{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,12]],"date-time":"2025-04-12T00:44:40Z","timestamp":1744418680063,"version":"3.37.3"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T00:00:00Z","timestamp":1562025600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T00:00:00Z","timestamp":1562025600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1007\/s13042-019-00978-7","type":"journal-article","created":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T19:03:04Z","timestamp":1562094184000},"page":"339-358","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An empirical study to estimate the stability of random forest classifier on the hybrid features recommended by filter based feature selection technique"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9556-1342","authenticated-orcid":false,"given":"S. L. Shiva","family":"Darshan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C. D.","family":"Jaidhar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,2]]},"reference":[{"key":"978_CR1","unstructured":"(2014) Cuckoo sandbox\u2014automated malware analysis. \nhttps:\/\/cuckoosandbox.org\/\n\n. Accessed Jan 2018"},{"key":"978_CR2","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/S1361-3723(13)70072-1","volume":"8","author":"M Ahmadi","year":"2013","unstructured":"Ahmadi M, Sami A, Rahimi H (2013) Yadegari B (2013) Malware detection by behavioural sequential patterns. Comput Fraud Secur 8:11\u201319","journal-title":"Comput Fraud Secur"},{"key":"978_CR3","doi-asserted-by":"publisher","unstructured":"Alam MS, Vuong ST (2013) Random forest classification for detecting android malware. In: 2013 IEEE International Conference on green computing and communications and IEEE internet of things and IEEE cyber, physical and social computing. IEEE, pp 663\u2013669. \nhttps:\/\/doi.org\/10.1109\/GreenCom-iThings-CPSCom.2013.122","DOI":"10.1109\/GreenCom-iThings-CPSCom.2013.122"},{"key":"978_CR4","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/978-981-10-5421-1_14","volume-title":"Applications and Techniques in Information Security","author":"Naqqash Aman","year":"2017","unstructured":"Aman N, Saleem Y, Abbasi FH, Shahzad F (2017) A hybrid approach for malware family classification. In: Applications and techniques in information security, vol 719. Springer, Singapore, pp 169\u2013180. \nhttps:\/\/doi.org\/10.1007\/978-981-10-5421-1_14"},{"key":"978_CR5","doi-asserted-by":"publisher","unstructured":"Amin M (2016) A survey of financial losses due to malware. In: Proceedings of the second international conference on information and communication technology for competitive Strategies. ACM, pp 145:1\u2013145:4. \nhttps:\/\/doi.org\/10.1145\/2905055.2905362","DOI":"10.1145\/2905055.2905362"},{"key":"978_CR6","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1007\/978-3-319-49145-5_6","volume-title":"Lecture Notes in Computer Science","author":"Saba Awan","year":"2016","unstructured":"Awan S, Saqib NA (2016) Detection of malicious executables using static and dynamic features of portable executable (PE) file. In: Security, privacy and anonymity in computation, communication and storage, vol 10067. Springer, Cham, pp 48\u201358. \nhttps:\/\/doi.org\/10.1007\/978-3-319-49145-5_6"},{"key":"978_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2014\/260905","volume":"2014","author":"J Bai","year":"2014","unstructured":"Bai J, Wang J, Zou G (2014) A malware detection scheme based on mining format information. Sci World J 2014:1\u201311. \nhttps:\/\/doi.org\/10.1155\/2014\/260905","journal-title":"Sci World J"},{"key":"978_CR8","doi-asserted-by":"crossref","unstructured":"Baldangombo U, Jambaljav N, Horng SJ (2013) A static malware detection system using data mining methods. CoRR. \narXiv:1308.2831","DOI":"10.5121\/ijaia.2013.4411"},{"issue":"1","key":"978_CR9","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s11416-006-0012-2","volume":"2","author":"U Bayer","year":"2006","unstructured":"Bayer U, Moser A, Kruegel C, Kirda E (2006) Dynamic analysis of malicious code. J Comput Virol 