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Secure Approximation Of Edit Distance On Genomic Data, Md Momin Al Aziz, Dima Alhadidi, Noman Mohammed

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© 2017 The Author(s). Background: Edit distance is a well established metric to quantify how dissimilar two strings are by counting the minimum number of operations required to transform one string into the other. It is utilized in the domain of human genomic sequence similarity as it captures the requirements and leads to a better diagnosis of diseases. However, in addition to the computational complexity due to the large genomic sequence length, the privacy of these sequences are highly important. As these genomic sequences are unique and can identify an individual, these cannot be shared in a plaintext. Methods: In …