{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T03:21:54Z","timestamp":1768274514610,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":49,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,15]],"date-time":"2021-11-15T00:00:00Z","timestamp":1636934400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,11,15]]},"DOI":"10.1145\/3474369.3486867","type":"proceedings-article","created":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T11:13:28Z","timestamp":1635419608000},"page":"73-84","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels"],"prefix":"10.1145","author":[{"given":"Robert J.","family":"Joyce","sequence":"first","affiliation":[{"name":"Booz Allen Hamilton &amp; University of Maryland, Baltimore County, McLean, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edward","family":"Raff","sequence":"additional","affiliation":[{"name":"Booz Allen Hamilton &amp; University of Maryland, Baltimore County, McLean, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charles","family":"Nicholas","sequence":"additional","affiliation":[{"name":"University of Maryland, Baltimore County, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,11,15]]},"reference":[{"key":"e_1_3_2_2_1_1","first-page":"210","volume-title":"Eds.","author":"Crowston K.","year":"2012","unstructured":"K. Crowston , \"Amazon mechanical turk : A research tool for organizations and information systems scholars,\" in Shaping the Future of ICT Research. Methods and Approaches, A. Bhattacherjee and B. Fitzgerald , Eds. , 2012 , pp. 210 -- 221 . K. Crowston, \"Amazon mechanical turk: A research tool for organizations and information systems scholars,\" in Shaping the Future of ICT Research. Methods and Approaches, A. Bhattacherjee and B. Fitzgerald, Eds., 2012, pp. 210--221."},{"key":"e_1_3_2_2_2_1","first-page":"230","volume-title":"Eds.","author":"Sebasti\u00e1n M.","year":"2016","unstructured":"M. Sebasti\u00e1n , R. Rivera , P. Kotzias , and J. Caballero , \" Avclass: A tool for massive malware labeling,\" in Research in Attacks, Intrusions, and Defenses, F. Monrose, M. Dacier, G. Blanc, and J. Garcia-Alfaro , Eds. , Cham , 2016 , pp. 230 -- 253 . et al.(2016)Sebasti\u00e1n, Rivera, Kotzias, and Caballero]avclassM. Sebasti\u00e1n, R. Rivera, P. Kotzias, and J. Caballero, \"Avclass: A tool for massive malware labeling,\" in Research in Attacks, Intrusions, and Defenses, F. Monrose, M. Dacier, G. Blanc, and J. Garcia-Alfaro, Eds., Cham, 2016, pp. 230--253."},{"key":"e_1_3_2_2_3_1","volume-title":"Accounting for Variance in Machine Learning Benchmarks,\" in Machine Learning and Systems (MLSys)","author":"Bouthillier X.","year":"2021","unstructured":"X. Bouthillier , P. Delaunay , M. Bronzi , A. Trofimov , B. Nichyporuk , J. Szeto , N. Sepah , E. Raff , K. Madan , V. Voleti , S. E. Kahou , V. Michalski , D. Serdyuk , T. Arbel , C. Pal , G. Varoquaux , and P. Vincent , \" Accounting for Variance in Machine Learning Benchmarks,\" in Machine Learning and Systems (MLSys) , 2021 . X. Bouthillier, P. Delaunay, M. Bronzi, A. Trofimov, B. Nichyporuk, J. Szeto, N. Sepah, E. Raff, K. Madan, V. Voleti, S. E. Kahou, V. Michalski, D. Serdyuk, T. Arbel, C. Pal, G. Varoquaux, and P. Vincent, \"Accounting for Variance in Machine Learning Benchmarks,\" in Machine Learning and Systems (MLSys), 2021."