{"id":"https://openalex.org/W4413639936","doi":"https://doi.org/10.1109/csr64739.2025.11130144","title":"Enhancing Deep Learning Based IDS Adversarial Robustness With Causal Inference","display_name":"Enhancing Deep Learning Based IDS Adversarial Robustness With Causal Inference","publication_year":2025,"publication_date":"2025-08-04","ids":{"openalex":"https://openalex.org/W4413639936","doi":"https://doi.org/10.1109/csr64739.2025.11130144"},"language":"en","primary_location":{"id":"doi:10.1109/csr64739.2025.11130144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csr64739.2025.11130144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Cyber Security and Resilience (CSR)","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/A5076374121","display_name":"Marin Fran\u00e7ois","orcid":"https://orcid.org/0000-0001-5661-8131"},"institutions":[{"id":"https://openalex.org/I56435720","display_name":"Universit\u00e9 Paris Dauphine-PSL","ror":"https://ror.org/052bz7812","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580","https://openalex.org/I56435720"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Marin Fran\u00e7ois","raw_affiliation_strings":["LAMSADE, UMR CNRS 7243 Universit&#x00E9; Paris-Dauphine PSL,Paris,France"],"affiliations":[{"raw_affiliation_string":"LAMSADE, UMR CNRS 7243 Universit&#x00E9; Paris-Dauphine PSL,Paris,France","institution_ids":["https://openalex.org/I56435720","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119433215","display_name":"Pierre-Emmanual Arduin","orcid":null},"institutions":[{"id":"https://openalex.org/I56435720","display_name":"Universit\u00e9 Paris Dauphine-PSL","ror":"https://ror.org/052bz7812","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580","https://openalex.org/I56435720"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Pierre-Emmanual Arduin","raw_affiliation_strings":["DRM, UMR CNRS 7088 Universit&#x00E9; Paris-Dauphine PSL,Paris,France"],"affiliations":[{"raw_affiliation_string":"DRM, UMR CNRS 7088 Universit&#x00E9; Paris-Dauphine PSL,Paris,France","institution_ids":["https://openalex.org/I56435720","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006330541","display_name":"Myriam M\u00e9rad","orcid":"https://orcid.org/0000-0002-8186-581X"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I56435720","display_name":"Universit\u00e9 Paris Dauphine-PSL","ror":"https://ror.org/052bz7812","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580","https://openalex.org/I56435720"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Myriam Merad","raw_affiliation_strings":["LAMSADE, UMR CNRS 7243 Universit&#x00E9; Paris-Dauphine PSL,Paris,France"],"affiliations":[{"raw_affiliation_string":"LAMSADE, UMR CNRS 7243 Universit&#x00E9; Paris-Dauphine PSL,Paris,France","institution_ids":["https://openalex.org/I56435720","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076374121"],"corresponding_institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I56435720"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1287033,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"57","last_page":"62"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987999796867371,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9825000166893005,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9614999890327454,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.7613726854324341},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7612418532371521},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7315126061439514},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6786723136901855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.638521671295166},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.5159921646118164},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.479341596364975},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45408254861831665},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08466610312461853},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.06879693269729614},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.06384885311126709}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7613726854324341},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7612418532371521},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7315126061439514},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6786723136901855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.638521671295166},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.5159921646118164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.479341596364975},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45408254861831665},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08466610312461853},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.06879693269729614},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.06384885311126709},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/csr64739.2025.11130144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csr64739.2025.11130144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Cyber Security and Resilience (CSR)","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":38,"referenced_works":["https://openalex.org/W1964940342","https://openalex.org/W1981457167","https://openalex.org/W2082418604","https://openalex.org/W2088794999","https://openalex.org/W2136540032","https://openalex.org/W2142384583","https://openalex.org/W2624816748","https://openalex.org/W2744338514","https://openalex.org/W2746600820","https://openalex.org/W2765424254","https://openalex.org/W2889836475","https://openalex.org/W2944851425","https://openalex.org/W2962743217","https://openalex.org/W3087470167","https://openalex.org/W3117906366","https://openalex.org/W3160455160","https://openalex.org/W3161599138","https://openalex.org/W3185244527","https://openalex.org/W3202565128","https://openalex.org/W4224109353","https://openalex.org/W4226116716","https://openalex.org/W4244977870","https://openalex.org/W4292425665","https://openalex.org/W4307940854","https://openalex.org/W4321484315","https://openalex.org/W4360995249","https://openalex.org/W4361010174","https://openalex.org/W4377022569","https://openalex.org/W4383555810","https://openalex.org/W4385190584","https://openalex.org/W4387394267","https://openalex.org/W4389201650","https://openalex.org/W4389513574","https://openalex.org/W4394769550","https://openalex.org/W4399485286","https://openalex.org/W4401450512","https://openalex.org/W4401752687","https://openalex.org/W4406600497"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"Deep":[0],"Learning":[1],"models":[2],"are":[3,89],"increasingly":[4],"employed":[5],"in":[6,28,86,91],"mission-critical":[7],"security":[8],"systems,":[9],"but":[10],"remain":[11],"vulnerable":[12],"to":[13,17,51,61],"adversarial":[14,79],"attacks":[15],"due":[16],"out-of-distribution":[18],"(OOD)":[19],"inference":[20,50],"biases.":[21],"These":[22],"biases":[23],"arise":[24],"from":[25],"spurious":[26,55],"correlations":[27],"training":[29],"data,":[30],"an":[31,46],"issue":[32],"exacerbated":[33],"by":[34],"the":[35,92],"use":[36],"of":[37],"synthetic":[38],"datasets.":[39],"To":[40],"address":[41],"these":[42],"concerns,":[43],"we":[44],"propose":[45],"algorithm":[47],"leveraging":[48],"causal":[49],"identify":[52],"and":[53,67,74,83],"transform":[54],"features.":[56],"We":[57],"test":[58],"our":[59],"algorithms":[60,84],"two":[62],"deep":[63],"learning":[64],"based":[65],"IDS,":[66],"experimentally":[68],"demonstrate":[69],"enhancing":[70],"both":[71],"model":[72],"robustness":[73],"performance":[75],"against":[76],"highly":[77],"aggressive":[78],"attacks.":[80],"All":[81],"data":[82],"presented":[85],"this":[87],"paper":[88],"available":[90],"replication":[93],"package<sup":[94],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[95,97],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>.<sup":[96],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>see":[98],"https://github.com/mbdlrocks/PhD_Replication_Package/tree/master/Causal-Hidden-Markov-Model%20(CHMM)":[99]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
