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Protecting sensitive visual data from unauthorized access drives the pursuit of advanced image encryption methods. This paper proposes a novel approach to enhance image encryption by combining the power of a chaotic map, elliptic curve cryptography, and genetic algorithm. The chaotic map, specifically Arnold\u2019s cat map, is employed to introduce chaos and randomness into the encryption process. The proposed image encryption process involves applying Arnold\u2019s cat map for shuffling the pixel positions, followed by elliptic curve cryptography for encrypting the pixel values using public and private keys. Additionally, a genetic algorithm is employed to optimize the key generation process, enhancing the security of the encryption scheme. The combined utilization of these techniques aims to achieve a high level of confidentiality and robustness in image encryption. The algorithm underwent thorough analysis. It achieved a maximum entropy score of 7.99, indicating a high level of randomness and unpredictability in the encrypted data. Additionally, it exhibited near-zero correlation, which suggests strong resistance against statistical attacks. Moreover, the cryptographic range of possible keys was found to be\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$2^{511}$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:msup>\n                            <mml:mn>2<\/mml:mn>\n                            <mml:mn>511<\/mml:mn>\n                          <\/mml:msup>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    . This extensive key space makes the algorithm highly resilient against brute force attacks. It took only 0.5634\u00a0s to encrypt a moderately sized\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$512\\times 512$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mrow>\n                            <mml:mn>512<\/mml:mn>\n                            <mml:mo>\u00d7<\/mml:mo>\n                            <mml:mn>512<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    pixel image with an 8-bit image on a standard desktop computer with a 2.3 GHz processor and 16 GB of RAM. The experimental findings confirm that the proposed approach is highly effective and efficient in safeguarding sensitive image data from unauthorized access and potential attacks. This scheme has the benefit of allowing us to protect our private image data while it\u2019s being transmitted.\n                  <\/jats:p>","DOI":"10.1007\/s10462-024-10719-0","type":"journal-article","created":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T17:22:41Z","timestamp":1710264161000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":174,"title":["A chaotic based image encryption scheme using elliptic curve cryptography and genetic algorithm"],"prefix":"10.1007","volume":"57","author":[{"given":"Sanjay","family":"Kumar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepmala","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,3,12]]},"reference":[{"issue":"10","key":"10719_CR1","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1016\/j.aeue.2012.01.015","volume":"66","author":"AH Abdullah","year":"2012","unstructured":"Abdullah AH, Enayatifar R, Lee M (2012) A hybrid genetic algorithm and chaotic function model for image encryption. 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