},{"key":"e_1_3_2_2_4_1","first-page":"7297","volume-title":"Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers,\" in ACL. hskip 1em plus 0.5em minus 0.4emrelax Online: Association for Computational Linguistics, aug","author":"Marie B.","year":"2021","unstructured":"B. Marie , A. Fujita , and R. Rubino , \" Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers,\" in ACL. hskip 1em plus 0.5em minus 0.4emrelax Online: Association for Computational Linguistics, aug 2021 , pp. 7297 -- 7306 . B. Marie, A. Fujita, and R. Rubino, \"Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers,\" in ACL. hskip 1em plus 0.5em minus 0.4emrelax Online: Association for Computational Linguistics, aug 2021, pp. 7297--7306."},{"key":"e_1_3_2_2_5_1","first-page":"2922","volume-title":"Identifying Statistical Bias in Dataset Replication,\" in Proceedings of the 37th International Conference on Machine Learning","author":"Engstrom L.","year":"2020","unstructured":"L. Engstrom , A. Ilyas , S. Santurkar , D. Tsipras , J. Steinhardt , and A. Madry , \" Identifying Statistical Bias in Dataset Replication,\" in Proceedings of the 37th International Conference on Machine Learning , vol. 119 , Virtual , 2020 , pp. 2922 -- 2932 . L. Engstrom, A. Ilyas, S. Santurkar, D. Tsipras, J. Steinhardt, and A. Madry, \"Identifying Statistical Bias in Dataset Replication,\" in Proceedings of the 37th International Conference on Machine Learning, vol. 119, Virtual, 2020, pp. 2922--2932."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging6060041"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"crossref","unstructured":"K. Musgrave S. Belongie and S.-N. Lim \"A Metric Learning Reality Check \" in ECCV 2020. [Online]. Available: http:\/\/arxiv.org\/abs\/2003.08505BIBentrySTDinterwordspacing  K. Musgrave S. Belongie and S.-N. Lim \"A Metric Learning Reality Check \" in ECCV 2020. [Online]. Available: http:\/\/arxiv.org\/abs\/2003.08505BIBentrySTDinterwordspacing","DOI":"10.1007\/978-3-030-58595-2_41"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412489"},{"key":"e_1_3_2_2_9_1","first-page":"725","volume-title":"Unreproducible Research is Reproducible,\" in Proceedings of the 36th International Conference on Machine Learning","author":"Bouthillier X.","year":"2019","unstructured":"X. Bouthillier , C. Laurent , and P. Vincent , \" Unreproducible Research is Reproducible,\" in Proceedings of the 36th International Conference on Machine Learning , vol. 97 , 2019 , pp. 725 -- 734 . X. Bouthillier, C. Laurent, and P. Vincent, \"Unreproducible Research is Reproducible,\" in Proceedings of the 36th International Conference on Machine Learning, vol. 97, 2019, pp. 725--734."},{"key":"e_1_3_2_2_10_1","unstructured":"E. Raff \"A Step Toward Quantifying Independently Reproducible Machine Learning Research \" in NeurIPS 2019.  E. Raff \"A Step Toward Quantifying Independently Reproducible Machine Learning Research \" in NeurIPS 2019."},{"key":"e_1_3_2_2_11_1","first-page":"15","article-title":"Are labels always necessary for classifier accuracy evaluation?","author":"Deng W.","year":"2021","unstructured":"W. Deng and L. Zheng , \" Are labels always necessary for classifier accuracy evaluation? \" in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , June 2021 , pp. 15 ,069--15,078. W. Deng and L. Zheng, \"Are labels always necessary for classifier accuracy evaluation?\" in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2021, pp. 15,069--15,078.","journal-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"e_1_3_2_2_12_1","first-page":"13799","article-title":"Assessing generalization of sgd via disagreement","volume":"2106","author":"Jiang Y.","year":"2021","unstructured":"Y. Jiang , V. Nagarajan , C. Baek , and J. Z. Kolter , \" Assessing generalization of sgd via disagreement ,\" ArXiv , vol. abs\/ 2106 . 