Epidemic Analysis of uncertainty in Deception Detection under Fuzzified Anomalies
S. Rajkumar1, V. Narayani2, S. P. Victor3
1S.Rajkumar, Research Scholar, Bharathiar University, HOD/CSE, Nehru Institute of Engineering & Technology, Coimbatore, India.
2V.Narayani, Dept. of Computer Science, St.Xavier’s College, Tirunelveli, India.
3Dr.S.P.Victor, Dept. of Computer Science, St.Xavier’s College, Tirunelveli, India.
Manuscript received on December 04, 2011. | Revised Manuscript received on December 26, 2011. | Manuscript published on January 05, 2012. | PP: 371-376 | Volume-1 Issue-6, January 2012. | Retrieval Number: F0345121611/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays in this competitive world of job seekers, the necessity of job makes many recruiters to provide more cautious on their selection process. The recruitment process is definitely a fuzzified anomaly for all the components available in the environment. The art of deception also changes its face with a modern artistic fashion. This paper deals with the uncertainty features which play the major role of Deception in a fuzzified environment of Recruitment process. We deal with the impacts of uncertainty in deception detections and also with the underlying environment of fuzzification. In this paper we proposed a Research Model which considers the linkage of fuzzification and uncertainty in Deception Detection. In this paper we implement our proposed model with an experiment which includes warning and lack of warning to the recruiters upon the competitors. Enumerated results and discussions mould the impact of uncertainty and fuzziness in Deception Detection.
Keywords: Deception, Fuzzy logic, Randomization, Uncertainty.