Efficient secure surveillance on smart healthcare IoT system through cosine-transform encryption
The emerging technologies with IoT (Internet of Things) systems are elevated as a prototype and combination of the smart connectivity ecosystem. These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organi...
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Veröffentlicht in: | Journal of intelligent & fuzzy systems 2021-01, Vol.40 (1), p.1417-1442 |
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creator | Khan, Jalaluddin Li, Jian Ping Haq, Amin Ul Khan, Ghufran Ahmad Ahmad, Sultan Abdullah Alghamdi, Abdulrahman Golilarz, Noorbakhsh Amiri |
description | The emerging technologies with IoT (Internet of Things) systems are elevated as a prototype and combination of the smart connectivity ecosystem. These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organized diagnosis process, intensive support and care against the traditional healthcare operations. But facilitating these highly technological adaptations, the preserving personal information of the patients are on the risk with data leakage and privacy theft in the current revolution. Concerning secure protection and privacy theft of the patient’s information. We emphasized this paper on secure monitoring with the help of intelligently recorded summary’s keyframe extraction and applied two rounds lightweight cosine-transform encryption. This article includes firstly, a regimented process of keyframe extraction which is employed to retrieve meaningful frames of image through visual sensor with sending alert (quick notice) to authority. Secondly, employed two rounds of lightweight cosine-transform encryption operation of agreed (detected) keyframes to endure security and safety for the further any kinds of attacks from the adversary. The combined methodology corroborates highly usefulness with engendering appropriate results, little execution of encryption time (0.2277-0.2607), information entropy (7.9996), correlation coefficient (0.0010), robustness (NPCR 99.6383, UACI 33.3516), uniform histogram deviation (R 0.0359, G 0.0492, B 0.0582) and other well adopted secure ideology than any other keyframe or image encryption approaches. Furthermore, this incorporating method can effectively reduce vital communication cost, bandwidth issues, storage, data transmission cost and effective timely judicious analysis over the occurred activities and keep protection by using effective encryption methodology to remain attack free from any attacker or adversary, and provide confidentiality about patient’s privacy in the smart healthcare system. |
doi_str_mv | 10.3233/JIFS-201770 |
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These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organized diagnosis process, intensive support and care against the traditional healthcare operations. But facilitating these highly technological adaptations, the preserving personal information of the patients are on the risk with data leakage and privacy theft in the current revolution. Concerning secure protection and privacy theft of the patient’s information. We emphasized this paper on secure monitoring with the help of intelligently recorded summary’s keyframe extraction and applied two rounds lightweight cosine-transform encryption. This article includes firstly, a regimented process of keyframe extraction which is employed to retrieve meaningful frames of image through visual sensor with sending alert (quick notice) to authority. Secondly, employed two rounds of lightweight cosine-transform encryption operation of agreed (detected) keyframes to endure security and safety for the further any kinds of attacks from the adversary. The combined methodology corroborates highly usefulness with engendering appropriate results, little execution of encryption time (0.2277-0.2607), information entropy (7.9996), correlation coefficient (0.0010), robustness (NPCR 99.6383, UACI 33.3516), uniform histogram deviation (R 0.0359, G 0.0492, B 0.0582) and other well adopted secure ideology than any other keyframe or image encryption approaches. Furthermore, this incorporating method can effectively reduce vital communication cost, bandwidth issues, storage, data transmission cost and effective timely judicious analysis over the occurred activities and keep protection by using effective encryption methodology to remain attack free from any attacker or adversary, and provide confidentiality about patient’s privacy in the smart healthcare system.