Efficient access control labeling scheme for secure XML query processing

We propose an efficient access control labeling scheme for secure query processing under dynamic Extensible Markup Language (XML) data streams. In recent years, XML has become an active research area. In particular, the needs for an efficient and secure query processing method for dynamic XML data in a ubiquitous data stream environment has become very important. The proposed access control labeling scheme supports the efficient processing of dynamic XML data, eliminating the need for re-labeling and secure query processing. Our proposal has the advantage of having an adaptable access control scheme for an existing XML labeling method.     

A practical mandatory access control model for XML databases

A practical mandatory access control (MAC) model for XML databases is presented in this paper. The label type and label access policy can be defined according to the requirements of different applications. In order to preserve the integrity of data in XML databases, a constraint between a read-access rule and a write-access rule in label access policy is introduced. Rules for label assignment and propagation are presented to alleviate the workload of label assignments. Furthermore, a solution for resolving conflicts in label assignments is proposed. Rules for update-related operations, rules for exceptional privileges of ordinary users and the administrator are also proposed to preserve the security of operations in XML databases. The MAC model, we proposed in this study, has been implemented in an XML database. Test results demonstrated that our approach provides rational and scalable performance.     

Secure query processing against encrypted XML data using Query-Aware Decryption

Dissemination of XML data on the internet could breach the privacy of data providers unless access to the disseminated XML data is carefully controlled. Recently, the methods using encryption have been proposed for such access control. However, in these methods, the performance of processing queries has not been addressed. A query processor cannot identify the contents of encrypted XML data unless the data are decrypted. This limitation incurs overhead of decrypting the parts of the XML data that would not contribute to the query result. In this paper, we propose the notion of Query-Aware Decryption for efficient processing of queries against encrypted XML data. Query-Aware Decryption allows us to decrypt only those parts that would contribute to the query result. For this purpose, we disseminate an encrypted XML index along with the encrypted XML data. This index, when decrypted, informs us where the query results are located in the encrypted XML data, thus preventing unnecessary decryption for other parts of the data. Since the size of this index is much smaller than that of the encrypted XML data, the cost of decrypting this index is negligible compared with that for unnecessary decryption of the data itself. The experimental results show that our method improves the performance of query processing by up to six times compared with those of existing methods. Finally, we formally prove that dissemination of the encrypted XML index does not compromise security.     

An efficient XML encoding and labeling method for query processing and updating on dynamic XML data

In this paper, we propose an efficient encoding and labeling scheme for XML, called EXEL, which is a variant of the region labeling scheme using ordinal and insert-friendly bit strings. We devise a binary encoding method to generate the ordinal bit strings, and an algorithm to make a new bit string inserted between bit strings without any influences on the order of preexisting bit strings. These binary encoding method and bit string insertion algorithm are the bases of the efficient query processing and the complete avoidance of re-labeling for updates. We present query processing and update processing methods based on EXEL. In addition, the Stack-Tree-Desc algorithm is used for an efficient structural join, and the String B-tree indexing is utilized to improve the join performance. Finally, the experimental results show that EXEL enables complete avoidance of re-labeling for updates while providing fairly reasonable query processing performance.     

Efficient recursive XML query processing using relational database systems

Recursive queries are quite important in the context of XML databases. In addition, several recent papers have investigated a relational approach to store XML data and there is growing evidence that schema-conscious approaches are a better option than schema-oblivious techniques as far as query performance is concerned. However, the issue of recursive XML queries for such approaches has not been dealt with satisfactorily. In this paper we argue that it is possible to design a schema-oblivious approach that outperforms schema-conscious approaches for certain types of recursive queries. To that end, we propose a novel schema-oblivious approach, called Sucxent++ (Schema Unconcious XML Enabled System), that outperforms existing schema-oblivious approaches such as XParent by up to 15 times and schema-conscious approaches (Shared-Inlining) by up to eight times for recursive query execution. Our approach has up to two times smaller storage requirements compared to existing schema-oblivious approaches and 10% less than schema-conscious techniques. In addition Sucxent++ performs marginally better than Shared-Inlining and is 5.7–47 times faster than XParent as far as insertion time is concerned.     

Extending path summary and region encoding for efficient structural query processing in native XML databases

Optimizing query processing is always a challenging task in the XML database community. Current state-of-the-art approaches focus mainly on simple query. Yet, as the usage of XML shifts towards the data-oriented paradigm, more and more complex query processing needs to be supported. In this paper, we present TwigX-Guide, a hybrid system, which takes advantage of the beautiful features of path summary in DataGuide and region encoding in TwigStack to improve complex query processing. Experimental results indicate that TwigX-Guide can process complex queries on an average 38% better than the TwigStack algorithm, 31% better than TwigINLAB, 11% better than TwigStackList and about 9% better than TwigStackXB in terms of execution time.     

