Tamper-Evident Complex Genomic Networks
This addresses a security issue for administrators managing genomic networks, but it is incremental as it applies existing techniques to a new domain.
The paper tackles the problem of network data not being tamper-evident, which is critical for storing personal genomic information, and presents a scheme using cryptographic and ego-based network analytic methods to detect changes, with results from experiments demonstrating its validity.
Networks are important storage data structures now used to store personal information of individuals around the globe. With the advent of personal genome sequencing, networks are going to be used to store personal genomic sequencing of people. In contrast to social media networks, the importance of relationships in this genomic network is extremely significant. Losing connections between individuals thus implies losing relationship information (E.g. father or son etc.). There currently exists a considerably serious problem in the current approach to storing network data. Simply stated, network data is not tamper-evident. In other words, if some links or nodes were changed/removed/added by a malicious attacker, it would be impossible for the administrator to detect such changes. While, in the current age of social media networks, change in node characteristics and links can be bad in terms of relationships, in the case of networks for storing personal genomes, the results could be truly devastating. Here we present a scheme for building tamper-evident networks using a combination of Cryptographic and Ego-based Network analytic methods. Using actual published data-sets, we also demonstrate the utility and validity of the scheme besides demonstrating its working in various possible scenarios of usage. Results from the extensive experiments demonstrate the validity of the proposed approach.