{"id":"https://openalex.org/W3216389486","doi":"https://doi.org/10.1109/isncc52172.2021.9615783","title":"Extending Direct Sequence Spread-Spectrum for Secure Communication","display_name":"Extending Direct Sequence Spread-Spectrum for Secure Communication","publication_year":2021,"publication_date":"2021-10-31","ids":{"openalex":"https://openalex.org/W3216389486","doi":"https://doi.org/10.1109/isncc52172.2021.9615783","mag":"3216389486"},"language":"en","primary_location":{"id":"doi:10.1109/isncc52172.2021.9615783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isncc52172.2021.9615783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Networks, Computers and Communications (ISNCC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059592615","display_name":"Avinash Kumar","orcid":"https://orcid.org/0000-0001-7953-0247"},"institutions":[{"id":"https://openalex.org/I102607778","display_name":"Cleveland State University","ror":"https://ror.org/002tx1f22","country_code":"US","type":"education","lineage":["https://openalex.org/I102607778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Avinash Kumar","raw_affiliation_strings":["Cleveland State University, Cleveland, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cleveland State University, Cleveland, USA","institution_ids":["https://openalex.org/I102607778"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101992277","display_name":"Ye Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I102607778","display_name":"Cleveland State University","ror":"https://ror.org/002tx1f22","country_code":"US","type":"education","lineage":["https://openalex.org/I102607778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ye Zhu","raw_affiliation_strings":["Cleveland State University, Cleveland, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cleveland State University, Cleveland, USA","institution_ids":["https://openalex.org/I102607778"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102607778"],"apc_list":null,"apc_paid":null,"fwci":0.8139,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.679727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10964","display_name":"Wireless Communication Security Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/direct-sequence-spread-spectrum","display_name":"Direct-sequence spread spectrum","score":0.9316315054893494},{"id":"https://openalex.org/keywords/spread-spectrum","display_name":"Spread spectrum","score":0.8699617385864258},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.804124116897583},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6859044432640076},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6497600674629211},{"id":"https://openalex.org/keywords/process-gain","display_name":"Process gain","score":0.5843466520309448},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5279608964920044},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.48307088017463684},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.43769511580467224},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.364840567111969},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.35326629877090454},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3522622883319855},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.26038578152656555},{"id":"https://openalex.org/keywords/code-division-multiple-access","display_name":"Code division multiple access","score":0.2420133352279663},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19814780354499817},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09699580073356628},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.07524362206459045}],"concepts":[{"id":"https://openalex.org/C194491627","wikidata":"https://www.wikidata.org/wiki/Q1334354","display_name":"Direct-sequence spread spectrum","level":4,"score":0.9316315054893494},{"id":"https://openalex.org/C105344744","wikidata":"https://www.wikidata.org/wiki/Q958957","display_name":"Spread spectrum","level":3,"score":0.8699617385864258},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.804124116897583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6859044432640076},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6497600674629211},{"id":"https://openalex.org/C198124995","wikidata":"https://www.wikidata.org/wiki/Q4075141","display_name":"Process gain","level":4,"score":0.5843466520309448},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5279608964920044},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.48307088017463684},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.43769511580467224},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.364840567111969},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.35326629877090454},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3522622883319855},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.26038578152656555},{"id":"https://openalex.org/C47696715","wikidata":"https://www.wikidata.org/wiki/Q233394","display_name":"Code division multiple access","level":2,"score":0.2420133352279663},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19814780354499817},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09699580073356628},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.07524362206459045},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isncc52172.2021.9615783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isncc52172.2021.9615783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Networks, Computers and Communications (ISNCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1572298868","https://openalex.org/W1977485163","https://openalex.org/W1980213939","https://openalex.org/W2022695516","https://openalex.org/W2060431793","https://openalex.org/W2062947382","https://openalex.org/W2077574412","https://openalex.org/W2096849803","https://openalex.org/W2109295013","https://openalex.org/W2116998814","https://openalex.org/W2133103811","https://openalex.org/W2158698691","https://openalex.org/W2736068844","https://openalex.org/W2756888089","https://openalex.org/W2798333393","https://openalex.org/W2886374543","https://openalex.org/W2890218181","https://openalex.org/W2957267905","https://openalex.org/W4205687621"],"related_works":["https://openalex.org/W4291802835","https://openalex.org/W2354227466","https://openalex.org/W4224302876","https://openalex.org/W69607479","https://openalex.org/W2392133287","https://openalex.org/W2374882508","https://openalex.org/W1881262264","https://openalex.org/W2079286573","https://openalex.org/W3216389486","https://openalex.org/W2720413303"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"to":[5,31,79],"extend":[6],"the":[7,44,80],"Direct":[8],"Sequence":[9],"Spread":[10,20],"Spectrum":[11,21],"(DSSS)":[12],"communication":[13,23,64],"scheme":[14],"with":[15,55,92],"a":[16,61],"Hidden":[17,56],"Markov":[18,57],"Model-based":[19],"(HSS)":[22],"scheme.":[24],"The":[25,75],"main":[26],"goal":[27],"of":[28,69,77],"HSS":[29,42,84],"is":[30,85],"defeat":[32],"existing":[33],"autocorrelation-based":[34,81],"attacks,":[35],"which":[36],"are":[37],"proven":[38],"effective":[39],"on":[40],"DSSS.":[41,93],"defeats":[43],"attacks":[45,82],"by":[46,72],"generating":[47],"chip":[48],"sequences":[49],"randomly":[50],"for":[51,83],"each":[52],"information":[53],"bit":[54],"Models.":[58],"HSS,":[59],"as":[60],"spread":[62],"spectrum":[63],"technique,":[65],"still":[66],"takes":[67],"advantage":[68],"benefits":[70],"brought":[71],"processing":[73],"gain.":[74],"cost":[76],"resistance":[78],"its":[86],"lower":[87],"BER":[88],"performance":[89],"in":[90],"comparison":[91]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}