Data Compression and Encryption for Multimedia

Background:

With mobile high-speed networks evolving from 5G to 6G and the advent of edge and quantum computing, coupled with the explosive growth of social media and downloadable entertainment, large-file (high-resolution) multimedia consumption is at an all-time high. As a result, the hardware industry has advanced to parallel user demand for high-resolution multimedia. With this growth in multimedia consumption comes the need for better data compression and encryption, factors that ensure the transmissivity and integrity of the file being transferred/shared/accessed.

To address the growing demand for data compression and encryption, numerous algorithms were developed that shared one common thread: data compression and encryption happen in separate phases, and the user must decide the order of encrypting or compressing data first, depending on the types of attacks he/she needs to circumnavigate. Initially, it was thought that the only way to combine encryption and compression was to compress the data before encryption. This is due to the fact that compression relies on patterns in data to function, while encryption attempts to destroy these patterns in data. The method of compression then encryption has been found to be weak to side-channel attacks. These types of attacks use JavaScript code to perform a brute force attack on the victim’s browser, allowing the attacker to infer what the transmitted data is based on the size of that compressed data.

What is needed is a method for enabling data compression and encryption at the same time. Such an approach would not only streamline data management (by being less taxing on the hardware involved) but offer stronger resilience to various types of cyberattacks.

Technology Overview:

The inventors have developed a novel means of concurrently compressing and encrypting data. More specifically, the invention is a cost-effective encryption method of files as a built-in component of a lossless compression algorithm that avoids the added cost of employing two separate processes -- data compression, and data encryption. This technology builds upon Burrows Wheeler with Inversion Coder (BWIC), which the lead inventor developed in 2004. SUNY’s novel approach further reduces computing resources and security vulnerability, thus reducing the operational cost of data management.

Advantages:

• Lower cost of deployment
• Greater data security
• More streamlined approach to data management
• Scalability across the broader data/multimedia businesses

Applications:

• Computing
• Telecommunication
• Media/entertainment
• Medical imaging

Intellectual Property Summary:

Patent application filed

Stage of Development:

Theoretic feasibility demonstrated via computational modeling.

Licensing Status:

Available for license. Inventors at SUNY are seeking a commercial partner for licensing and/or collaboration opportunities for research activities in this area.