This paper explores the spatial coverage potential of a vision sensor to implement a dual service for a museum security system. Services include object monitoring and invisible visual Multiple-Input and Multiple-Output (MIMO) communication. For object monitoring, the Kalman filter algorithm is used. To implement a secret visual MIMO communication, an Adaptive Row-Column (ARC)-based LSB substitution technique is used along with the Integer Wavelet Transform method. These proposed services are implemented using existing electronic visual displays and surveillance cameras. Experiments are carried out using a sample object and four stego images. The performance of the object tracking system is measured in terms of accuracy by comparing the actual and estimated position of an object. Similarly, the performance of the covert visual MIMO system is measured at two different stages. On the transmitter side, differences between the cover and stego-images are used to measure imperceptibility. Likewise, at the receiver, differences between the original and the reconstructed data images are used to measure the accuracy. Results illustrate that the proposed system has improved imperceptibility, accuracy, and robustness, as compared to existing techniques.
The exchange of sensitive digital information has increased significantly in the last decade due to the internet’s growth and availability. More robust encryption techniques were introduced to secure the data-in-transit and data-at-rest. The strength of these encryption algorithms depends on the keys. Keys are generated using Pseudorandom Number Generators (PRNG). The key generation algorithm defines these PRNGs. Although there are many robust key generation algorithms, there is a demand for new key generation algorithms to break hackers’ experience and knowledge. This paper proposed a new key generation algorithm using value generated from sudoku matrices and synthetic color image. 8 × 8 sudoku matrices are generated randomly for each session. These sudoku matrices are solved using backtracking and recursive programming. The solved sudoku matrices are used to extract bits from pixels of the synthetic color image. The extracted bits are then combined to form a key. Further, randomness in the key is tested using the NIST (National Institute of Standards and Technology).
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