Scalable Stream Encryption With Synchronized State Machines
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Solution Overview
Problem
Existing encryption methods are inefficient and insecure, particularly in real-time data streams, as they require decryption of encrypted files to convert to different encryption formats, exposing content to interception and are computationally intensive, and password/key management is cumbersome.
Innovation Solution
A transcoder system that uses synchronized state machines with pseudo-random number generators to increase the complexity of the encryption problem space, employing context-based deterministic number generation and scalable encryption schemes to maintain security without significant CPU resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional decryption and re-encryption process is used to convert encrypted files to different encryption formats, then the content can be converted to different formats, but the content is exposed to interception during the conversion process and the process is computationally intensive
Solution Approach 1:
The patent introduces a transcoder system that acts as an intermediary between different encryption formats. Instead of decrypting to plain text and then re-encrypting, the transcoder performs format conversion while maintaining encryption throughout the process, using synchronized state machines to coordinate the conversion without exposing the content.
Solution Approach 2:
The system performs preliminary setup by establishing synchronized state machines and shared secret keys before the actual conversion process. This preliminary configuration enables the transcoder to directly transform encrypted data from one format to another without needing to decrypt it first, preventing exposure during conversion.
2Productivity
If encryption is scaled to the end user application to minimize CPU usage, then customer experience is improved, but managing encryption for millions of users becomes more difficult
Solution Approach 1:
The transcoder system provides a universal encryption management platform that serves multiple functions: it manages encryption for millions of users, performs format conversions, and maintains security policies centrally. This multi-functional system reduces the burden on individual user applications while maintaining scalability.
Solution Approach 2:
The system segments encryption management into separate functional components: key generation, format conversion, and policy enforcement. This segmentation allows each component to be optimized independently and managed at appropriate levels, reducing overall system complexity while maintaining scalability across millions of users.
3Duration of action of stationary object
If the safe time of a cipher key is increased by using more complex algorithms and CPU power, then the encrypted data safe time is extended, but consumer IoT devices are left behind in encryption making them the attack vector
Solution Approach 1:
The system changes the parameters of encryption by using synchronized state machines with pseudo-random number generators instead of relying solely on algorithm complexity. This approach extends the safe time of encrypted data through deterministic randomness that is computationally efficient, allowing both high-security applications and consumer IoT devices to use the same encryption scheme at appropriate complexity levels.
Data Source
AI summary
Information security systems and methods are presented including synchronized state machines operating with private data and tamper-evident identifiers that expand the problem space of attacks by unauthorized consumers of data in flight or rest to near infinity. A quantum cryptography-resistant distribution network for identity, trust relationship, encryption, and transcoding of valuable information is described where a priori knowledge of the hardware or software is irrelevant to the safe time for the data protected and modified as needed within a multikey encryption and data control and availability assurance domains. Due to its low compute design, the methods described within are well suited for a variety of tasks including real-time data streams such as video and audio distribution.