Abstract
As network security monitoring grows more sophisticated, there is an increasing need for outsourcing such tasks to third-party analysts. However, organizations are usually reluctant to share their network traces due to privacy concerns over sensitive information, e.g., network and system configuration, which may potentially be exploited for attacks. In cases where data owners are convinced to share their network traces, the data are typically subjected to certain anonymization techniques, e.g., CryptoPAn, which replaces real IP addresses with prefix-preserving pseudonyms. However, most such techniques either are vulnerable to adversaries with prior knowledge about some network flows in the traces or require heavy data sanitization or perturbation, which may result in a significant loss of data utility. In this article, we aim to preserve both privacy and utility through shifting the trade-off from between privacy and utility to between privacy and computational cost. The key idea is for the analysts to generate and analyze multiple anonymized views of the original network traces: Those views are designed to be sufficiently indistinguishable even to adversaries armed with prior knowledge, which preserves the privacy, whereas one of the views will yield true analysis results privately retrieved by the data owner, which preserves the utility. We formally analyze the privacy of our solution and experimentally evaluate it using real network traces provided by a major ISP. The experimental results show that our approach can significantly reduce the level of information leakage (e.g., less than 1% of the information leaked by CryptoPAn) with comparable utility.
- Michalis Foukarakis, Demetres Antoniades, Spiros Antonatos, and Evangelos P. Markatos. 2007. Flexible and high-performance anonymization of NetFlow records using anontool. In Proceedings of the 3rd International Conference on Security and Privacy in Communications Networks and the Workshops (SecureComm’07). IEEE, 33--38.Google Scholar
- David Moore, Ken Keys, Ryan Koga, Edouard Lagache, and K. C. Claffy. 2001. The CoralReef software suite as a tool for system and network administrators. In Proceedings of the 15th USENIX Conference on System Administration (LISA’01). USENIX Association, Berkeley, CA, 133--144.Google Scholar
Digital Library
- Yifan Li, Adam Slagell, Katherine Luo, and William Yurcik. 2005. CANINE: A combined conversion and anonymization tool for processing net flows for security. In Proceedings of Tenth International Conference on Telecommunication Systems.Google Scholar
- Jani Hautakorpi and Gonzalo Camarillo Gonzalez. IP Address Distribution in Middleboxes. U.S. Patent Application No. 12/518,452.Google Scholar
- Meisam Mohammady, Lingyu Wang, Yuan Hong, Habib Louafi, Makan Pourzandi, and Mourad Debbabi. 2018. Preserving both privacy and utility in network trace anonymization. In Proceedings of the ACM SIGSAC Conference on Computer and Communications Security (CCS’18). ACM, New York, NY, 459--474. DOI:https://doi.org/10.1145/3243734.3243809Google Scholar
Digital Library
- Wen Ding, William Yurcik, and Xiaoxin Yin. 2005. Outsourcing internet security: Economic analysis of incentives for managed security service providers. In Proceedings of the International Workshop on Internet and Network Economics. Springer, Berlin, 947--958.Google Scholar
Digital Library
- Daniele Riboni, Antonio Villani, Domenico Vitali, Claudio Bettini, and Luigi V. Mancini. 2012. Obfuscation of sensitive data in network flows. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM’12). IEEE, 2372--2380.Google Scholar
- Jun Xu, Jinliang Fan, Mostafa H. Ammar, and Sue B. Moon. 2002. Prefix-preserving ip address anonymization: Measurement-based security evaluation and a new cryptography-based scheme. In Proceedings of the 10th IEEE International Conference on Network Protocols. IEEE, 280--289.Google Scholar
