ANALYSIS OF DATA HIDING ALGORITHMS FOR IMAGE SECURITY

The main goal of reversible data hiding algorithms is to embed the secret information in cover image and recover it back successfully. So we have implemented two methods. In first method, cover image is encrypted using stream cipher and pseudo randomly generated key and compressed using haar wavelet compression. The encrypted compressed image acts as a media for hiding secret image. And in second method, secret image is encrypted using randomly generated key and it is hidden in cover image. In both the method data hiding is done using LSB based image steganography. At the receiver, reverse process is done to extract secret image and recover cover image. At the end, we conclude that second method gives better security of image compared to method one

MULTI-MODAL BIO-METRIC AUTHENTICATION USING GABOR AND CANNY FILTERING METHOD

 Every human has unique biological features, which can be used for the person authentication. More than one biological feature can be used for authentication to achieve a higher degree of security. The proposed system uses fingerprint and iris biometric features for authentication purpose with Gabor and Canny filtering method. Gabor filters are linear filters applied in multiple directions to compensate for orientation effect. The proposed system uses Gabor filter with eight direction rotation. The canny filter is the multilevel algorithm that detects a wide range of edges with a low error rate in iris images. Fingerprint and iris both, when combined give the higher degree of security. The proposed system achieved 96% accuracy with 100 samples tested. Also, authentication approval error rate was almost zero, thus proposed system can be used in banks, secure government documents and military operations etc

Multi-modal Bio-metric Authentication Using Gabor And Canny Filtering Method

 Every human has unique biological features, which can be used for the person authentication. More than one biological feature can be used for authentication to achieve a higher degree of security. The proposed system uses fingerprint and iris biometric features for authentication purpose with Gabor and Canny filtering method. Gabor filters are linear filters applied in multiple directions to compensate for orientation effect. The proposed system uses Gabor filter with eight direction rotation. The canny filter is the multilevel algorithm that detects a wide range of edges with a low error rate in iris images. Fingerprint and iris both, when combined give the higher degree of security. The proposed system achieved 96% accuracy with 100 samples tested. Also, authentication approval error rate was almost zero, thus proposed system can be used in banks, secure government documents and military operations etc

Factors Affecting the Usage of Wearable Device Technology for Healthcare among Indian Adults: A Cross-Sectional Study

Background: Wearable device technology has recently been involved in the healthcare industry substantially. India is the world’s third largest market for wearable devices and is projected to expand at a compound annual growth rate of ~26.33%. However, there is a paucity of literature analyzing the factors determining the acceptance of wearable healthcare device technology among low-middle-income countries. Methods: This cross-sectional, web-based survey aims to analyze the perceptions affecting the adoption and usage of wearable devices among the Indian population aged 16 years and above. Results: A total of 495 responses were obtained. In all, 50.3% were aged between 25–50 years and 51.3% belonged to the lower-income group. While 62.2% of the participants reported using wearable devices for managing their health, 29.3% were using them daily. technology and task fitness (TTF) showed a significant positive correlation with connectivity (r = 0.716), health care (r = 0.780), communication (r = 0.637), infotainment (r = 0.598), perceived usefulness (PU) (r = 0.792), and perceived ease of use (PEOU) (r = 0.800). Behavioral intention (BI) to use wearable devices positively correlated with PEOU (r = 0.644) and PU (r = 0.711). All factors affecting the use of wearable devices studied had higher mean scores among participants who were already using wearable devices. Male respondents had significantly higher mean scores for BI (p = 0.034) and PEOU (p = 0.009). Respondents older than 25 years of age had higher mean scores for BI (p = 0.027) and Infotainment (p = 0.032). Conclusions: This study found a significant correlation with the adoption and acceptance of wearable devices for healthcare management in the Indian context