Publication Type:

Journal Article

Source:

International Journal of Pure and Applied Mathematics, Volume 118, Number 18, p.3017-3025 (2018)

Abstract:

In the current world scenario storing of any data securely in any storage medium is of major concern. Transferring any secret data without being compromised by the attacker is becoming difficult day by day. In such a situation, using the slack space for storing and retrieving secret information can be a great boon. Slack space is nothing but the unused space in a disk cluster. Here, the slack space of private cloud and slack space of the files which is being uploaded to the private cloud is considered for hiding and retrieving the secret information. Slack sizes of files are determined using hex editors. MD5 hashes of the path of the files containing slack and key are taken and sorted in the ascending order. Message to be hidden is encrypted and is divided into chunks of data depending on slack sizes of files which has been reordered by its corresponding sorting of MD5 hashes of file paths along with the key. Divided chunks of data are hidden in the slack spaces accordingly. Mapping of MD5 hashes of file paths along with the key and slack size will help in the retrieval of hidden information from slack spaces. The secret data will be securely hidden in the slack spaces of the private cloud. The idea of keeping secret data in slack space of private cloud is more advantageous because cloud itself provides security than usual physical storage media and moreover that, the possibility of being detected by an attacker is often less as slack space often contains data which could not be easily detected by normal analysis. Along with this, a secret sharing algorithm is proposed for splitting and sharing the secret data among cloud users and the file slack space in the cloud gives the accessibility of secret data

Cite this Research Publication

Ashok Kumar Mohan, Thampy, R. V., and Praveen, K., “Data Hiding in Slack Space Revisited”, International Journal of Pure and Applied Mathematics, vol. 118, pp. 3017-3025, 2018.