{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T00:25:27Z","timestamp":1778199927415,"version":"3.51.4"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2017,5,9]],"date-time":"2017-05-09T00:00:00Z","timestamp":1494288000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,5,9]],"date-time":"2017-05-09T00:00:00Z","timestamp":1494288000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100000001","name":"U.S. National Science Foundation","doi-asserted-by":"crossref","award":["CNS-1618629"],"award-info":[{"award-number":["CNS-1618629"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2018,2]]},"DOI":"10.1007\/s10115-017-1058-9","type":"journal-article","created":{"date-parts":[[2017,5,9]],"date-time":"2017-05-09T03:59:50Z","timestamp":1494302390000},"page":"265-285","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":98,"title":["DeepAM: a heterogeneous deep learning framework for intelligent malware detection"],"prefix":"10.1007","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8376-7239","authenticated-orcid":false,"given":"Yanfang","family":"Ye","sequence":"first","affiliation":[]},{"given":"Lingwei","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Shifu","family":"Hou","sequence":"additional","affiliation":[]},{"given":"William","family":"Hardy","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,9]]},"reference":[{"issue":"4","key":"1058_CR1","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1109\/MCI.2010.938364","volume":"5","author":"I Arel","year":"2010","unstructured":"Arel I, Rose DC, Karnowski TP (2010) Deep machine learning\u2014a new frontier in artificial intelligence research. IEEE Comput Intell Mag 5(4):13\u201318","journal-title":"IEEE Comput Intell Mag"},{"key":"1058_CR2","doi-asserted-by":"crossref","unstructured":"Bailey M, Oberheide J, Andersen J, Mao Z, Ahanian F, Nazario J (2007) Automated classification and analysis of internet malware. In: 10th international symposium on research in attacks, intrusions and defenses (RAID) 2007, LNCS, pp 178\u2013197","DOI":"10.1007\/978-3-540-74320-0_10"},{"key":"1058_CR3","doi-asserted-by":"crossref","unstructured":"Bengio Y, LeCun Y (2007) Scaling learning algorithms towards AI. Large-Scale Kernel Mach 34(5):1\u201341","DOI":"10.7551\/mitpress\/7496.003.0016"},{"issue":"1","key":"1058_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000006","volume":"2","author":"Y Bengio","year":"2009","unstructured":"Bengio Y (2009) Learning deep architectures for AI. Found Trends Mach Learn 2(1):1\u2013127","journal-title":"Found Trends Mach Learn"},{"key":"1058_CR5","doi-asserted-by":"crossref","unstructured":"Bengio Y, Lamblin P, Popovici D, Larochelle H (2007) Greedy layer-wise training of deep networks. In: Advances in neural information processing systems 19 (NIPS\u201906), pp 153\u2013160","DOI":"10.7551\/mitpress\/7503.003.0024"},{"key":"1058_CR6","unstructured":"Carreira-Perpinan M, Hinton G (2005) On contrastive divergence learning. In: Proceedings of the tenth international workshop on artificial intelligence and statistics"},{"issue":"4","key":"1058_CR7","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1109\/TDSC.2013.40","volume":"11","author":"S Cesare","year":"2014","unstructured":"Cesare S, Xiang Y, Zhou W (2014) Control flow-based malware variant detection. IEEE Trans Dependable Secure Comput 11(4):307\u2013317","journal-title":"IEEE Trans Dependable Secure Comput"},{"key":"1058_CR8","doi-asserted-by":"crossref","unstructured":"Collobert R, Weston J (2008) A unified architecture for natural language processing: deep neural networks with multitask learning. In: Proceedings of the 25th international conference on machine learning (ICML\u201908), pp 160\u2013167","DOI":"10.1145\/1390156.1390177"},{"key":"1058_CR9","doi-asserted-by":"publisher","DOI":"10.1002\/9780470148150","volume-title":"A statistical approach to neural networks for pattern recognition","author":"RA Dunne","year":"2007","unstructured":"Dunne RA (2007) A statistical approach to neural networks for pattern recognition, 1st edn. Wiley, New York","edition":"1"},{"key":"1058_CR10","unstructured":"Egele M, Scholte T, Kirda E, Kruegel C (2008) A survey on automated dynamic malware analysis techniques and tools. In: ACM computing surveys (CSUR), vol 44(2), pp 6:1\u20136:42"},{"issue":"1","key":"1058_CR11","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/s11416-006-0009-x","volume":"2","author":"E Filiol","year":"2006","unstructured":"Filiol E (2006) Malware pattern scanning schemes secure against blackbox analysis. J Comput Virol 