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Optimizing the same using one fitness function may not be a good choice, as it can result in different outcomes concerning other fitness functions. The proposed work initially encrypts the given image using chaotic function and DNA masks. Further, GA uses two fitness functions \u2013 entropy with correlation coefficient (CC), entropy with unified average changing intensity (UACI), and entropy with number of pixel change rate (NPCR) \u2013 simultaneously to optimize the encrypted data in the second stage. The bi-objective optimization using entropy with CC shows significant performance gain over the single-objective GA optimization for image encryption.<\/jats:p>","DOI":"10.1515\/jisys-2017-0069","type":"journal-article","created":{"date-parts":[[2017,8,18]],"date-time":"2017-08-18T06:01:18Z","timestamp":1503036078000},"page":"333-346","source":"Crossref","is-referenced-by-count":13,"title":["A Bi-objective Genetic Algorithm Optimization of Chaos-DNA Based Hybrid Approach"],"prefix":"10.1515","volume":"28","author":[{"given":"Shelza","family":"Suri","sequence":"first","affiliation":[{"name":"Department of Electronics , Banasthali Vidyapith , Banasthali, Rajasthan , India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ritu","family":"Vijay","sequence":"additional","affiliation":[{"name":"Department of Electronics , Banasthali Vidyapith , Banasthali, Rajasthan , India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2017,8,18]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"A. 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