CAPABILITY; SENSITIVE INFORMATIONS; STREAMING DATA;

DATA PRIVACY;

EID: 84979519849     PISSN: 18761364     EISSN: None     Source Type: Journal    
DOI: 10.3233/AIS-160384     Document Type: Article

References (61)

1. T. Akidau, A. Balikov, K. Bekiroglu, S. Chernyak, J. Haberman, R. Lax, S. McVeety, D. Mills, P. Nordstrom and S. Whittle, MillWheel: Fault-tolerant stream processing at Internet scale, Very Large Data Bases (2013), 734-746
2. L. Atzori, A. Iera and G. Morabito, The Internet of Things: A survey, Comput. Netw. 54(15) (October 2010), 2787-2805. doi:10.1016/j.comnet.2010.05.010
3. M. Barlow, Real-time big data analytics: Emerging architecture, Technical report, O'Reilly, June 2013
4. A. Barth, A. Datta, J.C. Mitchell and H. Nissenbaum, Privacy and contextual integrity: Framework and applications, in: Proc. of the 2006 IEEE Symposium on Security and Privacy, SP '06, IEEE Computer Society,Washington, DC, USA, 2006, pp. 184-198
5. P. Belsis and G. Pantziou, A k-anonymity privacy-preserving approach in wireless medical monitoring environments, Personal Ubiquitous Comput. 18(1) (January 2014), 61-74. doi: 10.1007/s00779-012-0618-y
6. P. Bogetoft, D.L. Christensen, I. Damgîrd, M. Geisler, T. Jakobsen, M. Krøigaard, J.D. Nielsen, J.B. Nielsen, K. Nielsen, J. Pagter, M. Schwartzbach and T. Toft, Secure multiparty computation goes live, in: Financial Cryptography and Data Security, Springer-Verlag, Berlin, Heidelberg, 2009, pp. 325-343
7. K. Borcea-Pfitzmann, A. Pfitzmann and M. Berg, Privacy 3.0: = data minimization + user control + contextual integrity (privatheit 3.0: = datenminimierung + nutzerkontrolle + kontextuelle integrität), it-Information Technology 53(1) (2011), 34-40
8. F. Buccafurri and G. Lax, An efficient k-anonymous localization technique for assistive environments, in: Proc. of the 2nd International Conference on Pervasive Technologies Related to Assistive Environments, PETRA '09, ACM, New York, NY, USA, 2009, pp. 2:1-2:8
9. L. Carafoli, F. Mandreoli and R. Martoglia, Advanced data management for real-time data intensive applications and services, Journal of Ambient Intelligence and Smart Environments 6(6) (November 2014), 741-742
10. B. Carminati, E. Ferrari, J. Cao and K.-L. Tan, A framework to enforce access control over data streams, ACM Trans. Inf. Syst. Secur. 13(3) (2010). doi:10.1145/1805974.1805984
11. A. Cavoukian, Privacy by Design. The 7 Foundational Principles, 2009
12. G. Cugola and A. Margara, Processing flows of information: From data stream to complex event processing, ACM Comput. Surv. 44(3) (June 2012), 15:1-15:62. doi:10.1145/ 2187671.2187677
13. N. Damianou, N. Dulay, E. Lupu and M. Sloman, The ponder policy specification language, in: Proc. of the International Workshop on Policies for Distributed Systems and Networks, POLICY '01, Springer-Verlag, London, UK, 2001, pp. 18-38. doi:10.1007/3-540-44569-2-2
14. J. Dean and S. Ghemawat, MapReduce: Simplified data processing on large clusters, Commun. ACM51(1) (January 2008), 107-113. doi:10.1145/1327452.1327492
15. C. Dwork, Differential privacy: A survey of results, in: Proc. of the 5th International Conference on Theory and Applications of Models of Computation, TAMC'08, Springer-Verlag, Berlin, Heidelberg, 2008, pp. 1-19. doi:10.1007/978-3-540-79228-4-1
16. A. Friedman and A. Schuster, Data mining with differential privacy, in: Proc. of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '10, ACM, New York, NY, USA, 2010, pp. 493-502
17. C. Gentry, A fully homomorphic encryption scheme, PhD thesis, Stanford, CA, USA, 2009, AAI3382729
18. I. Goldberg, Privacy enhancing technologies for the Internet III: Ten years later, in: Digital Privacy: Theory, Technologies and Practices, A. Acquisti, S. Gritzalis, C. Lambrinoudakis and S. De Capitani di Vimercati, eds, Auerbach Publications, New York, London, 2007, pp. 3-18. doi:10.1201/9781420052183.ch1
19. J. Gubbi, R. Buyya, S. Marusic and M. Palaniswami, Internet of Things (IoT): A vision, architectural elements, and future directions, Future Gener. Comput. Syst. 29(7) (September 2013), 1645-1660. doi:10.1016/j.future.2013.01.010
20. S. Gürses, C. Troncoso and C. Diaz, Engineering privacy by design, in: Conference on Computers, Privacy & Data Protection, 25-28 January 2011, January 2011
21. M. Jawurek, M. Johns and K. Rieck, Smart metering depseudonymization, in: Proc. of the 27th Annual Computer Security Applications Conference, ACSAC '11, ACM,NewYork, NY, USA, 2011, pp. 227-236