- T. Brekne, A. Årnes, and A. Øslebø. 2005. Anonymization of ip traffic monitoring data: Attacks on two prefix-preserving anonymization schemes and some proposed remedies. In Proceedings of the International Workshop on Privacy Enhancing Technologies. Springer, Berlin, 179--196.Google Scholar
- Adam J. Slagell, Yifan Li, and Katherine Luo. 2005. Sharing network logs for computer forensics: A new tool for the anonymization of netflow records. In Proceedings of the Workshop of the 1st International Conference on Security and Privacy for Emerging Areas in Communication Networks. IEEE, 37--42.Google Scholar
Cross Ref
- Morris Dworkin. Recommendation for block cipher modes of operation: Methods for format-preserving encryption. NIST Special Publication 800 (2016): 38G.Google Scholar
- Tianqing Zhu, Gang Li, Wanlei Zhou, and S. Yu Philip. 2017. Differentially private data publishing and analysis: A survey. IEEE Trans. Knowl. Data Eng. 29 8 (2017), 1619--1638.Google Scholar
Digital Library
- Tønnes Brekne and André Årnes. 2005. Circumventing IP-address pseudonymization. In Communications and Computer Networks. 43--48.Google Scholar
- Ting-Fang Yen, Xin Huang, Fabian Monrose, and Michael K. Reiter. 2009. Browser fingerprinting from coarse traffic summaries: Techniques and implications. In Proceedings of the International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment. Springer, Berlin, 157--175.Google Scholar
- Martin Burkhart, Daniela Brauckhoff, Martin May, and Elisa Boschi. 2008. The risk-utility tradeoff for IP address truncation. In Proceedings of the 1st ACM workshop on Network data anonymization. ACM, 23--30.Google Scholar
Digital Library
- Ruoming Pang, Mark Allman, Vern Paxson, and Jason Lee. 2006. The devil and packet trace anonymization. SIGCOMM Comput. Commun. Rev. 36, 1 (January 2006), 29--38. DOI:https://doi.org/10.1145/1111322.1111330Google Scholar
Digital Library
- Scott E. Coull, Michael P. Collins, Charles V. Wright, Fabian Monrose, and Michael K. Reiter. 2007. On web browsing privacy in anonymized NetFlows. In Proceedings of the Conference on USENIX Security.Google Scholar
- Wai Kit Wong, David W. Cheung, Edward Hung, Ben Kao, and Nikos Mamoulis. 2007. Security in outsourcing of association rule mining. In Proceedings of the 33rd International Conference on Very Large Data Bases. VLDB Endowment, 111--122.Google Scholar
Digital Library
- Dimitris Koukis, Spyros Antonatos, Demetres Antoniades, Evangelos P. Markatos, and Panagiotis Trimintzios. 2006. A generic anonymization framework for network traffic. In Proceedings of the IEEE International Conference on Communications. IEEE, 5, 2302--2309.Google Scholar
Cross Ref
- Ed Ferrara, Christopher McClean, and Michael Caputo. 2014. The Forrester Wave: Managed security services: North America, q4. Forrester Research.Google Scholar
- Chih-Hua Tai, Philip S. Yu, and Ming-Syan Chen. 2010. k-Support anonymity based on pseudo taxonomy for outsourcing of frequent itemset mining. In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 473--482.Google Scholar
Digital Library
- Greg Minshall. Tcpdpriv. Retrieved from http://ita. ee. lbl. gov/html/contrib/tcpdpriv. html.Google Scholar
- Universita degli Studi di Brescia. 2009. tcpanon. Retrieved from http://netweb.ing.unibs.it/ tools/tcpanon/index.php.Google Scholar
- Yurcik, William, Clay Woolam, Greg Hellings, Latifur Khan, and Bhavani Thuraisingham. 2007. Scrub-tcpdump: A multi-level packet anonymizer demonstrating privacy/analysis tradeoffs. In Proceedings of the 3rd International Conference on Security and Privacy in Communications Networks and the Workshops (SecureComm’07). IEEE, 49--56.Google Scholar
- Peter Haag. 2005. Watch your Flows with NfSen and NFDUMP. In Proceedings of the 50th RIPE Meeting.Google Scholar
- Jelena Mirkovic. 2008. Privacy-safe network trace sharing via secure queries. In Proceedings of the 1st ACM Workshop on Network Data Anonymization (NDA’08). ACM, New York, NY, 3--10. DOI:https://doi.org/10.1145/1456441.1456445Google Scholar
Digital Library