13799 , 2021 . Y. Jiang, V. Nagarajan, C. Baek, and J. Z. Kolter, \"Assessing generalization of sgd via disagreement,\" ArXiv, vol. abs\/2106.13799, 2021.","journal-title":"ArXiv"},{"key":"e_1_3_2_2_13_1","first-page":"197","volume-title":"Ed.","author":"Nov\u00e1k M.","year":"2019","unstructured":"M. Nov\u00e1k , J. M\u00edrovsk\u00fd , K. Rysov\u00e1 , and M. Rysov\u00e1 , \" Exploiting large unlabeled data in automatic evaluation of coherence in czech,\" in Text, Speech, and Dialogue, K. Ekvs tein , Ed. , Cham , 2019 , pp. 197 -- 210 . M. Nov\u00e1k, J. M\u00edrovsk\u00fd, K. Rysov\u00e1, and M. Rysov\u00e1, \"Exploiting large unlabeled data in automatic evaluation of coherence in czech,\" in Text, Speech, and Dialogue, K. Ekvs tein, Ed., Cham, 2019, pp. 197--210."},{"key":"e_1_3_2_2_14_1","first-page":"3239","volume-title":"NIPS'18","author":"Oliver A.","year":"2018","unstructured":"A. Oliver , A. Odena , C. Raffel , E. D. Cubuk , and I. J. Goodfellow , \" Realistic evaluation of deep semi-supervised learning algorithms,\" in Proceedings of the 32nd International Conference on Neural Information Processing Systems, ser . NIPS'18 . Red Hook, NY, USA: Curran Associates Inc. , 2018 , p. 3239 -- 3250 . A. Oliver, A. Odena, C. Raffel, E. D. Cubuk, and I. J. Goodfellow, \"Realistic evaluation of deep semi-supervised learning algorithms,\" in Proceedings of the 32nd International Conference on Neural Information Processing Systems, ser. NIPS'18. Red Hook, NY, USA: Curran Associates Inc., 2018, p. 3239--3250."},{"key":"e_1_3_2_2_15_1","volume-title":"Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints,\" in IJCAI-21 1st International Workshop on Adaptive Cyber Defense","author":"Nguyen A. T.","year":"2021","unstructured":"A. T. Nguyen , E. Raff , C. Nicholas , and J. Holt , \" Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints,\" in IJCAI-21 1st International Workshop on Adaptive Cyber Defense , 2021 . A. T. Nguyen, E. Raff, C. Nicholas, and J. Holt, \"Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints,\" in IJCAI-21 1st International Workshop on Adaptive Cyber Defense, 2021."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/asi.5090060209"},{"key":"e_1_3_2_2_17_1","volume-title":"16th Annual Network and Distributed System Security Symposium, 02","author":"Bayer U.","year":"2009","unstructured":"U. Bayer , P. M. Comparetti , C. Hlauschek , C. Kruegel , and E. Kirda , \" Scalable, behavior-based malware clustering,\" in NDSS 2009 , 16th Annual Network and Distributed System Security Symposium, 02 2009 . [Online]. Available : http:\/\/www.eurecom.fr\/publication\/2783 U. Bayer, P. M. Comparetti, C. Hlauschek, C. Kruegel, and E. Kirda, \"Scalable, behavior-based malware clustering,\" in NDSS 2009, 16th Annual Network and Distributed System Security Symposium, 02 2009. [Online]. Available: http:\/\/www.eurecom.fr\/publication\/2783"},{"key":"e_1_3_2_2_18_1","first-page":"238","volume-title":"Eds.","author":"Li P.","year":"2010","unstructured":"P. Li , L. Liu , D. Gao , and M. K. Reiter , \" On challenges in evaluating malware clustering,\" in Recent Advances in Intrusion Detection, S. Jha, R. Sommer, and C. Kreibich , Eds. , 2010 , pp. 238 -- 255 . P. Li, L. Liu, D. Gao, and M. K. Reiter, \"On challenges in evaluating malware clustering,\" in Recent Advances in Intrusion Detection, S. Jha, R. Sommer, and C. Kreibich, Eds., 2010, pp. 238--255."