A Secure Data Infrastructure for Personal Manufacturing Based on a Novel Key-Less, Byte-Less Encryption Method
【Author】 Vedeshin, Anton; Dogru, John Mehmet Ulgar; Liiv, Innar; Ben Yahia, Sadok; Draheim, Dirk
【Source】IEEE ACCESS
【影响因子】3.476
【Abstract】We are witnessing the advent of personal manufacturing, where home users and small and medium enterprises manufacture products locally, at the point and time of need. The impressively fast adoption of these technologies indicates this approach to manufacturing can become a key enabler of the real-time economy of the future. In this paper, we contribute a secure and dependable infrastructure and architecture for that new paradigm. Our solution leverages physical limitations of the computational process into a defense strategy that makes distributed file storage and transfer highly secure. The main idea is to replace asymmetric or public-key encryption functions with an unkeyed, collision, second preimage, and preimage resistant cryptographic hash function. Such a cryptosystem does not have an inverse function . We challenge each block hash against the full hash table to recreate the original message. To illustrate the approach, we describe secured protocols that provide a number of desirable properties during both data storage and streaming. Similar to proof-of-work blockchain consensus algorithms, we parameterized the solution based on the amount of infrastructure available. Experiments show the proposed method can recalculate hashes for a 3-dimensional of 256(3) at an average of 14 revisions per second, and one revision every 5 minutes for a bigger matrix of 4096(3). The increase in cloud infrastructure cost is insignificant compared to the level of protection offered.
【Keywords】Communication system security; computer aided manufacturing; content distribution networks; data security; data storage systems; distributed computing; information security; intelligent manufacturing systems; technology social factors; virtual manufacturing
【发表时间】2020
【收录时间】2022-01-02
【文献类型】
【主题类别】
--
评论