Notice Board :

Call for Paper
Vol. 5 Issue 12

Submission Start Date:
Dec 01, 2018

Acceptence Notification Start:
Dec 10, 2018

Submission End:
Dec 15, 2018

Final MenuScript Due:
Dec 30, 2018

Publication Date:
Jan 01, 2019
                         Notice Board: Call for PaperVol. 5 Issue 12      Submission Start Date: Dec 01, 2018      Acceptence Notification Start: Dec 10, 2018      Submission End: Dec 15, 2018      Final MenuScript Due: Dec 30, 2018      Publication Date: Jan 01, 2019




Volume V Issue III

Author Name
Srashtika Gupta, Mr. Mubeen A. Khan
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 3
Abstract
Cloud computing is a popular subject across the IT industry, but risks associated with this new technology and delivery model is not yet well understood. Because of the attractive features of cloud computing many organizations are using cloud storage for storing their critical information. The data can be stored remotely in the cloud by the users and can be accessed using clients as and when required. This technology provides services with one of the three service models: Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). This model allows users and organizations to share their vital information, crucial computing resources across the world. Securing these essential resources from the unauthorized access of the users is one of the major issues which leads to reduce the growth of this technology in the Information Technology (IT) Industries.
PaperID
2018/IJTRM/3/2018/11649

Author Name
Dr. Upendra Singh Panwar
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 3
Abstract
Purpose: The aim of this research paper is to compare perceptions of bank service quality dimensions among Indian and Thai customers, and to determine perception differences of service quality dimensions in both countries. Design/methodology/approach: Data were collected using SERVQUAL (Perception) scale of Parasuraman, Zeithml, and berry 1986, 1988) from two convenience samples of bank customers (101 in India and 101 in Thailand). Service quality was measured using the five SERVQUAL dimensions of Tangibles, Reliability, Responsiveness, Assurance, and Empathy. Data were analyzed using Normality, Reliablity and ANOVA.
PaperID
2018/IJTRM/3/2018/11650

Author Name
Yogadhar Pandey, Prof. Shailendra Singh
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 3
Abstract
Network-based intrusion detection systems (NIDS) have become important and widely used tools for ensuring network security. Processing huge amount of audit data is a challenging task for NIDS, because these data contains large amount of irrelevant or redundant features. To improve the accuracy and efficiency of NIDS, relevant features are essential to be extracted from original dataset with the help of feature selection methods. This paper proposes reduced feature selection algorithm (RFSA) an efficient feature selection approach for network based intrusion detection system. The RFSA gives better detection rate, accuracy and false alarm rate when compared to full feature set. RFSA also outperform when compared with the existing algorithms. Empirical results endorse the overall performance and accuracy of the system. This work uses KDD99 dataset for the evaluation of the experiments.
PaperID
2018/IJTRM/3/2018/11652

Author Name
Heena Ansari, Prof. Abhishek Raghuwanshi
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 3
Abstract
The data mining and their different applications are becomes more popular now in these days a number of large and small scale applications are developed with the help of data mining techniques i.e. predictors, regulators, weather forecasting systems and business intelligence. There are two kinds of model are available for namely supervised and unsupervised. The performance and accuracy of the supervised data mining techniques are higher as compared to unsupervised techniques therefore in sensitive applications the supervised techniques are used for prediction and classification. This paper presents a high utility item set mining technique. In this technique, the useless patterns are removed at the initial stage of mining. So it is helping in getting less time consumption.
PaperID
2018/IJTRM/3/2018/11653