</description><identifier>ISSN: 1064-1246</identifier><identifier>EISSN: 1875-8967</identifier><identifier>DOI: 10.3233/JIFS-201770</identifier><language>eng</language><publisher>Amsterdam: IOS Press BV</publisher><subject>Correlation coefficients ; Cost analysis ; Data transmission ; Encryption ; Entropy (Information theory) ; Health care ; Histograms ; Internet of medical things ; Internet of Things ; Lightweight ; Medical imaging ; Monitoring ; New technology ; Privacy ; Telemedicine ; Theft</subject><ispartof>Journal of intelligent & fuzzy systems, 2021-01, Vol.40 (1), p.1417-1442</ispartof><rights>Copyright IOS Press BV 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c303t-5950bae8fcf21229f05b2fac1444222cb509dc138b7bb759f838993f3d944eef3</citedby><cites>FETCH-LOGICAL-c303t-5950bae8fcf21229f05b2fac1444222cb509dc138b7bb759f838993f3d944eef3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Khan, Jalaluddin</creatorcontrib><creatorcontrib>Li, Jian Ping</creatorcontrib><creatorcontrib>Haq, Amin Ul</creatorcontrib><creatorcontrib>Khan, Ghufran Ahmad</creatorcontrib><creatorcontrib>Ahmad, Sultan</creatorcontrib><creatorcontrib>Abdullah Alghamdi, Abdulrahman</creatorcontrib><creatorcontrib>Golilarz, Noorbakhsh Amiri</creatorcontrib><title>Efficient secure surveillance on smart healthcare IoT system through cosine-transform encryption</title><title>Journal of intelligent & fuzzy systems</title><description>The emerging technologies with IoT (Internet of Things) systems are elevated as a prototype and combination of the smart connectivity ecosystem. These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organized diagnosis process, intensive support and care against the traditional healthcare operations. But facilitating these highly technological adaptations, the preserving personal information of the patients are on the risk with data leakage and privacy theft in the current revolution. Concerning secure protection and privacy theft of the patient’s information. We emphasized this paper on secure monitoring with the help of intelligently recorded summary’s keyframe extraction and applied two rounds lightweight cosine-transform encryption. This article includes firstly, a regimented process of keyframe extraction which is employed to retrieve meaningful frames of image through visual sensor with sending alert (quick notice) to authority. Secondly, employed two rounds of lightweight cosine-transform encryption operation of agreed (detected) keyframes to endure security and safety for the further any kinds of attacks from the adversary. The combined methodology corroborates highly usefulness with engendering appropriate results, little execution of encryption time (0.2277-0.2607), information entropy (7.9996), correlation coefficient (0.0010), robustness (NPCR 99.6383, UACI 33.3516), uniform histogram deviation (R 0.0359, G 0.0492, B 0.0582) and other well adopted secure ideology than any other keyframe or image encryption approaches. Furthermore, this incorporating method can effectively reduce vital communication cost, bandwidth issues, storage, data transmission cost and effective timely judicious analysis over the occurred activities and keep protection by using effective encryption methodology to remain attack free from any attacker or adversary, and provide confidentiality about patient’s privacy in the smart healthcare system.</description><subject>Correlation coefficients</subject><subject>Cost analysis</subject><subject>Data transmission</subject><subject>Encryption</subject><subject>Entropy (Information theory)</subject><subject>Health care</subject><subject>Histograms</subject><subject>Internet of medical things</subject><subject>Internet of Things</subject><subject>Lightweight</subject><subject>Medical imaging</subject><subject>Monitoring</subject><subject>New technology</subject><subject>Privacy</subject><subject>Telemedicine</subject><subject>Theft</subject><issn>1064-1246</issn><issn>1875-8967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNotkE1LAzEQhoMoWKsn_0DAo0Tz2WyOUqpWCh6s5zWbTtwt26QmWaH_3i31MMwcHublfRC6ZfRBcCEe35bPH4RTpjU9QxNWaUUqM9Pn401nkjAuZ5foKuctHRnF6QR9LbzvXAeh4AxuSIDzkH6h63sbHOAYcN7ZVHALti-tsyOwjGucD7nADpc2xeG7xS7mLgApyYbsY9phCC4d9qWL4RpdeNtnuPnfU_T5vFjPX8nq_WU5f1oRJ6goRBlFGwuVd54zzo2nquHeOial5Jy7RlGzcUxUjW4arYyvRGWM8GJjpATwYoruTn_3Kf4MkEu9jUMKY2TNpVZMCDnOFN2fKJdizgl8vU_dWPBQM1ofFdZHhfVJofgDpHBlOQ</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Khan, Jalaluddin</creator><creator>Li, Jian Ping</creator><creator>Haq, Amin Ul</creator><creator>Khan, Ghufran Ahmad</creator><creator>Ahmad, Sultan</creator><creator>Abdullah Alghamdi, Abdulrahman</creator><creator>Golilarz, Noorbakhsh Amiri</creator><general>IOS Press BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20210101</creationdate><title>Efficient secure surveillance on smart healthcare IoT system through cosine-transform encryption</title><author>Khan, Jalaluddin ; Li, Jian Ping ; Haq, Amin Ul ; Khan, Ghufran Ahmad ; Ahmad, Sultan ; Abdullah Alghamdi, Abdulrahman ; Golilarz, Noorbakhsh Amiri</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c303t-5950bae8fcf21229f05b2fac1444222cb509dc138b7bb759f838993f3d944eef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Correlation coefficients</topic><topic>Cost analysis</topic><topic>Data transmission</topic><topic>Encryption</topic><topic>Entropy (Information theory)</topic><topic>Health care</topic><topic>Histograms</topic><topic>Internet of medical things</topic><topic>Internet of Things</topic><topic>Lightweight</topic><topic>Medical imaging</topic><topic>Monitoring</topic><topic>New technology</topic><topic>Privacy</topic><topic>Telemedicine</topic><topic>Theft</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Khan, Jalaluddin</creatorcontrib><creatorcontrib>Li, Jian Ping</creatorcontrib><creatorcontrib>Haq, Amin Ul</creatorcontrib><creatorcontrib>Khan, Ghufran Ahmad</creatorcontrib><creatorcontrib>Ahmad, Sultan</creatorcontrib><creatorcontrib>Abdullah Alghamdi, Abdulrahman</creatorcontrib><creatorcontrib>Golilarz, Noorbakhsh Amiri</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of intelligent & fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Khan, Jalaluddin</au><au>Li, Jian Ping</au><au>Haq, Amin Ul</au><au>Khan, Ghufran Ahmad</au><au>Ahmad, Sultan</au><au>Abdullah Alghamdi, Abdulrahman</au><au>Golilarz, Noorbakhsh Amiri</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Efficient secure surveillance on smart healthcare IoT system through cosine-transform encryption</atitle><jtitle>Journal of intelligent & fuzzy systems</jtitle><date>2021-01-01</date><risdate>2021</risdate><volume>40</volume><issue>1</issue><spage>1417</spage><epage>1442</epage><pages>1417-1442</pages><issn>1064-1246</issn><eissn>1875-8967</eissn><abstract>The emerging technologies with IoT (Internet of Things) systems are elevated as a prototype and combination of the smart connectivity ecosystem. These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organized diagnosis process, intensive support and care against the traditional healthcare operations. But facilitating these highly technological adaptations, the preserving personal information of the patients are on the risk with data leakage and privacy theft in the current revolution. Concerning secure protection and privacy theft of the patient’s information. We emphasized this paper on secure monitoring with the help of intelligently recorded summary’s keyframe extraction and applied two rounds lightweight cosine-transform encryption. This article includes firstly, a regimented process of keyframe extraction which is employed to retrieve meaningful frames of image through visual sensor with sending alert (quick notice) to authority. Secondly, employed two rounds of lightweight cosine-transform encryption operation of agreed (detected) keyframes to endure security and safety for the further any kinds of attacks from the adversary. The combined methodology corroborates highly usefulness with engendering appropriate results, little execution of encryption time (0.2277-0.2607), information entropy (7.9996), correlation coefficient (0.0010), robustness (NPCR 99.6383, UACI 33.3516), uniform histogram deviation (R 0.0359, G 0.0492, B 0.0582) and other well adopted secure ideology than any other keyframe or image encryption approaches. Furthermore, this incorporating method can effectively reduce vital communication cost, bandwidth issues, storage, data transmission cost and effective timely judicious analysis over the occurred activities and keep protection by using effective encryption methodology to remain attack free from any attacker or adversary, and provide confidentiality about patient’s privacy in the smart healthcare system.</abstract><cop>Amsterdam</cop><pub>IOS Press BV</pub><doi>10.3233/JIFS-201770</doi><tpages>26</tpages></addata></record> |
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subjects | Correlation coefficients Cost analysis Data transmission Encryption Entropy (Information theory) Health care Histograms Internet of medical things Internet of Things Lightweight Medical imaging Monitoring New technology Privacy Telemedicine Theft |
title | Efficient secure surveillance on smart healthcare IoT system through cosine-transform encryption |
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