Building Confidential and Efficient Query Services in the Cloud with RASP Data Perturbation

With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a secured query service should still provide efficient query processing and significantly reduce the in-house workload to fully realize the benefits of cloud computing. We propose the RASP data perturbation method to provide secure and efficient range query and kNN query services for protected data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries. It also preserves multidimensional ranges, which allows existing indexing techniques to be applied to speedup range query processing. The kNN-R algorithm is designed to work with the RASP range query algorithm to process the kNN queries. We have carefully analyzed the attacks on data and queries under a precisely defined threat model and realistic security assumptions. Extensive experiments have been conducted to show the advantages of this approach on efficiency and security.Comment: 18 pages, to appear in IEEE TKDE, accepted in December 201

CS 400/600: Data Structures and Software Design

This course will cover the implementation of classical data structures and control structures, an introduction to the fundamentals of algorithm design and analysis, and the basic problem solving techniques

CS 3100/5100: Data Structures and Algorithms

This course will cover the fundamentals of algorithm design and analysis, the implementation of classical data structures and control structures, and the basic problem solving techniques

CS 405/605-02: Introduction to Database Management Systems

This course will cover the following topics: (1) Logical and physical aspects of database management systems (2) Data models including entity-relationship (ER) and relational models (#) Physical implementation (data organization and indexing) methods. (3) Query languages including SQL and relational algebra. (4) High level concepts: transactions, relation normalization, and security and privacy. Students will gain experience in creating and manipulating a database, and gain knowledge on professional and ethical responsibility and on the importance of privacy/security of data

CS 790-01: Privacy-Aware Computing

In this course, we will discuss a set of research papers on various topics of privacy-aware computing: data perturbation, data anonymization, randomized responses, privacy preserving data mining, privacy preserving multivariate statistical analysis, private information retrieval, and secure data outsourcing, etc. Students are expected to read some papers and submit paper summaries. Participation in the class discussion is encouraged. Students will need to finish a course project and give a project presentation. Each project team can have 1~2 people. (4 Hours Lecture)

CS 240: Computer Programming - I

Basic concepts of programming and programming languages are introduced. Emphasis is on problem solving and object oriented programming. This course provides a general introduction to the fundamentals of computer science and programming. Examples from and applications to a broad range of problems are given. No prior knowledge of programming is assumed. The concepts covered will be applied to the Java programming language. Students must register for both lecture and one laboratory section. 4 credit hours

CS 499/699: Cloud Computing

In this course, we will explore a few aspects of cloud computing: distributed data crunching with MapReduce, cloud and datacenter filesystems, virtualization, security&privacy, Amazon Web Services, and interactive web-based applications. Students are expected to finish a few mini projects, read some papers, and take the final exam. Participation in the class discussion is strongly encouraged. Guest speakers might be invited for some particular topics. (3 Hours Lecture+ 1 Hour lab)