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1137\/0216062"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2017.2739145"},{"key":"e_1_3_2_2_21_1","volume-title":"Surveys & Meta-Analyses (ML-RSA)","author":"Raff E.","year":"2020","unstructured":"E. Raff and C. Nicholas , \" A Survey of Machine Learning Methods and Challenges for Windows Malware Classification,\" in NeurIPS 2020 Workshop: ML Retrospectives , Surveys & Meta-Analyses (ML-RSA) , 2020 . E. Raff and C. Nicholas, \"A Survey of Machine Learning Methods and Challenges for Windows Malware Classification,\" in NeurIPS 2020 Workshop: ML Retrospectives, Surveys & Meta-Analyses (ML-RSA), 2020."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2015.04.001"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487788.2488056"},{"key":"e_1_3_2_2_24_1","volume-title":"An Observational Investigation of Reverse Engineers' Process and Mental Models,\" in USENIX Security Symposium","author":"Votipka D.","year":"2019","unstructured":"D. Votipka , S. Rabin , K. Micinski , J. S. Foster , and M. L. Mazurek , \" An Observational Investigation of Reverse Engineers' Process and Mental Models,\" in USENIX Security Symposium , 2019 . D. Votipka, S. Rabin, K. Micinski, J. S. Foster, and M. L. Mazurek, \"An Observational Investigation of Reverse Engineers' Process and Mental Models,\" in USENIX Security Symposium, 2019."},{"key":"e_1_3_2_2_25_1","first-page":"329","volume-title":"Towards a fully automated malware clustering validity analysis,\" in Proceedings of the 28th Annual Computer Security Applications Conference, 12","author":"Perdisci R.","year":"2012","unstructured":"R. Perdisci and M. U , \" Vamo : Towards a fully automated malware clustering validity analysis,\" in Proceedings of the 28th Annual Computer Security Applications Conference, 12 2012 , pp. 329 -- 338 . R. Perdisci and M. U, \"Vamo: Towards a fully automated malware clustering validity analysis,\" in Proceedings of the 28th Annual Computer Security Applications Conference, 12 2012, pp. 329--338."},{"key":"e_1_3_2_2_26_1","unstructured":"Y. Zhou \"Malgenome project \" http:\/\/malgenomeproject.org\/ Last accessed on 2020-3-9.  Y. Zhou \"Malgenome project \" http:\/\/malgenomeproject.org\/ Last accessed on 2020-3-9."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813665"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10207-014-0248-7"},{"key":"e_1_3_2_2_29_1","volume-title":"Measuring and modeling the label dynamics of online anti-malware engines,\" in 29th USENIX Security Symposium (USENIX Security 20)","author":"Zhu S.","year":"2020","unstructured":"S. Zhu , J. Shi , L. Yang , B. Qin , Z. Zhang , L. Song , and G. Wang , \" Measuring and modeling the label dynamics of online anti-malware engines,\" in 29th USENIX Security Symposium (USENIX Security 20) . Boston, MA : USENIX Association , Aug. 2020 . [Online]. Available: https:\/\/www.usenix.org\/conference\/usenixsecurity20\/presentation\/zhu S. Zhu, J. Shi, L. Yang, B. Qin, Z. Zhang, L. Song, and G. Wang, \"Measuring and modeling the label dynamics of online anti-malware engines,\" in 29th USENIX Security Symposium (USENIX Security 20). Boston, MA: USENIX Association, Aug. 2020. [Online]. Available: https:\/\/www.usenix.org\/conference\/usenixsecurity20\/presentation\/zhu"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2020.101859"},{"key":"e_1_3_2_2_31_1","first-page":"231","volume-title":"Eds.","author":"Mohaisen A.","year":"2014","unstructured":"A. Mohaisen , O. Alrawi , M. Larson , and D. McPherson , \" Towards a methodical evaluation of antivirus scans and labels,\" in Information Security Applications, Y. Kim, H. Lee, and A. Perrig , Eds. , Cham , 2014 , pp. 231 -- 241 . A. Mohaisen, O. Alrawi, M. Larson, and D. McPherson, \"Towards a methodical evaluation of antivirus scans and labels,\" in Information Security Applications, Y. Kim, H. Lee, and A. Perrig, Eds., Cham, 2014, pp. 231--241."