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.

Business data access client for online/offline client use

Abstract: Architecture for uninterrupted access to business data by enabling work on rich client machines to be stored in a local business data cache that is always available. A dispatching mechanism executes read/write requests against the local cache transparently to a client application, an automatic synchronization mechanism propagates changes bi-directionally when the client goes online and a live connection with the corresponding backend data source is available. A declarative data access model is employed based on operation stereotyping and grouping that enables client applications to transparently execute create, read, update, delete, query (CRUDQ) and association operations against the local cache as if executed against the actual business data source. The architecture supports the offline creation of entities and sets of related entities when the entity identifiers are generated by the business data source and offline navigation of entity associations when foreign keys are not present in the related entities.

The Ontop Framework for Ontology Based Data Access

Abstract: Ontology Based Data Access (OBDA) [4] is a paradigm of accessing data trough a conceptual layer. Usually, the conceptual layer is expressed in the form of an RDF(S) [10] or OWL [15] ontology, and the data is stored in relational databases.

Method and apparatus for controlling access to data elements in a data processing system based on status of an industrial process

Abstract: The security of data elements which represent an industrial process, which are manipulated by users on a data processing system and in which the industrial process includes a series of industrial process steps, are controlled by permitting groups of users to access predetermined data elements based on the industrial process step at which the industrial process is currently active. A user is prevented from accessing the requested element if the industrial process is not at an industrial process step corresponding to one of the industrial process steps for which the user has authority to access the data element. Thus, access to data is prevented based on the status of the data, in addition to the type of data. When selected database elements are associated with one of many locations, access is also denied to a user based on the location. Security access based on status and location may be provided in response to a change in the current industrial process step. Access authority to the data elements is changed compared to the access authority at the immediately preceding industrial process step based on mappings in one or more tables. Improved security of data elements which represent an industrial process is thereby provided.

Genetic Algorithm Rule-Based Intrusion Detection System (GAIDS)

Abstract: This study examines the detection of attacks or network intrusion by users referred to as hackers (whose aim is to gain illegal entry as well as access to a network system and resources. Network and data security has become a pertinent issue with the advent of the Internet; though the Internet comes with a lot of merits on its own. Traditional used methods for data security includes the use of passwords, cryptography to mention few. The approach considered here is Intrusion Detection System, which is a software, driver or device used to prevent an unauthorized or illegal access to data in a networked system. Most of the existing IDS are implemented via rule-based systems where new attacks are not detectable. This study thus, presents a genetic algorithm based approach (with its driver implementation), which employs a set of classification rule derived from network audit data and the support-confidence framework, utilized as fitness function to judge the quality of each rule. The software implementation is aimed at improving system security in networked settings allowing for confidentiality, integrity and availability of system resources.

Measurement and analysis of real-world 802.11 mesh networks

Abstract: Despite many years of work in wireless mesh networks built using 802.11 radios, the performance and behavior of these networks in the wild is not well-understood. This lack of understanding is due in part to the lack of access to data from a wide range of these networks; most researchers have access to only one or two testbeds at any time. In recent years, however, 802.11 mesh networks networks have been deployed commercially and have real users who use the networks in a wide range of conditions. This paper analyzes data collected from 1407 access points in 110 different commercially deployed Meraki wireless mesh networks, constituting perhaps the largest study of real-world 802.11 networks to date. After analyzing a 24-hour snapshot of data collected from these networks, we answer questions from a variety of active research topics, such as the accuracy of SNR-based bit rate adaptation, the impact of opportunistic routing, and the prevalence of hidden terminals. The size and diversity of our data set allows us to analyze claims previously only made in small-scale studies. In particular, we find that the SNR of a link is a good indicator of the optimal bit rate for that link, but that one could not make an SNR-to-bit rate look-up table that was accurate for an entire network. We also find that an ideal opportunistic routing protocol provides little to no benefit on most paths, and that "hidden triples"---network topologies that can lead to hidden terminals--are more common than suggested in previous work, and increase in proportion as the bit rate increases.