2(1):67\u201377","journal-title":"J Comput Virol"},{"key":"978_CR10","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1007\/978-3-319-19578-0_34","volume-title":"IFIP Advances in Information and Communication Technology","author":"Mohamed Belaoued","year":"2015","unstructured":"Belaoued M, Mazouzi S (2015) A real-time PE-malware detection system based on chi-square test and PE-file features. In: Computer science and its applications, vol 456. Springer, Cham, pp 416\u2013425. \nhttps:\/\/doi.org\/10.1007\/978-3-319-19578-0_34"},{"issue":"1","key":"978_CR11","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45(1):5\u201332","journal-title":"Mach Learn"},{"key":"978_CR12","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/978-1-4419-9326-7_5","volume-title":"Ensemble Machine Learning","author":"Adele Cutler","year":"2012","unstructured":"Cutler A, Cutler DR, Stevens JR (2012) Random forests. In: Ensemble machine learning: methods and applications. Springer, Boston, MA, pp 157\u2013175. \nhttps:\/\/doi.org\/10.1007\/978-1-4419-9326-7_5"},{"issue":"1","key":"978_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11416-015-0261-z","volume":"13","author":"A Damodaran","year":"2017","unstructured":"Damodaran A, Di Troia F, Visaggio CA, Austin TH, Stamp M (2017) A comparison of static, dynamic, and hybrid analysis for malware detection. J Comput Virol Hacking Tech 13(1):1\u201312","journal-title":"J Comput Virol Hacking Tech"},{"key":"978_CR14","doi-asserted-by":"publisher","unstructured":"Darshan SLS, Kumara MAA, Jaidhar CD (2016) Windows malware detection based on cuckoo sandbox generated report using machine learning algorithm. In: 2016 11th international conference on industrial and information systems (ICIIS). IEEE, pp 534-539. \nhttps:\/\/doi.org\/10.1109\/ICIINFS.2016.8262998","DOI":"10.1109\/ICIINFS.2016.8262998"},{"issue":"2","key":"978_CR15","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1109\/TIFS.2015.2491300","volume":"11","author":"S Das","year":"2016","unstructured":"Das S, Liu Y, Zhang W, Chandramohan M (2016) Semantics-based online malware detection: towards efficient real-time protection against malware. IEEE Trans Inform For Secur 11(2):289\u2013302","journal-title":"IEEE Trans Inform For Secur"},{"issue":"2","key":"978_CR16","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s11416-016-0274-2","volume":"13","author":"B David","year":"2017","unstructured":"David B, Filiol E, Gallienne K (2017) Structural analysis of binary executable headers for malware detection optimization. J Comput Virol Hacking Tech 13(2):87\u201393","journal-title":"J Comput Virol Hacking Tech"},{"key":"978_CR17","doi-asserted-by":"publisher","unstructured":"David OE, Netanyahu NS (2015) DeepSign: deep learning for automatic malware signature generation and classification. In: 2015 International joint conference on neural networks (IJCNN). IEEE, pp 1\u20138. \nhttps:\/\/doi.org\/10.1109\/IJCNN.2015.7280815","DOI":"10.1109\/IJCNN.2015.7280815"},{"key":"978_CR18","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.cose.2014.04.003","volume":"44","author":"Y Ding","year":"2014","unstructured":"Ding Y, Dai W, Yan S, Zhang Y (2014) Control flow-based opcode behavior analysis for malware detection. Comput Secur 44:65\u201374","journal-title":"Comput Secur"},{"key":"978_CR19","doi-asserted-by":"publisher","unstructured":"Faruki P, Laxmi V, Gaur MS, Vinod P (2012) Behavioural detection with API call-grams to identify malicious PE files. In: Proceedings of the first international conference on security of internet of things. ACM, pp 85\u201391. \nhttps:\/\/doi.org\/10.1145\/2490428.2490440","DOI":"10.1145\/2490428.2490440"},{"key":"978_CR20","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1007\/978-0-387-09823-4_66","volume-title":"Data Mining and Knowledge Discovery Handbook","author":"Eibe Frank","year":"2009","unstructured":"Frank E, Hall M, Holmes G, Kirkby R, Pfahringer B, Witten IH, Trigg L (2010) Weka-a machine learning workbench for data mining. In: Data mining and knowledge discovery handbook. Springer, Boston, MA, pp 