},{"key":"e_1_3_2_2_32_1","first-page":"07","article-title":"Mtnet: A multi-task neural network for dynamic malware classification","author":"Huang W.","year":"2016","unstructured":"W. Huang and J. Stokes , \" Mtnet: A multi-task neural network for dynamic malware classification ,\" in International Conference on Detection of Intrusions , 07 2016 . W. Huang and J. Stokes, \"Mtnet: A multi-task neural network for dynamic malware classification,\" in International Conference on Detection of Intrusions, 07 2016.","journal-title":"International Conference on Detection of Intrusions"},{"key":"e_1_3_2_2_33_1","unstructured":"K. Rieck \"Malheur dataset \" https:\/\/www.sec.cs.tu-bs.de\/data\/malheur\/ Last accessed on 2020-3-9.  K. Rieck \"Malheur dataset \" https:\/\/www.sec.cs.tu-bs.de\/data\/malheur\/ Last accessed on 2020-3-9."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.3233\/JCS-2010-0410"},{"key":"e_1_3_2_2_35_1","unstructured":"D. Arp \"The drebin dataset \" https:\/\/www.sec.cs.tu-bs.de\/ danarp\/drebin\/download.html Last accessed on 2020-3-9.  D. Arp \"The drebin dataset \" https:\/\/www.sec.cs.tu-bs.de\/ danarp\/drebin\/download.html Last accessed on 2020-3-9."},{"key":"e_1_3_2_2_36_1","volume-title":"Drebin: Effective and explainable detection of android malware in your pocket,\" in Symposium on Network and Distributed System Security (NDSS), 02","author":"Arp D.","year":"2014","unstructured":"D. Arp , M. Spreitzenbarth , M. H\u00fcbner , H. Gascon , and K. Rieck , \" Drebin: Effective and explainable detection of android malware in your pocket,\" in Symposium on Network and Distributed System Security (NDSS), 02 2014 . D. Arp, M. Spreitzenbarth, M. H\u00fcbner, H. Gascon, and K. Rieck, \"Drebin: Effective and explainable detection of android malware in your pocket,\" in Symposium on Network and Distributed System Security (NDSS), 02 2014."},{"key":"e_1_3_2_2_37_1","first-page":"10135","article-title":"Microsoft malware classification challenge","volume":"1802","author":"Ronen R.","year":"2018","unstructured":"R. Ronen , M. Radu , C. Feuerstein , E. Yom-Tov , and M. Ahmadi , \" Microsoft malware classification challenge ,\" CoRR , vol. abs\/ 1802 . 10135 , 2018 . R. Ronen, M. Radu, C. Feuerstein, E. Yom-Tov, and M. Ahmadi, \"Microsoft malware classification challenge,\" CoRR, vol. abs\/1802.10135, 2018.","journal-title":"CoRR"},{"key":"e_1_3_2_2_38_1","first-page":"95","volume-title":"May 2012","author":"Zhou Y.","unstructured":"Y. Zhou and X. Jiang , \" Dissecting android malware: Characterization and evolution,\" in 2012 IEEE Symposium on Security and Privacy , May 2012 , pp. 95 -- 109 . Y. Zhou and X. Jiang, \"Dissecting android malware: Characterization and evolution,\" in 2012 IEEE Symposium on Security and Privacy, May 2012, pp. 95--109."},{"key":"e_1_3_2_2_39_1","first-page":"929","volume-title":"Aug 2016","author":"Qiao Y.","unstructured":"Y. Qiao , X. Yun , and Y. Zhang , \" How to automatically identify the homology of different malware,\" in 2016 IEEE Trustcom\/BigDataSE\/ISPA , Aug 2016 , pp. 929 -- 936 . Y. Qiao, X. Yun, and Y. Zhang, \"How to automatically identify the homology of different malware,\" in 2016 IEEE Trustcom\/BigDataSE\/ISPA, Aug 2016, pp. 929--936."},{"key":"e_1_3_2_2_40_1","unstructured":"\"Dataset - malicia project \" http:\/\/malicia-project.com\/dataset.html Last accessed on 2020-3-9.  \"Dataset - malicia project \" http:\/\/malicia-project.com\/dataset.html Last accessed on 2020-3-9."