Frequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 5 Issue 2
Educational Data Mining by Using Neural Network
Nitya Upadhyay
10.7753/IJCATR0502.1013
keywords : Digital artifacts, man in the middle attack(MIMA), semantic web, RDF, trusty URI.
Distributed digital artifacts incorporate cryptographic hash values to URI called trusty URIs in a distributed environment building good in quality, verifiable and unchangeable web resources to prevent the rising man in the middle attack. The greatest challenge of a centralized system is that it gives users no possibility to check whether data have been modified and the communication is limited to a single server. As a solution for this, is the distributed digital artifact system, where resources are distributed among different domains to enable inter-domain communication. Due to the emerging developments in web, attacks have increased rapidly, among which man in the middle attack (MIMA) is a serious issue, where user security is at its threat. This work tries to prevent MIMA to an extent, by providing self reference and trusty URIs even when presented in a distributed environment. Any manipulation to the data is efficiently identified and any further access to that data is blocked by informing user that the uniform location has been changed. System uses self-reference to contain trusty URI for each resource, lineage algorithm for generating seed and SHA-512 hash generation algorithm to ensure security. It is implemented on the semantic web, which is an extension to the world wide web, using RDF (Resource Description Framework) to identify the resource. Hence the framework was developed to overcome existing challenges by making the digital artifacts on the semantic web distributed to enable communication between different domains across the network securely and thereby preventing MIMA.
@artical{n522016ijcatr05021013,
Title = "Educational Data Mining by Using Neural Network",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="2",
Pages ="104 - 109",
Year = "2016",
Authors ="Nitya Upadhyay"}
In this paper, a new algorithm used SPRINT which removes all memory restriction and accuracy problem.
It can be implemented in serial and parallel for data placement and load balancing.
SPRINT is fast, scalable decision tree classifier.
It provides excellent speed up, size up and scale up properties.