2(1):35\u201350","journal-title":"J Comput Virol"},{"issue":"1","key":"1058_CR12","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s11416-006-0026-9","volume":"3","author":"E Filiol","year":"2007","unstructured":"Filiol E, Jacob G, Liard ML (2007) Evaluation methodology and theoretical model for antiviral behavioural detection strategies. J Comput Virol 3(1):27\u201337","journal-title":"J Comput Virol"},{"issue":"5786","key":"1058_CR13","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Salakhutdinov RR (2006) Reducing the dimensionality of data with neural networks. Science 313(5786):504\u2013507","journal-title":"Science"},{"key":"1058_CR14","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Osindero S, Teh Y (2006) A fast learning algorithm for deep belief nets. Neural Comput 18:1527\u20131554","journal-title":"Neural Comput"},{"key":"1058_CR15","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1007\/978-3-642-35289-8_32","volume":"7700","author":"GE Hinton","year":"2012","unstructured":"Hinton GE (2012) A practical guide to training restricted Boltzmann machines. Neural Netw Tricks Trade 7700:599\u2013619","journal-title":"Neural Netw Tricks Trade"},{"issue":"5214","key":"1058_CR16","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.1126\/science.7761831","volume":"268","author":"GE Hinton","year":"1995","unstructured":"Hinton GE, Dayan P, Frey BJ, Neal RM (1995) The wake-sleep algorithm for unsupervised neural networks. Science 268(5214):1158\u20131161","journal-title":"Science"},{"key":"1058_CR17","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/S0079-6123(06)65034-6","volume":"165","author":"GE Hinton","year":"2007","unstructured":"Hinton GE (2007) To recognize shapes, first learn to generate images. Prog Brain Res 165:535\u2013547","journal-title":"Prog Brain Res"},{"key":"1058_CR18","doi-asserted-by":"crossref","unstructured":"Hou S, Chen L, Tas E, Demihovskiy I, Ye Y (2015) Cluster-oriented ensemble classifiers for malware detection. In: IEEE international conference on semantic computing (IEEE ICSC), pp 189\u2013196","DOI":"10.1109\/ICOSC.2015.7050805"},{"issue":"5","key":"1058_CR19","doi-asserted-by":"publisher","first-page":"2191","DOI":"10.1109\/TITS.2014.2311123","volume":"15","author":"W Huang","year":"2014","unstructured":"Huang W, Song G, Hong H, Xie K (2014) Deep architecture for traffic flow prediction: deep belief networks with multitask learning. IEEE Trans Intell Transp Syst 15(5):2191\u20132201","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"1058_CR20","unstructured":"Jung W, Kim S, Choi S (2015) Poster: deep learning for zero-day flash malware detection. In: 36th IEEE symposium on security and privacy"},{"key":"1058_CR21","unstructured":"Kaspersky Lab (2015) The great bank robbery. http:\/\/www.kaspersky.com\/about\/news\/virus\/2015\/Carbanak-cybergang-steals-1-bn-USD-from-100-financial-institutions-worldwide"},{"key":"1058_CR22","unstructured":"Kavukcuoglu K, Sermanet P, Boureau Y, Gregor K, Mathieu M, LeCun Y (2010) Learning convolutional feature hierarchies for visual recognition. In: Advances in neural information processing systems (NIPS 2010), vol 23"},{"key":"1058_CR23","unstructured":"Kephart J, Arnold W (1994) Automatic extraction of computer virus signatures. In: Proceedings of 4th virus bulletin international conference, pp 178\u2013184"},{"key":"1058_CR24","doi-asserted-by":"crossref","unstructured":"Kolter J, Maloof M (2004) Learning to detect malicious executables in the wild. In: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining (ACM SIGKDD\u201904), pp 470\u2013478","DOI":"10.1145\/1014052.1014105"},{"key":"1058_CR25","doi-asserted-by":"crossref","unstructured":"Kong D, Yan G (2013) Discriminant malware distance learning on structural information for automated malware classification. In: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 1357\u20131365","DOI":"10.1145\/2487575.2488219"},{"issue":"5","key":"1058_CR26","first-page":"205","volume":"9","author":"Y Li","year":"2015","unstructured":"Li Y, Ma R, Jiao R (2015) A hybrid malicious code detection method based on deep learning. Int J Secur Appl 9(5):205\u2013216","journal-title":"Int J Secur Appl"},{"issue":"2","key":"1058_CR27","first-page":"865","volume":"16","author":"Y Lv","year":"2015","unstructured":"Lv Y, Duan Y, Kang W, Li Z, Wang F (2015) Traffic flow prediction with big data: a deep learning approach. IEEE Trans Intell Transp Syst 16(2):865\u2013873","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"1058_CR28","unstructured":"Masud MM, Al-Khateeb TM, Hamlen