February 2018 Issue Vol.8 No.2



A PERFORMANCE COMPARISON OF AUTHENTICATION AND PRIVACY PRESERVING TECHNIQUES FOR SECURED COMMUNICATION IN VANET https://ia601504.us.archive.org/19/items/IJITCEFEB19/IJITCE_vol9no201.pdf
K . Nirmala Ph.D Research Scholar (Part-Time),
Department of Computer Science, Nandha Arts & Science College, Erode, Tamil Nadu, India

Dr.S.Prasath Assistant Professor & Research Supervisor,
Department of Computer Science, Nandha Arts & Science College, Erode, Tamil Nadu, India


Abstract: Vehicle adhoc network (VANET) is vital role in communication which is used for enhancing the traffic efficiency and safety through communicating one vehicle with other vehicles. Security is the key problems in VANETs and trust is an essential one that avoid the generic attacks on network. A misuse of information leads to the traffic accident and loss of human lives. Vehicle authentication is need for improving the security level in VANET. In the authentication, vehicle data like identity and location information are kept private. Privacy is an important one during communication in VANETs. The vehicle privacy information like current position, license number, drivers identity and travel route are maintained as confidential one for long time period. Many techniques were developed for secured communication in VANET. But the existing techniques have some drawbacks, there is a need to improve the authentication accuracy and privacy performance during communication in VANET. To improve the security level during communication, machine learning and cryptographic techniques is used.
Keywords:AES, CFES,MBC,MBECC,ECC.

ANALYTICAL MEASURES FOR DETECTING FRAUD USING CLASSIFICATION ALGORITHMS https://ia601504.us.archive.org/19/items/IJITCEFEB19/IJITCE_vol9no202.pdf

D .Vimal Kumar1 Associate Professor,
Dept. Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India.

M.V.Jisha2 Ph.D Scholar,
Dept. Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India.


Abstract: Abundant proliferation in usage of credit, debit and ATM card transactions, their use has become increasingly rampant in recent years. The proposed paper work investigates the efficiency of applying classifying algorithms to detect frauds prevailing in its usage. There exists various factors to analyze plentiful classification algorithms ,like KNN, Logistic Regression, Support Vector Machine and Random Forest. The proposed work analyzed that the performance of Random Forest is the efficient algorithm to detect the fraud transaction in terms of different factors
Keywords:Credit cards, KNN, Logistic Regression, Support Vector Machine and Random Forest

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