Data Partitioning for Semantic Web

Semantic web database is an RDF database. Tremendous increase can be seen in semantic web data, as real life applications of semantic web are using this data. Efficient management of this data at a larger scale, and efficient query performance are the two major concerns. This work aims at analyzing query performance issues in terms of execution time and scalability using data partitioning techniques. An experiment is devised to show effect of data partitioning technique on query performance. It demonstrates the query performance analysis for partitioning techniques applied. Vertical partitioning, hybrid partitioning and property table was used to store the RDF data and query execution time is analyzed. The experiment was carried out on a very small dummy data and now it will be scaled up using Barton library catalogue

Preventing SQL Injection through Automatic Query Sanitization with ASSIST

Web applications are becoming an essential part of our everyday lives. Many of our activities are dependent on the functionality and security of these applications. As the scale of these applications grows, injection vulnerabilities such as SQL injection are major security challenges for developers today. This paper presents the technique of automatic query sanitization to automatically remove SQL injection vulnerabilities in code. In our technique, a combination of static analysis and program transformation are used to automatically instrument web applications with sanitization code. We have implemented this technique in a tool named ASSIST (Automatic and Static SQL Injection Sanitization Tool) for protecting Java-based web applications. Our experimental evaluation showed that our technique is effective against SQL injection vulnerabilities and has a low overhead.Comment: In Proceedings TAV-WEB 2010, arXiv:1009.330