Table of Content - International Journal of Managing Information Technology (IJMIT) - Current Issue

INTERNATIONAL JOURNAL OF MANAGING INFORMATION TECHNOLOGY (IJMIT)

ISSN: 0975-5586 (ONLINE); 0975-5926 (PRINT)

http://airccse.org/journal/ijmit/ijmit.html

CURRENT ISSUEVOLUME 11, NUMBER 4      ------------         TABLE OF CONTENT

http://airccse.org/journal/ijmit/vol11.html

A Comparative Study Of NOSQL System Vulnerabilities With Big Data

Kiran Fahd¹, Sitalakshmi Venkatraman¹ and Fahd Khan Hammeed²,

¹Melbourne Polytechnic, Australia and ²Data Centre, Australia

ABSTRACT

With the emerging third wave in the development of the Internet, the past year has witnessed huge data exposure resulting in cyber-attacks that have increased four times as that of the previous year’s record. In this digital era, businesses are making use of NoSQL technologies for managing such Big Data. However, the NoSQL database systems come with inherent security issues, which pose a major challenge to many organisations worldwide. There is a paucity of research studies for exposing the security threats and vulnerabilities of NoSQL technologies comprehensively. This paper presents an in-depth study of NoSQL security issues by performing a detailed comparative study of the security vulnerabilities identified in NoSQL database systems. A set of key security features offered by the four commonly used NoSQL database systems, namely Redis, Cassandra, MongoDB and Neo4j are analysed with an aim to identify their strengths and weaknesses. The vulnerabilities associated with built-in security, encryption, authentication/authorization and auditing that impact Big Data management are compared among these popular NoSQL database systems and the risk levels are identified. In addition, illustrations of possible injection attacks experimented with these NoSQL systems are provided. Finally, a high-level framework is proposed for NoSQL databases with considerations for security measures in Big Data deployments. The discussion forms a significant technical contribution for learners, application developers and Big Data deployers paving way for a better awareness and management of the NoSQL systems in an organization.

KEYWORDS

NoSQL, Big Data, security, vulnerabilities, non-relational database, injection attacks

ORIGINAL SOURCE URL: http://aircconline.com/ijmit/V11N4/11419ijmit01.pdf

Abstract URL: http://aircconline.com/abstract/ijmit/v11n4/11419ijmit01.html

http://airccse.org/journal/ijmit/vol11.html

The Development Of Research Recommendation System For Southern Thailand Development

Nawapon Kewsuwun¹, Kanyarat Kwiecien¹ and Chumchit Sae-Chan²,

 ¹Khon Kaen University, Thailand and ²Prince of Songkla University, Thailand

ABSTRACT

The research was to identify needs on design and development of a research recommendation system for 14 southern province Thailand development. The system employs semantic search function, research system structure and scope of knowledge during January 2008 to December 2017. 3,873 entries had been gathered from Thai Library Integrated System (ThaiLIS), Thai National Research Repository (TNRR), and Southern universities research database by employing textual analysis and knowledge organization focusing on Classification Approach and categorization which main topics are sorted and categorized. To develop ontology, it applies knowledge engineering concept and using Protégé Ontology Editor version 3.5 beta and version 5.5 beta to process the data for the accurate system development according to user-centered design concept. The study findings were the developed system is able to support information exchange, information retrieval, and research search and to decrease research redundancy and unnecessary budgeting. Moreover, the system could possible enhance conducting more innovations, confirming experts in the area, showing research trends, and showing research results on related fields, strategies, and problems which leads to the Southern developments extensively. After the implementation, the users’ overall opinions and satisfaction was at a high level ( = 4.14, S.D = 0.14) and information retrieval efficiency of system was at a good level (overall = 0.70-0.88) with 0.70 accuracy, 0.78 recall, 0.88 precision, and 0.82 F-measure.

 KEYWORDS

 Research recommendation system, southern Thailand development, research for development, information        and knowledge management, Ontology.

ORIGINAL SOURCE URL: http://aircconline.com/ijmit/V11N4/11419ijmit02.pdf

Abstract URL: http://aircconline.com/abstract/ijmit/v11n4/11419ijmit02.html

http://airccse.org/journal/ijmit/vol11.html