KW, Gao J, Khan L, Han J, Thuraisingham B (2008) Cloud-based malware detection for evolving data streams. In: ACM transactions on management information systems (TMIS), vol 2(3), pp 16:1\u201316:27"},{"key":"1058_CR29","doi-asserted-by":"crossref","unstructured":"Menahem E, Shabtai A, Levhar A (2013) Detecting malware through temporal function-based features. In: Proceedings of the 2013 ACM SIGSAC conference on computer and communications security, pp 1379\u20131382","DOI":"10.1145\/2508859.2512505"},{"key":"1058_CR30","doi-asserted-by":"crossref","unstructured":"Ouellette J, Pfeffer A, Lakhotia A (2013) Countering malware evolution using cloud-based learning. In: 8th international conference on malicious and unwanted software (MALWARE), pp 85\u201394","DOI":"10.1109\/MALWARE.2013.6703689"},{"key":"1058_CR31","doi-asserted-by":"crossref","unstructured":"Park Y, Zhang Q, Reeves D, Mulukutla V (2010) AntiBot: clustering common semantic patterns for bot detection. In: IEEE 34th annual computer software and applications conference, pp 262\u2013272","DOI":"10.1109\/COMPSAC.2010.33"},{"key":"1058_CR32","unstructured":"Schultz M, Eskin E, Zadok E (2001) Data mining methods for detection of new malicious executables. In: Proccedings of IEEE symposium on security and privacy"},{"key":"1058_CR33","doi-asserted-by":"crossref","unstructured":"Shah S, Jani H, Shetty S, Bhowmick K (2013) Virus detection using artificial neural networks. Int J Comput Appl 84(5):3\u201321","DOI":"10.5120\/14572-2695"},{"key":"1058_CR34","unstructured":"Sung A, Xu J, Chavez P, Mukkamala S (2005) Static analyzer of vicious executables (save). In: Proceedings of the 20th annual computer security applications conference (ACSAC), pp 326\u2013334"},{"key":"1058_CR35","unstructured":"Symantec (2016) Internet security threat report. https:\/\/www.symantec.com\/secu-rity-center\/threat-report"},{"key":"1058_CR36","unstructured":"Teh YW, Hinton GE (2001) Rate-coded restricted Boltzmann machines for face recognition. In: Proceedings of advances in neural information processing systems, pp 908\u2013914"},{"key":"1058_CR37","first-page":"3371","volume":"11","author":"P Vincent","year":"2010","unstructured":"Vincent P, Larochelle H, Lajoie I, Bengio Y, Manzagol P (2010) Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. J Mach Learn Res 11:3371\u20133408","journal-title":"J Mach Learn Res"},{"key":"1058_CR38","unstructured":"Wang J, Deng P, Fan Y, Jaw L, Liu Y (2003) Virus detection using data mining techniques. In: Proccedings of IEEE 37th annual 2003 international Carnahan conference security technology"},{"key":"1058_CR39","unstructured":"Wueest C (2016) Symantec security response: financial threats 2015. http:\/\/www.syman-tec.com\/content\/en\/us\/enterprise\/media\/security_response\/whitepapers\/financial-threats-2015.pdf"},{"key":"1058_CR40","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1007\/s11416-008-0082-4","volume":"4","author":"Y Ye","year":"2008","unstructured":"Ye Y, Wang D, Li T, Ye D, Jiang Q (2008) An intelligent PE-malware detection system based on association mining. J Comput Virol 4:323\u2013334","journal-title":"J Comput Virol"},{"key":"1058_CR41","doi-asserted-by":"crossref","unstructured":"Ye Y, Wang D, Li T, Ye D (2007) IMDS: intelligent malware detection system. In: Proceedings of the 13th ACM SIGKDD, pp 1043\u20131047","DOI":"10.1145\/1281192.1281308"},{"key":"1058_CR42","doi-asserted-by":"crossref","unstructured":"Ye Y, Li T, Zhu S, Zhuang W, Tas E, Gupta U, Abdulhayoglu M (2011) Combining file content and file relations for cloud based malware detection. In: Proceedings of ACM international conference on knowledge discovery and data mining (ACM SIGKDD), pp 222\u2013230","DOI":"10.1145\/2020408.2020448"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-017-1058-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-017-1058-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-017-1058-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T13:25:57Z","timestamp":1692797157000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-017-1058-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,9]]},"references-count":42,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2018,2]]}},"alternative-id":["1058"],"URL":"https:\/\/doi.org\/10.1007\/s10115-017-1058-9","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,9]]},"assertion":[{"value":"12 May 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 April 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 May 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}