Current day database applications, with large numbers of users, require fine-grained access control mechanisms, at the level of individual tuples, not just entire relations/views, to control which parts of the data can be accessed by each user. Fine-grained access control is often enforced in the application code, which has numerous drawbacks; these can be avoided by specifying/enforcing access control at the database level. We present a novel fine-grained access control model based on authorization views that allows "authorizationtransparent" querying; that is, user queries can be phrased in terms of the database relations, and are valid if they can be answered using only the information contained in these authorization views. We extend earlier work on authorization-transparent querying by introducing a new notion of validity, conditional validity. We give a powerful set of inference rules to check for query validity. We demonstrate the practicality of our techniques by describing how an existing query optimizer can be extended to perform access control checks by incorporating these inference rules.

Complex queries are becoming commonplace, with the growing use of decision support systems. These complex queries often have a lot of common sub-expressions, either within a single query, or across multiple such queries run as a batch. Multiquery optimization aims at exploiting common sub-expressions to reduce evaluation cost. Multi-query optimization has hither-to been viewed as impractical, since earlier algorithms were exhaustive, and explore a doubly exponential search space.In this paper we demonstrate that multi-query optimization using heuristics is practical, and provides significant benefits. We propose three cost-based heuristic algorithms: Volcano-SH and Volcano-RU, which are based on simple modifications to the Volcano search strategy, and a greedy heuristic. Our greedy heuristic incorporates novel optimizations that improve efficiency greatly. Our algorithms are designed to be easily added to existing optimizers. We present a performance study comparing the algorithms, using workloads consisting of queries from the TPC-D benchmark. The study shows that our algorithms provide significant benefits over traditional optimization, at a very acceptable overhead in optimization time.

XML has become an important medium for data representation, particularly when that data is exchanged over or browsed on the Internet. As the volume of XML data increases, there is a growing interest in storing XML in relational databases so that the well-developed features of these systems (e.g., concurrency control, crash recovery, query processors) can be re-used. However, given the wide variety of XML applications and the mismatch between XML's nested-tree structure and the flat tuples of the relational model, storing XML documents in relational databases presents interesting challenges.LegoDB is a cost-based XML-to-relational mapping engine that addresses this problem. It explores a space of possible mappings and selects the best mapping for a given application (defined by an XML Schema, XML data statistics, and an XML query workload). LegoDB leverages existing XML and relational technologies: it represents the target application using XML standards and constructs the space of configurations using XML-specific operations, and it uses a traditional relational optimizer to obtain accurate cost estimates of the derived configurations. In this paper, we describe the LegoDB mapping engine and provide experimental results that demonstrate the effectiveness of this approach.

Complex queries are becoming commonplace, with the growing use of decision support systems. These complex queries often have a lot of common sub-expressions, either within a single query, or across multiple such queries run as a batch. Multi-query optimization aims at exploiting common subexpressions to reduce evaluation cost. Multi-query optimization has hither-to been viewed as impractical, since earlier algorithms were exhaustive, and explore a doubly exponential search space.In this paper we demonstrate that multi-query optimization using heuristics is practical, and provides significant benefits. We propose three cost-based heuristic algorithms: Volcano-SH and Volcano-RU, which are based on simple modifications to the Volcano search strategy, and a greedy heuristic. Our greedy heuristic incorporates novel optimizations that improve efficiency greatly. Our algorithms are designed to be easily added to existing optimizers. We present a performance study comparing the algorithms, using workloads consisting of queries from the TPC-D benchmark. The study shows that our algorithms provide significant benefits over traditional optimization, at a very acceptable overhead in optimization time.

Materialized views have been found to be very effective at speeding up queries, and are increasingly being supported by commercial databases and data warehouse systems. However, whereas the amount of data entering a warehouse and the number of materialized views are rapidly increasing, the time window available for maintaining materialized views is shrinking. These trends necessitate efficient techniques for the maintenance of materialized views.In this paper, we show how to find an efficient plan for the maintenance of a set of materialized views, by exploiting common subexpressions between different view maintenance expressions. In particular, we show how to efficiently select (a) expressions and indices that can be effectively shared, by transient materialization; (b) additional expressions and indices for permanent materialization; and (c) the best maintenance plan -incremental or recomputation -for each view. These three decisions are highly interdependent, and the choice of one affects the choice of the others. We develop a framework that cleanly integrates the various choices in a systematic and efficient manner. Our evaluations show that many-fold improvement in view maintenance time can be achieved using our techniques. Our algorithms can also be used to efficiently select materialized views to speed up workloads containing queries and updates.

Sanitization of a document involves removing sensitive information from the document, so that it may be distributed to a broader audience. Such sanitization is needed while declassifying documents involving sensitive or confidential information such as corporate emails, intelligence reports, medical records, etc. In this paper, we present the ERASE framework for performing document sanitization in an automated manner. ERASE can be used to sanitize a document dynamically, so that different users get different views of the same document based on what they are authorized to know. We formalize the problem and present algorithms used in ERASE for finding the appropriate terms to remove from the document. Our preliminary experimental study demonstrates the efficiency and efficacy of the proposed algorithms.

No abstract

The effects of the St. Patrick's Day geomagnetic storms of 2013 and 2015 in the equatorial and low‐latitude regions of both hemispheres in the 100°E longitude sector is investigated and compared with the response in the Indian sector at 77°E. The data from a chain of ionosondes and GPS/Global Navigation Satellite Systems receivers at magnetic conjugate locations in the 100°E sector have been used. The perturbation in the equatorial zonal electric field due to the prompt penetration of the magnetospheric convective under shielded electric field and the over shielding electric field gives rise to rapid fluctuations in the F2 layer parameters. The direction of IMF Bz and disturbance electric field perturbations in the sunset/sunrise period is found to play a crucial role in deciding the extent of prereversal enhancement which in turn affect the irregularity formation (equatorial spread F) in the equatorial region. The northward (southward) IMF Bz in the sunset period inhibited (supported) the irregularity formation in 2015 (2013) in the 100°E sector. Large height increase (hmF2) during sunrise produced short‐duration irregularities during both the storms. The westward disturbance electric field on 18 March inhibited the equatorial ionization anomaly causing negative (positive) storm effect in low latitude (equatorial) region. The negative effect was amplified in low midlatitude by disturbed thermospheric composition which produced severe density/total electron content depletion. The longitudinal and hemispheric asymmetry of storm response is observed and attributed to electrodynamic and thermospheric differences.