The advance of information technologies has enabled various organizations (e.g., census agencies, hospitals) to collect large volumes of sensitive personal data (e.g., census data, medical records). Due to the great research value of such data, it is often released for public benefit purposes, which, however, poses a risk to individual privacy. A typical solution to this problem is to anonymize the data before releasing it to the public. In particular, the anonymization should be conducted in a careful manner, such that the published data not only prevents an adversary from inferring sensitive information, but also remains useful for data analysis. / This thesis prevents an extensive study on the anonymization techniques for privacy preserving data publishing. We explore various aspects of the problem (e.g., definitions of privacy, modeling of the adversary, methodologies of anonymization), and devise novel solutions that address several important issues overlooked by previous work. Experiments with real-world data confirm the effectiveness and efficiency of our techniques. / Xiao, Xiaokui. / Adviser: Yufei Yao. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3618. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 307-314). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

by Shum Kwan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 30-32). / Abstracts in English and Chinese. / Acknowledgement --- p.ii / Abstract --- p.iii / □ □ --- p.iv / Chapter 1 . --- Introduction --- p.1 / Chapter 1.1 --- Introduction to topic --- p.1 / Chapter 1.2 --- What is proxy signature? --- p.2 / Chapter 1.3 --- Terminologies in proxy signature --- p.2 / Chapter 1.4 --- Levels of delegation --- p.3 / Chapter 1.5 --- Previous work on Proxy Signature --- p.4 / Chapter 1.6 --- Our Contributions --- p.4 / Chapter 1.7 --- Thesis Organization --- p.4 / Chapter 2. --- Backgroun d --- p.6 / Chapter 2.1 --- Digital Signature --- p.6 / Chapter 2.2 --- Digital Certificate and CA --- p.6 / Chapter 2.3 --- Hash Functions --- p.7 / Chapter 2.4 --- Bit commitment --- p.7 / Chapter 3. --- Brief introduction to Our Result --- p.8 / Chapter 3.1 --- A Proxy Signature Scheme with Proxy Signer Privacy Protection --- p.8 / Chapter 3.2 --- Applications of Proxy Signature --- p.9 / Chapter 4. --- Detail Explanation of Certified Alias and its Application on Proxy Signature --- p.10 / Chapter 4.1 --- Introduction --- p.10 / Chapter 4.2 --- Protecting Signer Privacy Using Certified Alias Definition 4.2.3 --- p.10 / Chapter 4.3 --- Constructing Proxy signature Scheme by Consecutive Execution of Cryptographic Primitives (Scheme CE) --- p.11 / Chapter 4.4 --- Constructing Proxy signature Scheme by Direct Form Equations (Scheme DF) --- p.15 / Chapter 4.5 --- Comparison between scheme CE and scheme DF --- p.19 / Chapter 4.6 --- Chapter Summary --- p.20 / Chapter 5 . --- Applications of Proxy Signature with Proxy Signer Privacy Protection --- p.21 / Chapter 5.1 --- Secure Mobile agent Signature with Itinerary Privacy --- p.21 / Chapter 5.1.1 --- Introduction to Mobile Agent --- p.21 / Chapter 5.1.2 --- "Review on Lee, et al. strong non-designated proxy signature scheme for mobile agents" --- p.21 / Chapter 5.1.3 --- Constructing Signature scheme for Mobile Agent using Proxy signature with Proxy Signer Privacy Protection --- p.22 / Chapter 5.1.4 --- Remarks --- p.23 / Chapter 5.2 --- Group Signature with Unlimited Group Size --- p.24 / Chapter 5.2.1 --- Introduction to group signature --- p.24 / Chapter 5.2.2 --- Constructing group signature scheme using certified alias --- p.24 / Chapter 5.2.4 --- Remarks --- p.26 / Chapter 5.3 --- Chapter Summary --- p.27 / Chapter 6. --- Conclusions --- p.28 / Appendix: Paper derived from this thesis --- p.29 / Bibliography --- p.30