- Niels Van Dijkhuizen and Jeroen Van Der Ham. 2018. A survey of network traffic anonymisation techniques and implementations. ACM Comput. Surv. 51, 3, Article 52 (May 2018), 27 pages. DOI:https://doi.org/10.1145/3182660.Google Scholar
- Matt Roughan. 2006. Public review for the devil and packet trace anonymization. SIGCOMM Comput. Commun. Rev. 36, 1 (Jan. 2006), 27--28. DOI:http://dx.doi.org/10.1145/1111322.1111329Google Scholar
Digital Library
- Adam J. Slagell, Kiran Lakkaraju, and Katherine Luo. 2006. FLAIM: A multi-level anonymization framework for computer and network logs. In Proceedings of the Large Installation System Administration Conference (LISA’06). 3--8.Google Scholar
- Michael Foukarakis, Demetres Antoniades, and Michalis Polychronakis. 2009. Deep packet anonymization. In Proceedings of the 2nd European Workshop on System Security. ACM, 16--21.Google Scholar
Digital Library
- Martin Burkhart, Dominik Schatzmann, Brian Trammell, Elisa Boschi, and Bernhard Plattner. 2010. The role of network trace anonymization under attack. ACM SIGCOMM Comput. Commun. Rev. 40, 1 (2010), 5--11.Google Scholar
Digital Library
- Jeffrey C. Mogul, and Martin Arlitt. 2006. Sc2d: An alternative to trace anonymization. In Proceedings of the SIGCOMM Workshop on Mining Network Data. ACM, 323--328.Google Scholar
Digital Library
- Florian Kerschbaum. 2015. Frequency-hiding order-preserving encryption. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (CCS’15). ACM, New York, NY, 656--667. DOI:https://doi.org/10.1145/2810103.2813629Google Scholar
Digital Library
- Dongxi Liu and Shenlu Wang. 2013. Nonlinear order preserving index for encrypted database query in service cloud environments. Concurr. Comput.: Pract. Exper. 25, 13 (2013), 1967--1984.Google Scholar
Cross Ref
- Prateek Mittal, Vern Paxson, Robin Sommer, and Mark Winterrowd. 2009. Securing mediated trace access using black-box permutation analysis. In Proceedings of the ACM Workshop on Hot Topics in Networks (HotNets’09).Google Scholar
- Frank McSherry and Ratul Mahajan. 2010. Differentially private network trace analysis. In ACM SIGCOMM Computer Communication Review, 40, 4 (2010), 123--134.Google Scholar
Digital Library
- Kato Mivule and Blake Anderson. 2015. A study of usability-aware network trace anonymization. In Proceedings of the Science and Information Conference (SAI’15). IEEE, 1293--1304.Google Scholar
Cross Ref
- Tanjila Farah and Ljiljana Trajković. 2013. Anonym: A tool for anonymization of the Internet traffic. In Proceedings of the IEEE International Conference on Cybernetics (CYBCO’13). IEEE, 261--266.Google Scholar
Cross Ref
- Travis Mayberry, Erik-Oliver Blass, and Agnes Hui Chan. 2014. Efficient private file retrieval by combining ORAM and PIR. In Proceedings of the Network and Distributed System Security Symposium (NDSS’14).Google Scholar
Cross Ref
- Adam J. Slagell, Kiran Lakkaraju, and Katherine Luo. 2006. FLAIM: A multi-level anonymization framework for computer and network logs. In Proceedings of the Large Installation System Administration Conference (LISA’06). 3--8.Google Scholar
- Jun Xu, Jinliang Fan, Mostafa H. Ammar, and Sue B. Moon. 2002. Prefix-preserving ip address anonymization: Measurement-based security evaluation and a new cryptography-based scheme. In Proceedings of the 10th IEEE International Conference on Network Protocols. IEEE, 280--289.Google Scholar
- Xiao Shaun Wang, Yan Huang, T. H. Hubert Chan, Abhi Shelat, and Elaine Shi. 2014. SCORAM: Oblivious RAM for secure computation. In Proceedings of the ACM SIGSAC Conference on Computer and Communications Security. ACM, 191--202.Google Scholar
Digital Library
- William Yurcik, Clay Woolam, Greg Hellings, Latifur Khan, and Bhavani Thuraisingham. 2008. Measuring anonymization privacy/analysis tradeoffs inherent to sharing network data. In Proceedings of the IEEE Network Operations and Management Symposium (NOMS’08). IEEE, 991--994.Google Scholar
Cross Ref
- Shantanu Gattani and Thomas E. Daniels. 2008. Reference models for network data anonymization. In Proceedings of the 1st ACM Workshop on Network Data Anonymization. ACM, 41--48.Google Scholar
