| Digital traffic over the Internet is continuing to grow rapidly. This mounting traffic can cause adverse effects on the cost and expediency of sending data files. To alleviate this load, data compression is used to accurately represent data within the fewest bits possible. For many applications - e.g., confidential transmission, video surveillance, and other military and medical applications - data security is also a requirement. For these applications, both encryption and compression need to be performed. In order for compression to be successful, redundancies within the data must be removed. Because encryption hides redundancies within a data set, most existing compression and encryption methods must compress a file before encrypting it. If the file has little redundancy to begin with - as is the case with an already-encrypted file - these systems will provide a suboptimal compression ratio. In many cases, the compression operation will actually inflate the size of the file that was intended to be compressed.;This thesis provides a coding solution which both simultaneously compresses and encrypts digital data through implementation of a key-dependent compression algorithm. This algorithm minimizes computational cost and provides a theoretically secure encryption without compromising the optimal compression ratio. A detailed, region-dependent framework utilizing the coding algorithm for image compression is presented which provides equivalent or better compression ratios in comparison to other contemporary compression standards and can be adapted to lossy, high compression ratio implementations. It is suitable for use on already-encrypted files. |
