International Journal of Computer Networks and Applications

44-56

Authors: Neha Tayal, Sangeeta Dhall, Shailender Gupta

Steganography is an art and science of hiding the secret information into a carrier such as image, audio etc. in order to conceal the existence of the data. It can be broadly classified into two categories: Spatial (Time) and Frequency domain. The former technique preserves the quality of the cover image while the latter technique provides robustness during the embedding process. As mentioned, both the techniques have their certain pros. Therefore, in this paper a hybrid scheme based on the merits of the two has been proposed. The scheme is implemented in MATLAB-10 and various performance metrics such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Correlation coefficient, Time Complexity, Bit Error Rate(BER), effect of Gaussian Noise & salt & paper noise on image are used to evaluate the efficacy of the proposed mechanism in comparison to others in literature. The results show that the proposed mechanism is highly robust to various kinds of attacks and has low time complexity.

63-69

Authors: Priyanka Joshi, Madhumita Chatterjee

With an upsurge in the use of internet, there are various attacks being launched every day. These attacks target the vulnerabilities of various computer resources, such as, the operating system, web browsers, toolbars, etc. along with the susceptibility of the users due to lack of awareness about the possible scams. The existing solutions suffer various drawbacks. The website phishing solutions fail when JavaScript is used in the webpage. The email phishing solution propose use of a special web browser instead of the existing popular ones, in order to secure the user from phishing emails. The tabnabbing solutions follow visual cues which are prone to false negatives. The proposed approach aims to resolve these issues and provides a solution to phishing through websites, email phishing and tabnabbing using web browser monitor and an email phishing detection module that uses Bayesian classifier, but in a way different from the way it was used in a solution proposed earlier. The system keeps sending popups to the user until the user closes the phishing page detected by the system, hence reducing the chance of the user getting masqueraded.