- Zach Jorgensen, Ting Yu, and Graham Cormode. 2015. Conservative or liberal? Personalized differential privacy. In Proceedings of the IEEE 31St International Conference on Data Engineering. IEEE, 1023--1034.Google Scholar
Cross Ref
- Ninghui Li, Wahbeh Qardaji, and Dong Su. 2012. On sampling, anonymization, and differential privacy or, k-anonymization meets differential privacy. In Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security (ASIACCS’12). ACM, New York, NY, 32--33.Google Scholar
Digital Library
- Ninghui Li, Wahbeh Qardaji, and Dong Su. 2011. Provably private data anonymization: Or, k-anonymity meets differential privacy. CoRR. abs/1101.2604.Google Scholar
- Ruoming Pang and Vern Paxson. 2003. A high-level programming environment for packet trace anonymization and transformation. In Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM’03). ACM, New York, NY, 339--351. DOI:https://doi.org/10.1145/863955.863994Google Scholar
Digital Library
- Johannes Gehrke, Michael Hay, Edward Lui, and Rafael Pass. 2012. Crowd-blending privacy. In Proceedings of the Annual Cryptology Conference. Springer, Berlin, 479--496.Google Scholar
Digital Library
- Raffael Bild, Klaus A. Kuhn, and Fabian Prasser. 2018. Safepub: A truthful data anonymization algorithm with strong privacy guarantees. Proc. Privacy Enhanc. Technol. 1 (2018), 67--87.Google Scholar
Cross Ref
- Liyue Fan and Hongxia Jin. 2015. A practical framework for privacy-preserving data analytics. In Proceedings of the 24th International Conference on World Wide Web (WWW’15). 311--321. DOI:https://doi.org/10.1145/2736277.2741122Google Scholar
Digital Library
- Jianqing Zhang, Nikita Borisov, and William Yurcik. 2006. Outsourcing security analysis with anonymized logs. In Proceedings of the Securecomm and Workshops. IEEE, 2006, 1--9.Google Scholar
Cross Ref
- Stefan Saroiu, P. Krishna Gummadi, and Steven D. Gribble. 2001. Measurement study of peer-to-peer file sharing systems. In Proceedings of the Conference on Electronic Imaging. International Society for Optics and Photonics, 156--170.Google Scholar
- Benny Chor et al. 1995. Private information retrieval. In Proceedings of the 36th Annual Symposium on Foundations of Computer Science. IEEE, 1995.Google Scholar
- Piotr Biler and Alfred Witkowski. 1990. Problems in mathematical analysis. https://search.ebscohost.com/login.aspx?direct=truescope=sitedb=nlebkdb=nlabkAN=1619203.Google Scholar
- Qianli Zhang and Xing Li. 2006. An IP address anonymization scheme with multiple access levels. In Proceedings of the International Conference on Information Networking. Springer, Berlin, 793--802.Google Scholar
Digital Library
- Bruno F. Ribeiro, Weifeng Chen, Gerome Miklau, and Donald F. Towsley. 2008. Analyzing privacy in enterprise packet trace anonymization. In Proceedings of the Network and Distributed System Security Symposium (NDSS’08).Google Scholar
- Georgios Kellaris, George Kollios, Kobbi Nissim, and Adam O’Neill. 2016. Generic attacks on secure outsourced databases. In Proceedings of the ACM SIGSAC Conference on Computer and Communications Security (CCS’16). ACM, New York, NY, 1329--1340. DOI:https://doi.org/10.1145/2976749.2978386Google Scholar
Digital Library
- F. Betül Durak, Thomas M. DuBuisson, and David Cash. 2016. What else is revealed by order-revealing encryption? In Proceedings of the ACM SIGSAC Conference on Computer and Communications Security (CCS’16). ACM, New York, NY, 1155--1166. DOI:https://doi.org/10.1145/2976749.2978379Google Scholar
Digital Library
- Vincent Bindschaedler, Paul Grubbs, David Cash, Thomas Ristenpart, and Vitaly Shmatikov. 2018. The tao of inference in privacy-protected databases. Proc. VLDB Endow. 11, 11 (July 2018), 1715--1728. DOI:https://doi.org/10.14778/3236187.3236217.Google Scholar
Digital Library
- Paul Grubbs, Marie-Sarah Lacharite, Brice Minaud, Kenneth G. Paterson. 2019. Learning to reconstruct: Statistical learning theory and encrypted database attacks. In Proceedings of the IEEE Symposium on Security and Privacy (S8P’19).Google Scholar
