Image steganography is a technique for concealing sensitive data inside an image. The conventional image steganography method secures sensitive information in the host image, so the payload capability is almost overlooked, and steganographic image quality for the Human Visual System (HVS) needs to be enhanced. As a result, we proposed a new deep learning-based multiple image steganography approach in this work. The secret image is embedded into the cover image using a Deep Neural Network (DNN), and the embedded cover image is then encrypted using Elliptic Curve Cryptography (ECC) to reinforce the anti-detection property of the obtained image. The Deep Neural Network is a combination of Pre-processing, Hiding, and Revealing networks that enable steganography and extraction of full-size images to enhance steganographic performance. The results of the experiments show that the network can successfully embed up to three secret images into the cover image without causing a major difference in the Structural Similarity Index (SSIM). Furthermore, the image obtained using this steganography method has higher SSIM and Peak Signal-to-Noise Ratio (PSNR) values, reaching 0.99 and 35dB, respectively, using this steganography method.

A secret-sharing scheme is a method by which a dealer distributes shares to parties such that only authorized subsets of parties can reconstruct the secret. Secret-sharing schemes are important tools in cryptography and they are used as a building box in many secure protocols, e.g., general protocol for multiparty computation, Byzantine agreement, threshold cryptography, access control, attribute-based encryption, and generalized oblivious transfer. In this work, I have described the most important constructions of secret-sharing schemes, explaining the connections between secret-sharing schemes and monotone formulae and monotone span programs. The main problem with known secret-sharing schemes is the large share size: it is exponential in the number of parties. I conjecture that this is unavoidable. I have discussed the known lower bounds on the share size. These lower bounds are fairly weak and there is a big gap between the lower and upper bounds. For linear secret-sharing schemes, which is a class of schemes based on linear algebra that contains the most known schemes, super-polynomial lower bounds on the share size are known. I have described the proofs of these lower bounds.

Developed an Automatic Irrigation System using Sensor Technology with Microcontroller to automate the process of irrigation in agricultural fields.

GSM BASED SECURITY SYSTEM which provides security to our belongings from any remote location. If intruders try to break the security system, there shall be an automatic SMS from the system to the registered mobile number and after 10 seconds an alarm will go off.