Attribute grammars for scalable query processing on XML streams

We introduce the notion of XML Stream Attribute Grammars (XSAGs). XSAGs are the first scalable query language for XML streams (running strictly in linear time with bounded memory consumption independent of the size of the stream) that allows for actual data transformations rather than just document filtering. XSAGs are also relatively easy to use for humans. Moreover, the XSAG formalism provides a strong intuition for which queries can or cannot be processed scalably on streams. We introduce XSAGs together with the necessary language-theoretic machinery, study their theoretical properties such as expressiveness and complexity, and discuss their implementation.     

RPE query processing and optimization techniques for XML databases

An extent join to compute path expressions containing parent-children and ancestor-descendent operations and two path expression optimization rules, path-shortening and path-complementing, are presented in this paper. Path-shortening reduces the number of joins by shortening the path while path-complementing optimizes the path execution by using an equivalent complementary path expression to compute the original one. Experimental results show that the algorithms proposed are more efficient than traditional algorithms.     

Efficiently supporting order in XML query processing

XML is an ordered data model and XQuery expressions return results that have a well-defined order. However, little work on how order is supported in XML query processing has been done to date. In this paper we study the issues related to handling order in the XML context, namely challenges imposed by the XML data model, the variety of order requirements of the XQuery language, and the need to maintain order in the presence of updates to the XML data. We propose an efficient solution that addresses all these issues. Our solution is based on a key encoding for XML nodes that serves as node identity and at the same time encodes order. We design rules for encoding order of processed XML nodes based on the XML algebraic query execution model and the node key encoding. These rules do not require any actual sorting for intermediate results during execution. Our approach enables efficient order-sensitive incremental view maintenance as it makes most XML algebra operators distributive with respect to bag union. We prove the correctness of our order encoding approach. Our approach is implemented and integrated with Rainbow, an XML data management system developed at WPI. We have tested the efficiency of our approach using queries that have different order requirements. We have also measured the relative cost of different components related to our order solution in different types of queries. In general the overhead of maintaining order in our approach is very small relative to the query processing time.     

Query optimization in XML structured-document databases

While the information published in the form of XML-compliant documents keeps fast mounting up, efficient and effective query processing and optimization for XML have now become more important than ever. This article reports our recent advances in XML structured-document query optimization. In this article, we elaborate on a novel approach and the techniques developed for XML query optimization. Our approach performs heuristic-based algebraic transformations on XPath queries, represented as PAT algebraic expressions, to achieve query optimization. This article first presents a comprehensive set of general equivalences with regard to XML documents and XML queries. Based on these equivalences, we developed a large set of deterministic algebraic transformation rules for XML query optimization. Our approach is unique, in that it performs exclusively deterministic transformations on queries for fast optimization. The deterministic nature of the proposed approach straightforwardly renders high optimization efficiency and simplicity in implementation. Our approach is a logical-level one, which is independent of any particular storage model. Therefore, the optimizers developed based on our approach can be easily adapted to a broad range of XML data/information servers to achieve fast query optimization. Experimental study confirms the validity and effectiveness of the proposed approach.     

XML数据库的安全查询处理

当今XML数据库查询系统必须处理快速增长的数据量和大量的用户,如果使用细粒度级别的访问控制保护敏感XML数据,则查询效率会较低,因为当用户视图需要计算得出时,很难对XML文档的每个节点实施访问控制。提出一个安全的XML查询方案,它使用缓存存储查询结果和安全信息。用户查询重写为安全的系统查询,依据缓存是否命中,决定在缓存还是源XML文档上执行得到查询结果;提出一个新的缓存替换策略LSL,它基于安全级别对缓存更新。实验结果表明,该方案能显著地改进查询系统性能。     

Rule-based spatiotemporal query processing for video databases

In our earlier work, we proposed an architecture for a Web-based video database management system (VDBMS) providing an integrated support for spatiotemporal and semantic queries. In this paper, we focus on the task of spatiotemporal query processing and also propose an SQL-like video query language that has the capability to handle a broad range of spatiotemporal queries. The language is rule-based in that it allows users to express spatial conditions in terms of Prolog-type predicates. Spatiotemporal query processing is carried out in three main stages: query recognition, query decomposition, and query execution.Received: 11 October 2001, Accepted: 3 October 2003, Published online: 12 December 2003Edited by: A. Buchmann Correspondence to: Özgür UlusoyThis work is supported by the Scientific and Research Council of Turkey (TÜBITAK) under Project Code 199E025. This work was done while the first author was at Bilkent University.     

