{"id":"https://openalex.org/W4385324695","doi":"https://doi.org/10.1145/3603781.3603906","title":"Detection of Network Time Covert Channels Based on Image Processing","display_name":"Detection of Network Time Covert Channels Based on Image Processing","publication_year":2023,"publication_date":"2023-05-26","ids":{"openalex":"https://openalex.org/W4385324695","doi":"https://doi.org/10.1145/3603781.3603906"},"language":"en","primary_location":{"id":"doi:10.1145/3603781.3603906","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3603781.3603906","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","raw_type":"proceedings-article"},"type":"article","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/A5101688595","display_name":"Xuwen Huang","orcid":"https://orcid.org/0009-0005-5666-4556"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuwen Huang","raw_affiliation_strings":["Huaqiao University, China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University, China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006664711","display_name":"Yonghong Chen","orcid":"https://orcid.org/0009-0000-9030-0266"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghong Chen","raw_affiliation_strings":["Huaqiao University, China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University, China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037063481","display_name":"Zhiqiang Li","orcid":"https://orcid.org/0009-0004-7706-6734"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Li","raw_affiliation_strings":["Huaqiao University, China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University, China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034784917","display_name":"Zhan Teng","orcid":"https://orcid.org/0000-0002-2680-6892"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Teng Zhan","raw_affiliation_strings":["Huaqiao University, China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University, China","institution_ids":["https://openalex.org/I119045251"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101688595"],"corresponding_institution_ids":["https://openalex.org/I119045251"],"apc_list":null,"apc_paid":null,"fwci":0.246,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51330143,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"701","last_page":"707"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9995999932289124,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7304524779319763},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4965687394142151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46508851647377014},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4270496964454651},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4260396361351013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7304524779319763},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4965687394142151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46508851647377014},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4270496964454651},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4260396361351013}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3603781.3603906","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3603781.3603906","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","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":23,"referenced_works":["https://openalex.org/W1504573138","https://openalex.org/W2099593264","https://openalex.org/W2117539524","https://openalex.org/W2132177566","https://openalex.org/W2194775991","https://openalex.org/W2267282851","https://openalex.org/W2883780447","https://openalex.org/W2951498981","https://openalex.org/W3114468998","https://openalex.org/W3116036149","https://openalex.org/W3138516171","https://openalex.org/W3162068173","https://openalex.org/W3215039338","https://openalex.org/W3216623900","https://openalex.org/W3217570085","https://openalex.org/W4206307994","https://openalex.org/W4226054955","https://openalex.org/W4300981723","https://openalex.org/W4312443924","https://openalex.org/W4318832544","https://openalex.org/W4321021237","https://openalex.org/W6601290046","https://openalex.org/W6603884005"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Abstract:":[0],"Network":[1],"covert":[2],"timing":[3],"channels":[4,61],"(NCTCs)":[5],"utilize":[6],"Inter-Packet":[7],"Delay":[8],"(IPD)":[9],"encoding":[10],"to":[11,27,77],"hide":[12],"data.":[13],"It":[14],"can":[15],"be":[16],"used":[17],"for":[18,57,93,103,180],"spreading":[19],"malware":[20],"and":[21,43,62,97,120,125,130,142,173],"data":[22,110],"leakage,":[23],"posing":[24],"severe":[25],"threats":[26],"network":[28,101,168],"security.":[29],"With":[30],"the":[31,34,47,99,159],"increasing":[32],"risk,":[33],"research":[35],"on":[36,51],"NCTC":[37],"detection":[38,48,71,171,181],"has":[39],"become":[40],"an":[41],"important":[42],"urgent":[44],"task.":[45],"However,":[46],"methods":[49,72],"based":[50],"IPD":[52,65,95,107,161,177],"statistics":[53],"are":[54],"only":[55],"effective":[56,157],"few":[58],"types":[59],"of":[60],"require":[63],"large":[64],"sampling":[66,178],"samples.":[67],"The":[68,166],"recent":[69],"ML-based":[70],"have":[73],"multiple":[74],"limitations":[75],"due":[76],"their":[78],"coarse-grained":[79],"feature":[80,151],"extraction":[81,152,162],"method.":[82,165],"In":[83],"this":[84],"paper,":[85],"we":[86,136],"propose":[87],"a":[88,143],"multi-channel":[89],"image":[90,134,139,153,163],"transformation":[91,164],"method":[92],"extracting":[94],"features":[96],"select":[98],"lightweight":[100],"MobileVit":[102,167],"detection.":[104],"We":[105],"encode":[106],"one-dimensional":[108],"time-series":[109],"into":[111,128],"Gramian":[112],"Angular":[113],"Field":[114,118],"(GAF),":[115],"Markov":[116],"Transition":[117],"(MTF),":[119],"Recurrence":[121],"plot":[122],"(RP)":[123],"images":[124],"stack":[126],"them":[127],"dual-channel":[129],"three-channel":[131],"images.":[132],"After":[133],"transformation,":[135],"compare":[137],"mainstream":[138],"classification":[140,154],"networks":[141],"self-built":[144],"CNN.":[145],"Experimental":[146],"results":[147],"show":[148],"that":[149],"our":[150],"is":[155],"more":[156],"than":[158],"existing":[160],"shows":[169],"better":[170],"performance":[172],"accuracy,":[174],"requiring":[175],"fewer":[176],"samples":[179],"windows.":[182]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}