},{"key":"e_1_3_2_2_41_1","first-page":"252","volume-title":"Eds.","author":"Wei F.","year":"2017","unstructured":"F. Wei , Y. Li , S. Roy , X. Ou , and W. Zhou , \" Deep ground truth analysis of current android malware,\" in Detection of Intrusions and Malware, and Vulnerability Assessment, M. Polychronakis and M. Meier , Eds. , Cham , 2017 , pp. 252 -- 276 . F. Wei, Y. Li, S. Roy, X. Ou, and W. Zhou, \"Deep ground truth analysis of current android malware,\" in Detection of Intrusions and Malware, and Vulnerability Assessment, M. Polychronakis and M. Meier, Eds., Cham, 2017, pp. 252--276."},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.diin.2018.01.007"},{"key":"e_1_3_2_2_43_1","volume-title":"Ember: An open dataset for training static pe malware machine learning models","author":"Anderson H. S.","year":"2018","unstructured":"H. S. Anderson and P. Roth , \" Ember: An open dataset for training static pe malware machine learning models ,\" 2018 . H. S. Anderson and P. Roth, \"Ember: An open dataset for training static pe malware machine learning models,\" 2018."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2808769.2808780"},{"key":"e_1_3_2_2_45_1","volume-title":"A novel approach to fast malware clustering,\" in LEET","author":"Wicherski G.","year":"2009","unstructured":"G. Wicherski , \"pehash : A novel approach to fast malware clustering,\" in LEET , 2009 . G. Wicherski, \"pehash: A novel approach to fast malware clustering,\" in LEET, 2009."},{"key":"e_1_3_2_2_46_1","unstructured":"\"Clamav \" http:\/\/anubis.iseclab.org\/ Last accessed on 2020-5-04.  \"Clamav \" http:\/\/anubis.iseclab.org\/ Last accessed on 2020-5-04."},{"key":"e_1_3_2_2_47_1","unstructured":"\"Virusshare.com - because sharing is caring \" https:\/\/virusshare.com\/ Last accessed on 2021-9-18.  \"Virusshare.com - because sharing is caring \" https:\/\/virusshare.com\/ Last accessed on 2021-9-18."},{"key":"e_1_3_2_2_48_1","volume-title":"Labeling the virusshare corpus- lessons learned","author":"Seymour J.","year":"2016","unstructured":"J. Seymour , \"Bsideslv 2016 : Labeling the virusshare corpus- lessons learned ,\" 2016 , bSides Las Vegas . [Online]. Available: https:\/\/www.peerlyst.com\/posts\/bsideslv-2016-labeling-the-virusshare-corpus-lessons- learned-john-seymourBIBentrySTDinterwordspacing J. Seymour, \"Bsideslv 2016: Labeling the virusshare corpus- lessons learned,\" 2016, bSides Las Vegas. [Online]. Available: https:\/\/www.peerlyst.com\/posts\/bsideslv-2016-labeling-the-virusshare-corpus-lessons- learned-john-seymourBIBentrySTDinterwordspacing"},{"key":"e_1_3_2_2_49_1","unstructured":"VirusTotal \"File statistics during last 7 days \" https:\/\/www.virustotal.com\/en\/statistics\/ Last accessed on 2020-3-8.  VirusTotal \"File statistics during last 7 days \" https:\/\/www.virustotal.com\/en\/statistics\/ Last accessed on 2020-3-8."}],"event":{"name":"CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security","location":"Virtual Event Republic of Korea","acronym":"CCS '21","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"]},"container-title":["Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3474369.3486867","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3474369.3486867","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:26Z","timestamp":1750188626000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3474369.3486867"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,15]]},"references-count":49,"alternative-id":["10.1145\/3474369.3486867","10.1145\/3474369"],"URL":"https:\/\/doi.org\/10.1145\/3474369.3486867","relation":{},"subject":[],"published":{"date-parts":[[2021,11,15]]},"assertion":[{"value":"2021-11-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}