Temporal XML: modeling, indexing, and query processing

In this paper we address the problem of modeling and implementing temporal data in XML. We propose a data model for tracking historical information in an XML document and for recovering the state of the document as of any given time. We study the temporal constraints imposed by the data model, and present algorithms for validating a temporal XML document against these constraints, along with methods for fixing inconsistent documents. In addition, we discuss different ways of mapping the abstract representation into a temporal XML document, and introduce TXPath, a temporal XML query language that extends XPath 2.0. In the second part of the paper, we present our approach for summarizing and indexing temporal XML documents. In particular we show that by indexing continuous paths, i.e., paths that are valid continuously during a certain interval in a temporal XML graph, we can dramatically increase query performance. To achieve this, we introduce a new class of summaries, denoted TSummary, that adds the time dimension to the well-known path summarization schemes. Within this framework, we present two new summaries: LCP and Interval summaries. The indexing scheme, denoted TempIndex, integrates these summaries with additional data structures. We give a query processing strategy based on TempIndex and a type of ancestor-descendant encoding, denoted temporal interval encoding. We present a persistent implementation of TempIndex, and a comparison against a system based on a non-temporal path index, and one based on DOM. Finally, we sketch a language for updates, and show that the cost of updating the index is compatible with real-world requirements.     

Enabling privacy and leakage resistance for dynamic blockchain-based access control systems

With rise of 5G/6G network, low-storage devices usually outsource data for higher rate and less latency. Non-controlled outsourcing and complex communications incur security issues for IoT applications. Specially, user privacy and access reliability pose technical challenges for sensitive data outsourcing and sharing. In this paper, we harmonize functional encryption and blockchain to propose a reliable and privacy-aware access control system named R-PAC. It allows a result-form access without learning raw information and fair interaction against malicious users. With a combination of all-or-nothing encapsulation technology, R-PAC supports users’ dynamic joining and key leakage resistance. We design R-PAC from Boneh–Franklin identity-based encryption, with forward-coverable encryption and reverse-discoverable decryption, and formally prove its indistinguishability security. We implement a R-PAC prototype and deploy it to a simulated Ethereum network to evaluate its performance. Experiments from both data access and transaction overhead show that R-PAC is with reasonable cost and has a trade-off between efficiency and strong security/functionality.     

A coherent query language for XML

Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents. On the other hand, the query languages supported by specialized XML search engines are very complex. In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction of relevant fragments of information while simultaneously falling back on retrieval through plain text search if necessary. Our approach combines and generalizes several available techniques to obtain precise and coherent results.

A performance comparison of distance-based query algorithms using R-trees in spatial databases

Efficient processing of distance-based queries (DBQs) is of great importance in spatial databases due to the wide area of applications that may address such queries. The most representative and known DBQs are the K Nearest Neighbors Query (KNNQ), ρ Distance Range Query (ρDRQ), K Closest Pairs Query (KCPQ) and ρ Distance Join Query (ρDJQ). In this paper, we propose new pruning mechanism to apply them in the design of new Recursive Best-First Search (RBFS) algorithms for DBQs between spatial objects indexed in R-trees. RBFS is a general search algorithm that runs in linear space and expands nodes in best-first order, but it can suffer from node re-expansion overhead (i.e. to expand nodes in best-first order, some nodes can be considered more than once). The R-tree and its variations are commonly cited spatial access methods that can be used for answering such spatial queries. Moreover, an exhaustive experimental study was also included using R-trees, which resulted to several conclusions about the efficiency of proposed RBFS algorithm and its comparison with respect to other search algorithms (Best-First Search (BFS) and Depth-First Branch-and-Bound (DFBnB)), in terms of disk accesses, response time and main memory requirements, taking into account several important parameters as maximum branching factor (Cmax), cardinality of the final query result (K), distance threshold (ρ) and size of a global LRU buffer (B). In general RBFS is competitive for KNNQ and KCPQ where the maximum branching factor (Cmax) is large enough (even better than DFBnB and very close to BFS), and it is a good alternative when we have main memory limitations in our computer due to high process overload in our system, since it is linear space consuming with respect to the height of the R-trees. Nevertheless, RBFS is the worst alternative for ρDRQ and ρDJQ. DFBnB is also a linear space algorithm and it obtains the same behavior as BFS for ρDRQ and ρDJQ; and it is the best when an LRU buffer was included. Finally, we have been able to check experimentally that BFS is the best for all DBQs, but it can consume many main memory resources to perform spatial queries.     