Cross Ref
- Scott E. Coull, Charles V. Wright, Fabian Monrose, Michael P. Collins, and Michael K. Reiter. 2007. Playing Devil’s advocate: Inferring sensitive information from anonymized network traces. In Proceedings of the Network and Distributed System Security Symposium (NDSS’07). 35--47.Google Scholar
- William Yurcik, and Yifan Li. 2005. Internet security visualization case study: Instrumenting a network for NetFlow security visualization tools. In Proceedings of the 21st Annual Computer Security Applications Conference (ACSAC’05).Google Scholar
- S. E. Coull, Monrose, F., Reiter, M. K., and Bailey, M. 2009. The challenges of effectively anonymizing network data. In Proceedings of the Conference For Homeland Security (CATCH’09). IEEE, 230--236.Google Scholar
- Valentin Del Piccolo et al. 2016. A survey of network isolation solutions for multi-tenant data centers. IEEE Commun. Surveys Tutor. 18, 4 (2016), 2787--2821.Google Scholar
Digital Library
- Cynthia Dwork. 2011. Differential privacy. Encyclopedia of Cryptography and Security (2011), 338--340.Google Scholar
- Cynthia Dwork. 2008. Differential privacy: A survey of results. In Proceedings of the International Conference on Theory and Applications of Models of Computation. Springer, Berlin, 1--19.Google Scholar
Cross Ref
- Eyal Kushilevitz and Rafail Ostrovsky. 1997. Replication is not needed: Single database, computationally-private information retrieval. In Proceedings of the 38th Annual Symposium on Foundations of Computer Science. IEEE, 364--373.Google Scholar
Cross Ref
- Oded Goldreich and Rafail Ostrovsky. 1996. Software protection and simulation on oblivious RAMs. J. ACM 43, 3 (May 1996), 431--473. DOI:http://dx.doi.org/10.1145/233551.233553Google Scholar
Digital Library
- Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. 2006. Calibrating noise to sensitivity in private data analysis. In Proceedings of the Theory of Cryptography Conference. Springer, Berlin, 265--284.Google Scholar
Digital Library
- Andrew Chi-Chih Yao. 1986. How to generate and exchange secrets. In Proceedings of the 27th Annual Symposium on Foundations of Computer Science. IEEE, 162--167.Google Scholar
- Oded Goldreich. 1999. Secure multi-party computation. In Available at Theory of Cryptography Library. http://philby.ucsb.edu/cryptolib/BOOKS.Google Scholar
- Thomas H. Cormen et al. 2001. Data structures for disjoint sets. Introduction to Algorithms (2nd Edition). The MIT Press.Google Scholar
- Robert Sedgewick. 1978. Implementing quicksort programs. Commun. ACM 21, 10 (1978), 847--857.Google Scholar
Digital Library
- Adam Slagell, Jun Wang, and William Yurcik. 2004. Network log anonymization: Application of Crypto-PAn to Cisco netflows. In Proceedings of the Workshop on Secure Knowledge Management.Google Scholar
- Minshall G. TCPdpriv command manual. 1996. Retrieved from http://ita.ee.lbl.gov/html/contrib/tcpdpriv.0.txt.Google Scholar
- Ruma R. Paul, Victor C. Valgenti, and Min Sik Kim. 2011. Real-time Netshuffle: Graph distortion for on-line anonymization. In Proceedings of the 19th IEEE International Conference on Network Protocols (ICNP’11). IEEE, 133--134.Google Scholar
Digital Library
- Gagan Aggarwal, Tomás Feder, Krishnaram Kenthapadi, Samir Khuller, Rina Panigrahy, Dilys Thomas, and An Zhu. 2006. Achieving anonymity via clustering. In Proceedings of the 25th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems. ACM, 153--162.Google Scholar
Digital Library
- Martin Burkhart, Mario Strasser, Dilip Many, and Xenofontas Dimitropoulos. 2010. SEPIA: Privacy-preserving aggregation of multi-domain network events and statistics. In Proceedings of USENIX Security Symposium.Google Scholar
- Alexandra Boldyreva, Nathan Chenette, Younho Lee, and Adam O’neill. 2009. Order-preserving symmetric encryption. In Proceedings of the Annual International Conference on the Theory and Applications of Cryptographic Techniques. Springer, Berlin, 224--241.Google Scholar
Cross Ref