22. X. Jin, R. Krishnan and R. Sandhu, A unified attribute-based access control model covering DAC, MAC and RBAC, in: Proc. of the 26th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec'12, Springer-Verlag, Berlin, Heidelberg, 2012, pp. 41-55
23. S. Kandala, R. Sandhu and V. Bhamidipati, An attribute based framework for risk-adaptive access control models, in: 2011 Sixth International Conference on Availability, Reliability and Security (ARES), Aug. 2011, pp. 236-241. doi:10.1109/ARES.2011.41
24. M. Langheinrich, Privacy by design-Principles of privacyaware ubiquitous systems, in: Proc. of the 3rd International Conference on Ubiquitous Computing, UbiComp '01, Springer-Verlag, London, UK, 2001, pp. 273-291
25. E.A. Lee, Cyber physical systems: Design challenges, in: Proc. of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing, ISORC '08, IEEE Computer Society, Washington, DC, USA, 2008, pp. 363-369. doi:10.1109/ISORC.2008.25
26. J. Leibiusky, G. Eisbruch and D. Simonassi, Getting Started with Storm-Continuous Streaming Computation with Twitter's Cluster Technology, O'Reilly, 2012
27. N. Li, T. Li and S. Venkatasubramanian, t-Closeness: Privacy beyond k-anonymity and l-diversity, in: 23rd International Conference on Data Engineering (ICDE 2007), IEEE, 2007, pp. 106-115. doi:10.1109/ICDE.2007.367856
28. A. Machanavajjhala and J.P. Reiter, Big privacy: Protecting confidentiality in big data, XRDS 19(1) (September 2012), 20-23. doi:10.1145/2331042.2331051
29. R.V. Nehme, H.-S. Lim and E. Bertino, Fence: Continuous access control enforcement in dynamic data stream environments, in: Proc. of the Third ACM Conference on Data and Application Security and Privacy, CODASPY '13, ACM, New York, NY, USA, 2013, pp. 243-254
30. L. Neumeyer, B. Robbins, A. Nair and A. Kesari, S4: Distributed stream computing platform, in: Proc. of the 2010 IEEE International Conference on Data Mining Workshops, ICDMW '10, Washington, DC, USA, 2010, pp. 170-177. doi:10.1109/ICDMW.2010.172
31. Q. Ni, E. Bertino and J. Lobo, Risk-based access control systems built on fuzzy inferences, in: Proc. of the 5th ACM Symposium on Information, Computer and Communications Security, ASIACCS '10, ACM, New York, NY, USA, 2010, pp. 250-260
32. F. Prasser and F. Kohlmayer, Putting statistical disclosure control into practice: The ARX data anonymization tool, in: Medical Data Privacy Handbook, Springer International Publishing, Cham, 2015, pp. 111-148
33. D. Preuveneers and Y. Berbers, Prime numbers considered useful: Ontology encoding for efficient subsumption testing, CW Reports CW464, Department of Computer Science, K.U. Leuven, Leuven, Belgium, October 2006
34. D. Preuveneers and Y. Berbers, Encoding semantic awareness in resource-constrained devices, IEEE Intelligent Systems 23(2) (2008), 26-33. doi:10.1109/MIS.2008.25
35. D. Preuveneers and Y. Berbers, SAMURAI: A streaming multi-tenant context-management architecture for intelligent and scalable Internet of things applications, in: 2014 International Conference on Intelligent Environments, Shanghai, China, June 30-July 4, 2014, IEEE, 2014, pp. 226-233
36. D. Preuveneers, Y. Berbers and W. Joosen, SAMURAI: A batch and streaming context architecture for large-scale intelligent applications and environments, Journal of Ambient Intelligence and Smart Environments 8(1) (2016), 63-78. doi:10.3233/AIS-150357
37. D. Preuveneers and W. Joosen, SparkXS: Efficient access control for intelligent and large-scale streaming data applications, in: 2015 International Conference on Intelligent Environments (IE), July 2015, pp. 96-103. doi:10.1109/IE.2015.21
38. D. Preuveneers and W. Joosen, Privacy-enabled remote health monitoring applications for resource constrained wearable devices, in: Proc. of the 31st Annual ACM Symposium on Applied Computing, Vol. 1, ACM, April 2016, pp. 119-124. doi:10.1145/2851613.2851683
39. D. Preuveneers, S.N.Z. Naqvi, A. Ramakrishnan, Y. Berbers and W. Joosen, Adaptive dissemination for mobile electronic health record applications with proactive situational awareness, in: HICSS 49, Vol. 49, CPS: IEEE Computer Society Conference Publishing Services, January 2016, pp. 3229-3238
40. R.R. Rajkumar, I. Lee, L. Sha and J. Stankovic, Cyber-physical systems: The next computing revolution, in: Proc. of the 47th Design Automation Conference, DAC '10, ACM, New York, NY, USA, 2010, pp. 731-736
