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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Luring Conditions and Their Proof of Necessity through Mathematical Modelling
verfasst von : Anand Gupta, Prashant Khurana, Raveena Mathur
Erschienen in: Big Data Analytics
Verlag: Springer Berlin Heidelberg
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Luring is a social engineering technique used to capture individuals having malicious intent of breaching the information security defense of an organization. Certain conditions(Need, Environment, Masquerading Capability and Unawareness) are necessary for its effective implementation. To the best of our knowledge the necessity of these conditions is not yet proved so far. The proof is essential as it not only facilitates automation of the luring mechanism but also paves way for proof of the completeness of the conditions. The present paper attempts on this aspect by invoking three approaches namely probability, entropy and proof by contra positive. Also, the concept of cost effectiveness is introduced. Luring is acceptable if its cost works out less than cost of data theft.