Since nearly two decades threats to public security through events such as 9/11, the Madrid (2004) and London (2005) bombings and more recently the Paris attacks (2015) resulted in the adoption of a plethora of national and EU measures aiming at fighting terrorism and serious crime. In addition, the Snowden revelations brought the privacy and data protection implications of these public security measures into the spotlight. In this highly contentious context, three EU data retention and access measures have been introduced for the purpose of fighting serious crime and terrorism: The Data Retention Directive (DRD), the EU-US PNR Agreement and the EU-US SWIFT Agreement. All three regimes went through several revisions (SWIFT, PNR) or have been annulled (DRD) exemplifying the difficulty of determining how privacy and data protection ought to be protected in the context of public security. The trigger for this research is to understand the underlying causes of these difficulties by examining the problem from different angles. The thesis applies the theory of 'New Institutionalism' (NI) which allows both a political and legal analysis of privacy and data protection in the public security context. According to NI, 'institutions' are defined as the operational framework in which actors interact and they steer the behaviours of the latter in the policy-making cycle. By focusing on the three data retention and access regimes, the aim of this thesis is to examine how the EU 'institutional framework' shapes data protection and privacy in regard to data retention and access measures in the public security context. Answering this research question the thesis puts forward three main hypotheses: (i) privacy and data protection in the Area of Freedom, Security and Justice (AFSJ) is an institutional framework in transition where historic and new features determine how Articles 7 and 8 of the Charter of Fundamental Rights of the European Union (CFREU) are shaped; (ii) policy outcomes on Articles 7 and 8 CFREU are influenced by actors' strategic preferences pursued in the legislation-making process; and (iii) privacy and data protection are framed by the evolution of the Court of Justice of the European Union (CJEU) from a 'legal basis arbiter' to a political actor in its own right as a result of the constitutional changes brought by the Lisbon Treaty.

Fung, Siu Yuen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 58-63). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background and Related Work --- p.7 / Chapter 2.1 --- Request Forgery Attacks --- p.7 / Chapter 2.2 --- Current Defense Approaches --- p.10 / Chapter 2.3 --- Lessons Learned --- p.13 / Chapter 3 --- Design of DeRef --- p.15 / Chapter 3.1 --- Threat Model --- p.16 / Chapter 3.2 --- Fine-Grained Access Control --- p.18 / Chapter 3.3 --- Two-Phase Privacy-Preserving Checking --- p.24 / Chapter 3.4 --- Putting It All Together --- p.29 / Chapter 3.5 --- Implementation --- p.33 / Chapter 4 --- Deployment Case Studies --- p.36 / Chapter 4.1 --- WordPress --- p.37 / Chapter 4.2 --- Joomla! and Drupal --- p.42 / Chapter 5 --- Evaluation --- p.44 / Chapter 5.1 --- Performance Overhead of DeRef in Real Deployment --- p.45 / Chapter 5.2 --- Performance Overhead of DeRef with Various Configurations --- p.50 / Chapter 6 --- Conclusions --- p.56 / Bibliography --- p.58

Bu, Yingyi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 89-94). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Anomaly Monitoring --- p.1 / Chapter 1.2 --- Privacy Preservation --- p.5 / Chapter 1.2.1 --- Motivation --- p.7 / Chapter 1.2.2 --- Contribution --- p.12 / Chapter 2 --- Anomaly Monitoring --- p.16 / Chapter 2.1 --- Problem Statement --- p.16 / Chapter 2.2 --- A Preliminary Solution: Simple Pruning --- p.19 / Chapter 2.3 --- Efficient Monitoring by Local Clusters --- p.21 / Chapter 2.3.1 --- Incremental Local Clustering --- p.22 / Chapter 2.3.2 --- Batch Monitoring by Cluster Join --- p.24 / Chapter 2.3.3 --- Cost Analysis and Optimization --- p.28 / Chapter 2.4 --- Piecewise Index and Query Reschedule --- p.31 / Chapter 2.4.1 --- Piecewise VP-trees --- p.32 / Chapter 2.4.2 --- Candidate Rescheduling --- p.35 / Chapter 2.4.3 --- Cost Analysis --- p.36 / Chapter 2.5 --- Upper Bound Lemma: For Dynamic Time Warping Distance --- p.37 / Chapter 2.6 --- Experimental Evaluations --- p.39 / Chapter 2.6.1 --- Effectiveness --- p.40 / Chapter 2.6.2 --- Efficiency --- p.46 / Chapter 2.7 --- Related Work --- p.49 / Chapter 3 --- Privacy Preservation --- p.52 / Chapter 3.1 --- Problem Definition --- p.52 / Chapter 3.2 --- HD-Composition --- p.58 / Chapter 3.2.1 --- Role-based Partition --- p.59 / Chapter 3.2.2 --- Cohort-based Partition --- p.61 / Chapter 3.2.3 --- Privacy Guarantee --- p.70 / Chapter 3.2.4 --- Refinement of HD-composition --- p.75 / Chapter 3.2.5 --- Anonymization Algorithm --- p.76 / Chapter 3.3 --- Experiments --- p.77 / Chapter 3.3.1 --- Failures of Conventional Generalizations --- p.78 / Chapter 3.3.2 --- Evaluations of HD-Composition --- p.79 / Chapter 3.4 --- Related Work --- p.85 / Chapter 4 --- Conclusions --- p.87 / Bibliography --- p.89

