G. S. Thejas

TL;DR: A deep-learning based model is proposed that is a hybrid of artificial neural network (ANN), autoencoder and semi-supervised generative adversarial network (GAN) and triumphs excellent accuracy than other models towards click fraud detection.

TL;DR: This work proposes a new feature selection mechanism, an amalgamation of the filter and the wrapper techniques by taking into consideration the benefits of both the methods, based on a two phase process where the features are ranked and the best subset of features are chosen based on the ranking.

TL;DR: The objective of the proposed work is to model multi-time-scale time series data on AR/MA by relying only on time and the label without the need of too many attributes and to model different time scales separately on Auto-regression (AR) and Moving Average (MA) models.

TL;DR: This paper proposes a modified dynamic framework which is the self-adaptable trust-based access control (SATBAC) with the help of several access request evaluating techniques like opinion and reputation, behavior and history, and credential and location and analyzes the trust values obtained using game theory-based reward-punishment strategy.

TL;DR: A comprehensive key management infrastructure (CKMI) is designed for IACS by considering the generic industrial automation network and employs ECDH, matrix method, and polynomial crypto mechanisms, which handles all the standard key management operations.