Context-aware privacy-preserving access control for mobile computing

In mobile and pervasive computing applications, opportunistic connections allow co-located devices to exchange data directly. Keeping data sharing local enables large-scale cooperative applications and empowers individual users to control what and how information is shared. Supporting such applications requires runtime frameworks that allow them to manage the who, what, when, and how of access to resources. Existing frameworks have limited expressiveness and do not allow data owners to modulate the granularity of information released. In addition, these frameworks focus exclusively on security and privacy concerns of data providers and do not consider the privacy of data consumers. We present PADEC, a context-sensitive, privacy-aware framework that allows users to define rich access control rules over their resources and to attach levels of granularity to each rule. PADEC is also characterized by its expressiveness, allowing users to decide under which conditions should which information be shared. We provide a formal definition of PADEC and an implementation based on private function evaluation. Our evaluation shows that PADEC is more expressive than other mechanisms, protecting privacy of both consumers and providers.     

Native XML数据库XSQS查询处理系统的设计与实现

XML已经成为互联网中数据表示和数据交换事实上的标准.实现专门对于XML数据的有效存储和查询变得十分重要.报告了当前NativeXML数据库在国内外的发展情况,讨论了一种NativeXML数据库管理系统原型XSQS的功能及概要设计.系统采用了基于压缩表的存储方式和索引结构,采用了基于结果集的查询处理方法.重点讨论了系统查询处理部分的设计及实现.实践结果表明,这种存储索引结构和查询方式相结合,使系统在查询效率上有了显著的提高.     

Information access in multimedia databases based on feature models

With the increasing popularity of the WWW, the main challenge in computer science has become content-based retrieval of multimedia objects. Access to multimedia objects in databases has long been limited to the information provided in manually assigned keywords. Now, with the integration of feature-detection algorithms in database systems software, content-based retrieval can be fully integrated with query processing. We describe our experimentation platform under development, making database technology available to multimedia. Our approach is based on the new notion of feature databases. Its architecture fully integrates traditional query processing and content-based retrieval techniques. Arjen P. de Vries, Ph.D.: He received his Ph.D. in Computer Science from the University of Twente in 1999, on the integration of content management in database systems. He is especially interested in the new requirements on the design of database systems to support content-based retrieval in multimedia digital libraries. He has continued to work on multimedia database systems as a postdoc at the CWI in Amsterdam as well as University of Twente. Menzo Windhouwer: He received his MSc in Computer Science and Management from the University of Amsterdam in 1997. Currently he is working in the CWI Database Research Group on his Ph.D., which is concerned with multimedia indexing and retrieval using feature grammars. Peter M.G. Apers, Ph.D.: He is a full professor in the area of databases at the University of Twente, the Netherlands. He obtained his MSc and Ph.D. at the Free University, Amsterdam, and has been a visiting researcher at the University of California, Santa Cruz and Stanford University. His research interests are query optimization in parallel and distributed database systems to support new application domains, such as multimedia applications and WWW. He has served on the program committees of major database conferences: VLDB, SIGMOD, ICDE, EDBT. In 1996 he was the chairman of the EDBT PC. In 2001 he will, for the second time, be the chairman of the European PC of the VLDB. Currently he is coordinating Editor-in-Chief of the VLDB Journal, editor of Data & Knowledge Engineering, and editor of Distributed and Parallel Databases. Martin Kersten, Ph.D.: He received his PhD in Computer Science from the Vrije Universiteit in 1985 on research in database security, whereafter he moved to CWI to establish the Database Research Group. Since 1994 he is professor at the University of Amsterdam. Currently he is heading a department involving 60 researchers in areas covering BDMS architectures, datamining, multimedia information systems, and quantum computing. In 1995 he co-founded Data Distilleries, specialized in data mining technology, and became a non-executive board member of the software company Consultdata Nederland. He has published ca. 130 scientific papers and is member of the editorial board of VLDB journal and Parallel and Distributed Systems. He acts as a reviewer for ESPRIT projects and is a trustee of the VLDB Endowment board.     

The CQL continuous query language: semantic foundations and query execution

CQL, a continuous query language, is supported by the STREAM prototype data stream management system (DSMS) at Stanford. CQL is an expressive SQL-based declarative language for registering continuous queries against streams and stored relations. We begin by presenting an abstract semantics that relies only on “black-box” mappings among streams and relations. From these mappings we define a precise and general interpretation for continuous queries. CQL is an instantiation of our abstract semantics using SQL to map from relations to relations, window specifications derived from SQL-99 to map from streams to relations, and three new operators to map from relations to streams. Most of the CQL language is operational in the STREAM system. We present the structure of CQL's query execution plans as well as details of the most important components: operators, interoperator queues, synopses, and sharing of components among multiple operators and queries. Examples throughout the paper are drawn from the Linear Road benchmark recently proposed for DSMSs. We also curate a public repository of data stream applications that includes a wide variety of queries expressed in CQL. The relative ease of capturing these applications in CQL is one indicator that the language contains an appropriate set of constructs for data stream processing. Edited by M. Franklin