41. A.K. Ramakrishnan, D. Preuveneers and Y. Berbers, A loosely coupled and distributed Bayesian framework for multi-context recognition in dynamic ubiquitous environments, in: Ubiquitous Intelligence and Computing, 2013 IEEE 10th International Conference on and 10th International Conference on Autonomic and Trusted Computing (UIC/ATC), Dec. 2013, pp. 270-277
42. O. Sacco and J.G. Breslin, PPO & PPM 2.0: Extending the privacy preference framework to provide finer-grained access control for the web of data, in: Proc. of the 8th International Conference on Semantic Systems, I-SEMANTICS '12, ACM, New York, NY, USA, 2012, pp. 80-87
43. O. Sacco and A. Passant, A privacy preference ontology (PPO) for linked data, in: WWW2011 Workshop on Linked Data on the Web, C. Bizer, T. Heath, T. Berners-Lee and M. Hausenblas, eds, Hyderabad, India, March 29, 2011, CEURWorkshop Proceedings, Vol. 813, CEUR-WS.org, 2011
44. R.S. Sandhu, Lattice-based access control models, Computer 26(11) (November 1993), 9-19. doi:10.1109/2.241422
45. R.S. Sandhu, E.J. Coyne, H.L. Feinstein and C.E. Youman, Role-based access control models, Computer 29(2) (February 1996), 38-47. doi:10.1109/2.485845
46. R. Sandhu and P. Samarati, Access control: Principle and practice, IEEE Communications Magazine 32(9) (Sept. 1994), 40-48. doi:10.1109/35.312842
47. B. Schilling, B. Koldehofe, K. Rotherme and U. Ramachandran, Access policy consolidation for event processing systems, in: Proc. of the 2013 Conference on Networked Systems, NETSYS '13, IEEE Computer Society, Washington, DC, USA, 2013, pp. 92-101. doi:10.1109/NetSys.2013.18
48. M. Stonebraker, U. Cetintemel and S. Zdonik, The 8 requirements of real-time stream processing, ACM SIGMOD Record 34(4) (December 2005), 42-47. doi:10.1145/1107499. 1107504
49. J. Suomalainen and J. Julku, Enhancing privacy of information brokering in smart districts by adaptive pseudonymization, IEEE Access 4 (2016), 914-927. doi:10.1109/ACCESS. 2016.2538818
50. L. Sweeney, Achieving k-anonymity privacy protection using generalization and suppression, Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 10(5) (October 2002), 571-588. doi: 10.1142/S021848850200165X
51. L. Sweeney, K-anonymity: A model for protecting privacy, Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 10(5) (October 2002), 557-570. doi:10.1142/S0218488502001648
52. H.T. Tavani and J.H. Moor, Privacy protection, control of information, and privacy-enhancing technologies, SIGCAS Comput. Soc. 31(1) (March 2001), 6-11. doi:10.1145/572277. 572278
53. G. Tonti, J.M. Bradshaw, R. Jeffers, R. Montanari, N. Suri and A. Uszok, Semantic web languages for policy representation and reasoning: A comparison of KAoS, Rei, and Ponder, in: International Semantic Web Conference, D. Fensel, K.P. Sycara and J. Mylopoulos, eds, Lecture Notes in Computer Science, Vol. 2870, Springer, 2003, pp. 419-437
54. T. White, Hadoop: The Definitive Guide, O'Reilly Media, Inc., 1st edn, 2009
55. K. Wuyts, R. Scandariato and W. Joosen, Empirical evaluation of a privacy-focused threat modeling methodology, Journal of Systems and Software 96 (2014), 122-138. doi:10.1016/ j.jss.2014.05.075
56. XACML-V3.0, eXtensible Access Control Markup Language (XACML) Version 3.0. Candidate OASIS Standard 01, http://docs.oasis-open.org/xacml/3.0/xacml-3.0-core-speccos01-en.html, September 2012
57. Y. Xiao and L. Xiong, Protecting locations with differential privacy under temporal correlations, in: Proc. of the 22nd ACM SIGSAC Conference on Computer and Communications Security, CCS '15, ACM, New York, NY, USA, 2015, pp. 1298-1309
58. M. Zaharia, M. Chowdhury, M.J. Franklin, S. Shenker and I. Stoica, Spark: Cluster computing with working sets, in: Proc. of the 2nd USENIX Conference on Hot Topics in Cloud Computing, HotCloud'10, USENIX Association, Berkeley, CA, USA, 2010
59. M. Zaharia, T. Das, H. Li, T. Hunter, S. Shenker and I. Stoica, Discretized streams: Fault-tolerant streaming computation at scale, in: ACMSIGOPS 24th Symposium on Operating Systems Principles, SOSP '13, Farmington, PA, USA, November 3-6, 2013, M. Kaminsky and M. Dahlin, eds, ACM, 2013, pp. 423-438
60. Y. Zheng, T-drive trajectory data sample, http://research. microsoft.com/apps/pubs/default.aspx?id=152883, August 2011
61. Y. Zheng, L. Capra, O. Wolfson and H. Yang, Urban computing: Concepts, methodologies, and applications, ACM Transaction on Intelligent Systems and Technology (2014).