Tata Consultancy Services Limited

Tulika Bose

Arpan Pal

Soma Bandyopadhyay

Arijit Ukil

Tanushyam Chattopadhyay

Abhijan Bhattacharyya

Chetanya Puri

Angshul Majumdar

Arjit Ukil

A method and system for incorporating regression into a Stacked Auto Encoder utilizing deep learning based regression technique that enables joint learning of parameters for a regression model to train the SAE for a regression problem. The method comprises generating a regression model for the SAE for solving the regression problem, wherein regression model is formulated as a non-convex joint optimization function for an asymmetric SAE. The method further comprises reformulating the non-convex joint optimization function as an Augmented Lagrangian formulation in terms of a plurality of proxy variables and a plurality of hyper parameters. The method comprises splitting the Augmented Lagrangian formulation into sub-problems using Alternating Direction Method of Multipliers and jointly learning parameters for the regression model to train the SAE for the regression problem. The learned weights enable estimating the unknown target values.

Method and system for incorporating regression into stacked auto encoder (SAE)

The present subject matter discloses a system and a method for identifying information from sensor data in a sensor agnostic manner. The system may receive sensor data provided by a sensor and may determine statistical features of the sensor data. The system may determine signal dynamics of the sensor data based on at least one of the statistical features, signal processing features, and a data distribution model. The system may select at least one outlier class based on the signal dynamics, number of streams of the sensor data, and dimensions of the sensor data. The system may select at least one outlier detection method associated with an outlier class for detecting outliers in the sensor data. The system may determine information content of the sensor data based on the outliers, the signal dynamics, the statistical features, and information theoretic features, and similarity or dissimilarity measure.

System and method for determining information and outliers from sensor data

A system(s) and method(s) for secure session establishment and secure encrypted exchange of data is disclosed. The system satisfies authentication requirement of general networking/communication systems. It provides an easy integration with systems already using schemes like DTLS-PSK. The system follows a cross layer approach in which session establishment is performed in a lightweight higher layer like the application layer. The system then passes resultant parameters of such session establishment including the session keys to a lower layer. The lower layer like the transport layer is then used by the system to perform channel encryption to allow exchange of encrypted data based on a cross layer approach, over a secure session. As the exchange of data becomes the responsibility of the lower layer like the transport layer, the data is protected from replay attacks since the transport layer record encryption mechanism provides that kind of protection.

Computer implemented system and method for secure session establishment and encrypted exchange of data

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Kolkata, India

Tulika Bose