Data access

About: Data access is a research topic. Over the lifetime, 13141 publications have been published within this topic receiving 172859 citations. The topic is also known as: Data access.

Disclosure Detection in Multivariate Categorical Databases: Auditing Confidentiality Protection Through Two New Matrix Operators

Abstract: As databases grow more prevalent and comprehensive, database administrators seek to limit disclosure of confidential information while still providing access to data. Practical databases accommodate users with heterogeneous needs for access. Each class of data user is accorded access to only certain views. Other views are considered confidential, and hence to be protected. Using illustrations from health care and education, this article addresses inferential disclosure of confidential views in multidimensional categorical databases. It demonstrates that any structural, so data-value-independent method for detecting disclosure can fail. Consistent with previous work for two-way tables, it presents a data-value-dependent method to obtain tight lower and upper bounds for confidential data values. For two-dimensional projections of categorical databases, it exploits the network structure of a linear programming (LP) formulation to develop two transportation flow algorithms that are both computationally efficient and insightful. These algorithms can be easily implemented through two new matrix operators, cell-maxima and cell-minima. Collectively, this method is called matrix comparative assignment (MCA). Finally, it extends both the LP and MCA approaches to inferential disclosure when accessible views have been masked.

Data structure for access control

Abstract: Data structures for use in controlling access to data objects by users of a computer system or computing device are described. The data structures include an access control group data structure, a user access data structure, and a data object access data structure. The access control group data structure stores access control group data. The user access data structure stores user access data. The user access data relates to at least one entry in the access control group data structure. The data object access data structure stores data object access data, which relates to at least one entry in the access control group. Additional data structures described include an access control rule data structure and a characteristic method data structure.

Data prefetching for high-performance processors

Abstract: Recent technological advances are such that the gap between processor cycle times and memory cycle times is growing. Techniques to reduce or tolerate large memory latencies become essential for achieving high processor utilization. In this dissertation, we propose and evaluate data prefetching techniques that address the data access penalty problems. First, we propose a hardware-based data prefetching approach for reducing memory latency. The basic idea of the prefetching scheme is to keep track of data access patterns in a reference prediction table (RPT) organized as an instruction cache. It includes three variations of the design of the RPT and associated logic: generic design, a lookahead mechanism, and a correlated scheme. They differ mostly on the timing of the prefetching. We evaluate the three schemes by simulating them in a uniprocessor environment using the ten SPEC benchmarks. The results show that the prefetching scheme effectively eliminates a major portion of data access penalty and is particularly suitable to an on-chip design and a primary-secondary cache hierarchy. Next, we study and compare the substantive performance gains that could be achieved with hardware-controlled and software-directed prefetching on shared-memory multiprocessors. Simulation results indicate that both hardware and software schemes can handle programs with regular access patterns. The hardware scheme is good at manipulating dynamic information, whereas software prefetching has the flexibility of prefetching larger blocks of data and of dealing with complex data access patterns. The execution overhead of the additional prefetching instructions may decrease the software prefetching performance gains. An approach that combines software and hardware schemes is shown to be very promising for reducing the memory latency with the least overhead. Finally, we study non-blocking caches that can tolerate read and write miss penalties by exploiting the overlap between post-miss computations and data accesses. We show that hardware data prefetching caches generally outperform non-blocking caches. We derive a static instruction scheduling algorithm to order instructions at compile time. The algorithm is shown to be effective in exploiting instruction parallelism available in a basic block for non-blocking loads.