{"id":"https://openalex.org/W3170584831","doi":"https://doi.org/10.1145/3460620.3460759","title":"<i>Retracted on September 10, 2025:</i> Design of Gaussian Similarity Measure for Network Anomaly Detection","display_name":"<i>Retracted on September 10, 2025:</i> Design of Gaussian Similarity Measure for Network Anomaly Detection","publication_year":2021,"publication_date":"2021-04-05","ids":{"openalex":"https://openalex.org/W3170584831","doi":"https://doi.org/10.1145/3460620.3460759","mag":"3170584831"},"language":"en","primary_location":{"id":"doi:10.1145/3460620.3460759","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460620.3460759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Data Science, E-learning and Information Systems 2021","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/A5037466905","display_name":"Arun Nagaraja","orcid":"https://orcid.org/0000-0002-2652-4748"},"institutions":[{"id":"https://openalex.org/I106826634","display_name":"Jain University","ror":"https://ror.org/01cnqpt53","country_code":"IN","type":"education","lineage":["https://openalex.org/I106826634"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Nagaraja","raw_affiliation_strings":["Jain University, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jain University, India","institution_ids":["https://openalex.org/I106826634"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024763489","display_name":"Uma Boregowda","orcid":"https://orcid.org/0000-0001-5125-798X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Uma Boregowda","raw_affiliation_strings":["Malnad College of Engineering, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Malnad College of Engineering, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041895275","display_name":"Vangipuram Radhakrishna","orcid":"https://orcid.org/0000-0002-7373-6276"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Radhakrishna Vangipuram","raw_affiliation_strings":["VNRVJIET, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VNRVJIET, India","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Rajeshkumar Gunupudi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rajeshkumar Gunupudi","raw_affiliation_strings":["VNRVJIET, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VNRVJIET, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.481,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66178782,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"225","last_page":"230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.98580002784729,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.6637579202651978},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6286189556121826},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6212487816810608},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6164355874061584},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6029808521270752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5856665968894958},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5592209100723267},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5578838586807251},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5570877194404602},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.522519588470459},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.42401087284088135},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.41622835397720337}],"concepts":[{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.6637579202651978},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6286189556121826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6212487816810608},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6164355874061584},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6029808521270752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5856665968894958},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5592209100723267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5578838586807251},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5570877194404602},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.522519588470459},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.42401087284088135},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.41622835397720337},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3460620.3460759","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460620.3460759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Data Science, E-learning and Information Systems 2021","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":92,"referenced_works":["https://openalex.org/W1485321296","https://openalex.org/W1489073918","https://openalex.org/W1504694836","https://openalex.org/W1571061365","https://openalex.org/W1983944999","https://openalex.org/W1988122148","https://openalex.org/W1997415712","https://openalex.org/W2002900768","https://openalex.org/W2003282593","https://openalex.org/W2003740762","https://openalex.org/W2008678252","https://openalex.org/W2023426496","https://openalex.org/W2028469201","https://openalex.org/W2098298360","https://openalex.org/W2099940443","https://openalex.org/W2102832680","https://openalex.org/W2116377106","https://openalex.org/W2130676130","https://openalex.org/W2134490011","https://openalex.org/W2144182447","https://openalex.org/W2191024670","https://openalex.org/W2191495690","https://openalex.org/W2191976002","https://openalex.org/W2192642394","https://openalex.org/W2193493184","https://openalex.org/W2195660543","https://openalex.org/W2195747123","https://openalex.org/W2220567469","https://openalex.org/W2221884226","https://openalex.org/W2296707350","https://openalex.org/W2306850986","https://openalex.org/W2340896621","https://openalex.org/W2422379219","https://openalex.org/W2477350604","https://openalex.org/W2509205439","https://openalex.org/W2510170228","https://openalex.org/W2537725778","https://openalex.org/W2546923044","https://openalex.org/W2549066293","https://openalex.org/W2557314464","https://openalex.org/W2557761283","https://openalex.org/W2557779747","https://openalex.org/W2557843173","https://openalex.org/W2558623596","https://openalex.org/W2559536865","https://openalex.org/W2559677667","https://openalex.org/W2570160403","https://openalex.org/W2573910544","https://openalex.org/W2574209248","https://openalex.org/W2596206083","https://openalex.org/W2599354622","https://openalex.org/W2614188298","https://openalex.org/W2615135581","https://openalex.org/W2759696253","https://openalex.org/W2772110660","https://openalex.org/W2785783567","https://openalex.org/W2786069311","https://openalex.org/W2786998222","https://openalex.org/W2787366979","https://openalex.org/W2787701577","https://openalex.org/W2800369870","https://openalex.org/W2808472075","https://openalex.org/W2885080997","https://openalex.org/W2885301212","https://openalex.org/W2885683779","https://openalex.org/W2886641087","https://openalex.org/W2886789964","https://openalex.org/W2895343364","https://openalex.org/W2898623405","https://openalex.org/W2898776936","https://openalex.org/W2899074204","https://openalex.org/W2904778447","https://openalex.org/W2919659556","https://openalex.org/W2920682993","https://openalex.org/W2953482279","https://openalex.org/W2954122424","https://openalex.org/W2954439562","https://openalex.org/W2954631229","https://openalex.org/W2955262356","https://openalex.org/W2955543247","https://openalex.org/W2964102409","https://openalex.org/W2964742977","https://openalex.org/W2969282196","https://openalex.org/W2975517869","https://openalex.org/W2987821246","https://openalex.org/W2997998108","https://openalex.org/W3008735069","https://openalex.org/W3014732532","https://openalex.org/W3016371023","https://openalex.org/W3120360473","https://openalex.org/W3163054355","https://openalex.org/W4212883601"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W4391160746","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"Identifying":[0],"intrusion":[1,28],"in":[2,10,26],"networks":[3],"is":[4,44,76,85],"one":[5],"of":[6,15,20,38],"the":[7,36,82],"important":[8,24],"concerns":[9],"computer":[11],"networks.":[12],"The":[13,73],"task":[14],"dimensionality":[16,42],"reduction":[17,31],"and":[18],"choice":[19],"classifier":[21,39],"plays":[22],"an":[23],"role":[25],"network":[27,68],"detection.":[29],"Dimensionality":[30],"should":[32],"make":[33,79],"sure":[34,80],"that":[35,81],"efficacy":[37],"on":[40],"reduced":[41],"data":[43],"atleast":[45],"retained":[46],"if":[47],"not":[48],"improved.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"suggest":[54],"a":[55],"similarity":[56,64,74,91],"function":[57],"which":[58],"can":[59],"be":[60],"used":[61],"to":[62,78],"find":[63],"between":[65],"any":[66],"two":[67],"elements":[69],"expressed":[70],"as":[71],"vectors.":[72],"measure":[75],"designed":[77],"attribute":[83],"distribution":[84],"taken":[86],"into":[87],"account":[88],"for":[89],"finding":[90],"value.":[92]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2021-06-22T00:00:00"}