Mo, Mingzhen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 111-123). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Thesis Contributions --- p.5 / Chapter 1.3 --- Problem Description --- p.6 / Chapter 1.4 --- Thesis Organization --- p.8 / Chapter 2 --- Background Study --- p.11 / Chapter 2.1 --- Overview --- p.11 / Chapter 2.2 --- Problem Definitions --- p.12 / Chapter 2.3 --- Privacy in Online Social Networks --- p.14 / Chapter 2.4 --- Attack --- p.17 / Chapter 2.4.1 --- Statistical Learning --- p.18 / Chapter 2.4.2 --- Graph Theory --- p.22 / Chapter 2.5 --- Protection --- p.23 / Chapter 2.5.1 --- Clustering-Based Approach --- p.24 / Chapter 2.5.2 --- Modification-Based Approach --- p.27 / Chapter 3 --- Exploit Social Networks with SSL --- p.30 / Chapter 3.1 --- Overview --- p.31 / Chapter 3.2 --- Semi-Supervised Learning Framework --- p.35 / Chapter 3.2.1 --- Co-Training SSL --- p.36 / Chapter 3.2.2 --- Graph-Based SSL --- p.38 / Chapter 3.2.3 --- Local and Global Consistency Graph-Based SSL --- p.39 / Chapter 3.3 --- Experiment --- p.40 / Chapter 3.3.1 --- Dataset Description --- p.41 / Chapter 3.3.2 --- Data Preprocessing --- p.43 / Chapter 3.3.3 --- Experiment Process --- p.45 / Chapter 3.3.4 --- Experiment Results --- p.47 / Chapter 3.4 --- Conclusion --- p.49 / Chapter 4 --- Exploiting Social Networks with CG SSL --- p.50 / Chapter 4.1 --- Overview --- p.51 / Chapter 4.2 --- Exploit Learning Model and Algorithms --- p.56 / Chapter 4.2.1 --- Exploit Learning Model --- p.57 / Chapter 4.2.2 --- Algorithms --- p.60 / Chapter 4.2.3 --- Community Generation --- p.65 / Chapter 4.3 --- Experiment --- p.66 / Chapter 4.3.1 --- Dataset Description --- p.67 / Chapter 4.3.2 --- Data Preprocessing --- p.70 / Chapter 4.3.3 --- Experiment Process --- p.72 / Chapter 4.3.4 --- Experiment Results --- p.77 / Chapter 4.4 --- Conclusion --- p.82 / Chapter 5 --- APA Comparison Scheme --- p.83 / Chapter 5.1 --- Overview --- p.84 / Chapter 5.2 --- Attack-Protect-Attack (APA) Comparisons Scheme --- p.87 / Chapter 5.2.1 --- Algorithm --- p.87 / Chapter 5.2.2 --- Attack & Protection Approaches --- p.88 / Chapter 5.3 --- Experiment --- p.91 / Chapter 5.3.1 --- Dataset Description --- p.92 / Chapter 5.3.2 --- Data Preprocessing --- p.92 / Chapter 5.3.3 --- Experiment Process --- p.94 / Chapter 5.3.4 --- Experiment Result --- p.95 / Chapter 5.4 --- Conclusion --- p.103 / Chapter 6 --- Conclusion and Future Work --- p.105 / Chapter 6.1 --- Conclusion --- p.105 / Chapter 6.2 --- Future Work --- p.107 / Bibliography --- p.111

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thèse (Docteur ès sciences)--Université de Genève, 2002. / Summary in French. "Thèse no 3396." Includes bibliographical references.

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Computer Science." Includes bibliographical references (p. 99-103).

Thesis (M.S.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains x, 112 p. : ill. (some col.). Document provides links to supplementary files in Pro/E, AI0WIN, Step, and Excel. Includes abstract. Includes bibliographical references (p. 110-112).