- Reza Curtmola, Juan Garay, Seny Kamara, and Rafail Ostrovsky. 2011. Searchable symmetric encryption: Improved definitions and efficient constructions. J. Comput. Secur. 19 5 (2011), 895--934.Google Scholar
- Dawn Xiaoding Song, David Wagner, and Adrian Perrig. 2000. Practical techniques for searches on encrypted data. In Proceedings of the IEEE Symposium on Security and Privacy (S8P’00). IEEE, 44--55.Google Scholar
Digital Library
- Craig Gentry. 2009. Fully homomorphic encryption using ideal lattices. In Proceedings of the 41st Annual ACM Symposium on Theory of Computing (STOC’09). ACM, New York, NY, 169--178.Google Scholar
Digital Library
- Dan Boneh, Amit Sahai, and Brent Waters. 2011. Functional encryption: Definitions and challenges. In Proceedings of the Theory of Cryptography Conference. Springer, Berlin, 253--273.Google Scholar
Cross Ref
- Mihir Bellare, Alexandra Boldyreva, and Adam O’Neill. 2007. Deterministic and efficiently searchable encryption. In Proceedings of the Annual International Cryptology Conference. Springer, Berlin, 535--552.Google Scholar
Cross Ref
- Alexandra Boldyreva, Nathan Chenette, Younho Lee, and Adam O’neill. 2009. Order-preserving symmetric encryption. In Proceedings of the Annual International Conference on the Theory and Applications of Cryptographic Techniques. Springer, Berlin, 224--241.Google Scholar
Cross Ref
- Mohammad Saiful Islam, Mehmet Kuzu, and Murat Kantarcioglu. 2012. Access pattern disclosure on searchable encryption: Ramification, attack and mitigation. In Proceedings of the Network and Distributed System Security Symposium (NDSS’12), 20.Google Scholar
- Muhammad Naveed, Seny Kamara, and Charles V. Wright. 2015. Inference attacks on property-preserving encrypted databases. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security. ACM, 644--655.Google Scholar
- Zhao Chang, Dong Xie, and Feifei Li. 2016. Oblivious ram: A dissection and experimental evaluation. Proc. VLDB Endow. 9 12 (2016), 1113--1124.Google Scholar
Digital Library
- Brian Caswell and Jay Beale. 2004. Snort 2.1 Intrusion Detection. Elsevier.Google Scholar
- E. Stefanov, M. Van Dijk, E. Shi, C. Fletcher, L. Ren, X. Yu, and S. Devadas. 2013. Path ORAM: an extremely simple oblivious RAM protocol. In Proceedings of the 20th ACM SIGSAC Conference on Computer and Communications Security (CCS’13). ACM, 299--310.Google Scholar
- Justin King, Kiran Lakkaraju, and Adam Slagell. 2009. A taxonomy and adversarial model for attacks against network log anonymization. In Proceedings of the ACM Symposium on Applied Computing (SAC’09). ACM, New York, NY, 1286--1293. DOI:https://doi.org/10.1145/1529282.1529572Google Scholar
Digital Library
Index Terms
A Multi-view Approach to Preserve Privacy and Utility in Network Trace Anonymization
Recommendations
Preserving Both Privacy and Utility in Network Trace Anonymization
CCS '18: Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications SecurityAs network security monitoring grows more sophisticated, there is an increasing need for outsourcing such tasks to third-party analysts. However, organizations are usually reluctant to share their network traces due to privacy concerns over sensitive ...
Preserving Utility in Social Network Graph Anonymization
TRUSTCOM '13: Proceedings of the 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and CommunicationsTo protect from privacy disclosure, the social network graph is modified in order to hide the information that potentially be used to disclose person's identity. However, when the social network graph is changed, it is a great challenge to balance ...
An Anonymization Method Based on Tradeoff between Utility and Privacy for Data Publishing
ICMECG '12: Proceedings of the 2012 International Conference on Management of e-Commerce and e-GovernmentPrivacy preserving is an important issue in data publishing. Many anonymization algorithms are available in meeting the privacy requirements of the privacy models such as k-anonymity, l-diversity and t-closeness. In this paper, we discuss the ...






Comments