Classification of Big Data Security Based on Ontology Web Language

A vast amount of data (known as big data) may now be collected and stored from a variety of data sources, including event logs, the internet, smartphones, databases, sensors, cloud computing, and Internet of Things (IoT) devices. The term “big data security” refers to all the safeguards and instruments used to protect both the data and analytics processes against intrusions, theft, and other hostile actions that could endanger or adversely influence them. Beyond being a high-value and desirable target, protecting Big Data has particular difficulties. Big Data security does not fundamentally differ from conventional data security. Big Data security issues are caused by extraneous distinctions rather than fundamental ones. This study meticulously outlines the numerous security difficulties Large Data analytics now faces and encourages additional joint research for reducing both big data security challenges utilizing Ontology Web Language (OWL). Although we focus on the Security Challenges of Big Data in this essay, we will also briefly cover the broader Challenges of Big Data. The proposed classification of Big Data security based on ontology web language resulting from the protégé software has 32 classes and 45 subclasses.

Implementation of Enterprises Interoperation Based on Ontology

The interoperation among enterprises in e-business could block the ambient semantic collaboration and cause a big problem since varying information descriptions and different data models may be used in different enterprises＇ information systems. Ontology is an important tool to overcome the above mentioned syntax and semantic misunderstanding problem. Our goal is to provide a user-friendly environment supporting syntax and neutral format data model for business information. In this paper, two scenarios are discussed and a unified description of data model is developed to solve the gap in interoperation through mapping from logical data of enterprise＇s information system. It provides the methods to realize the mapping among different types of data or information. First, database and other types of information are transformed into neutral format that are described by web ontology language （OWL）. Second, the neutral format can be mapped into the semantic entities and semantic linking through the process of extraction and annotation and added into ontology and then described in a standard format that makes the collaboration be understood easily.

Description method of conceptual model based on the ontology

The conceptual model is the first time abstraction ceptual model description method based on the UML and the of the real world. The traditional con- text usually has the semantic ambiguity problem. The formal description method lacks the mechanism of integrity and consistency check. Therefore both of them cannot support the simulation scenario description and the model compos- ability. A simulation conceptual description method based on ontology is put forward. According to the OWL language which was put forward by the W3C organization, a conceptual model description language is established. The OWL language semantic element in the description function in the mili- tary conceptual model is introduced. Then two layers of the military conceptual model framework are built up based on the general ontology and the domain ontology. In the general ontology, the class and property definition are given. While in the domain ontology, they are extended and a relat- ed example is given. The technique advantages of our method include the mechanism of conceptual model consistency and integrity check, the support of composable simulation models, and automatic creation of simulation scenario.

Generalized Testability Scheme Modeling of Materiel System Based on Information Ontology

A mode of ontology-based information integration and management( OIIM) for testability scheme was proposed through expatiating on the connotation of the system testability scheme.Aiming at the complexity of influencing factors in optimal design procedure of the testability scheme, the information of concept entities,concept attributions and concept relationships was analyzed and extracted,and then the testability scheme information ontology( TSIO) was built and coded via web ontology language( OWL).Based on the information ontology, the generalized model for testability scheme( GMTS) was founded by defining transformation rules. The primary study shows that the mode of OIIM for testability scheme can make up the deficiencies in knowledge representation and reasoning existing in traditional information models,and achieve the information share and reuse. It provides the effectual model basis for the optimal design of the testability scheme.

AN IMPROVED HYBRID SEMANTIC MATCHING ALGORITHM WITH LEXICAL SIMILARITY

In this paper, we proposed an improved hybrid semantic matching algorithm combining Input/Output (I/O) semantic matching with text lexical similarity to overcome the disadvantage that the existing semantic matching algorithms were unable to distinguish those services with the same I/O by only performing I/O based service signature matching in semantic web service discovery techniques. The improved algorithm consists of two steps, the first is logic based I/O concept ontology matching, through which the candidate service set is obtained and the second is the service name matching with lexical similarity against the candidate service set, through which the final precise matching result is concluded. Using Ontology Web Language for Services (OWL-S) test collection, we tested our hybrid algorithm and compared it with OWL-S Matchmaker-X (OWLS-MX), the experimental results have shown that the proposed algorithm could pick out the most suitable advertised service corresponding to user's request from very similar ones and provide better matching precision and efficiency than OWLS-MX.

Development and Research on the Internet Resources Aggregation Platform

We proposed an Intemet resource aggregation platform based on semantic web. The platform includes an Web Ontology Language（OWL） ontology design toolkit（VO-Editor） and a selective inference algorithm engine so that it can visually editing ontology and using novel selective reasoning for information aggregation. We introduce the VO-Editor and the principle of selective inference algorithm. At last a case of budget travel system is used to interpret the approach of Internet resources aggregation by this platform.

Towards a Service-Oriented Architecture for a Mobile Assistive System with Real-time Environmental Sensing

With the growing aging population, age-related diseases have increased considerably over the years.In response to these, Ambient Assistive Living（AAL） systems are being developed and are continually evolving to enrich and support independent living. While most researchers investigate robust Activity Recognition（AR）techniques, this paper focuses on some of the architectural challenges of the AAL systems. This work proposes a system architecture that fuses varying software design patterns and integrates readily available hardware devices to create Wireless Sensor Networks（WSNs） for real-time applications. The system architecture brings together the Service-Oriented Architecture（SOA）, semantic web technologies, and other methods to address some of the shortcomings of the preceding system implementations using off-the-shelf and open source components. In order to validate the proposed architecture, a prototype is developed and tested positively to recognize basic user activities in real time. The system provides a base that can be further extended in many areas of AAL systems,including composite AR.