1269\u20131277. \nhttps:\/\/doi.org\/10.1007\/978-0-387-09823-4_66"},{"key":"978_CR21","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1007\/978-3-642-04180-8_47","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Gokhan Gulgezen","year":"2009","unstructured":"Gulgezen G, Cataltepe Z, Yu L (2009) Stable and accurate feature selection. In: Machine learning and knowledge discovery in databases, vol 5781. Springer, Berlin, Heidelberg, pp 455\u2013468. \nhttps:\/\/doi.org\/10.1007\/978-3-642-04180-8_47"},{"key":"978_CR22","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.future.2014.06.001","volume":"55","author":"S Huda","year":"2016","unstructured":"Huda S, Abawajy J, Alazab M, Abdollalihian M, Islam R, Yearwood J (2016) Hybrids of support vector machine wrapper and filter based framework for malware detection. Future Gener Comput Syst 55:376\u2013390","journal-title":"Future Gener Comput Syst"},{"key":"978_CR23","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.future.2017.12.037","volume":"83","author":"S Huda","year":"2018","unstructured":"Huda S, Islam R, Abawajy J, Yearwood J, Hassan MM, Fortino G (2018) A hybrid-multi filter-wrapper framework to identify run-time behaviour for fast malware detection. Future Gener Comput Sys 83:193\u2013207","journal-title":"Future Gener Comput Sys"},{"issue":"2","key":"978_CR24","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.jnca.2012.10.004","volume":"36","author":"R Islam","year":"2013","unstructured":"Islam R, Tian R, Batten LM, Versteeg S (2013) Classification of malware based on integrated static and dynamic features. J Netw Comput Appl 36(2):646\u2013656","journal-title":"J Netw Comput Appl"},{"key":"978_CR25","doi-asserted-by":"publisher","unstructured":"Jain A, Singh AK (2017) Integrated malware analysis using machine learning. In: 2017 2nd International conference on telecommunication and networks (TEL-NET). IEEE, pp 1\u20138. \nhttps:\/\/doi.org\/10.1109\/TEL-NET.2017.8343554","DOI":"10.1109\/TEL-NET.2017.8343554"},{"key":"978_CR26","doi-asserted-by":"publisher","unstructured":"Kawaguchi N, Omote K (2015) Malware function classification using APIs in initial behavior. In: 2015 10th Asia joint conference on information security. IEEE, pp 138\u2013144. \nhttps:\/\/doi.org\/10.1109\/AsiaJCIS.2015.15","DOI":"10.1109\/AsiaJCIS.2015.15"},{"key":"978_CR27","doi-asserted-by":"publisher","unstructured":"Khoshgoftaar TM, Golawala M, Hulse JV (2007)\u00a0An empirical study of learning from imbalanced data using random forest. In: 19th IEEE international conference on tools with artificial intelligence (ICTAI 2007), vol 2. IEEE, pp 310\u2013317. \nhttps:\/\/doi.org\/10.1109\/ICTAI.2007.46","DOI":"10.1109\/ICTAI.2007.46"},{"key":"978_CR28","first-page":"2721","volume":"7","author":"JZ Kolter","year":"2006","unstructured":"Kolter JZ, Maloof MA (2006) Learning to detect and classify malicious executables in the wild. J Mach Learn Res 7:2721\u20132744","journal-title":"J Mach Learn Res"},{"key":"978_CR29","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.jksus.2018.04.015","volume":"31","author":"A Kumar","year":"2019","unstructured":"Kumar A, Kuppusamy K, Aghila G (2019) A learning model to detect maliciousness of portable executable using integrated feature set. J King Saud Univ Comput Inform Sci 31:252\u2013265","journal-title":"J King Saud Univ Comput Inform Sci"},{"key":"978_CR30","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.diin.2017.10.004","volume":"23","author":"MA Kumara","year":"2017","unstructured":"Kumara MA, Jaidhar C (2017) Leveraging virtual machine introspection with memory forensics to detect and characterize unknown malware using machine learning techniques at hypervisor. Digit Investig 23:99\u2013123","journal-title":"Digit Investig"},{"key":"978_CR31","doi-asserted-by":"crossref","unstructured":"Lee J, Im C, Jeong H (2011) A study of malware detection and classification by comparing extracted strings. In: Proceedings of the 5th international conference on ubiquitous information management and communication. ACM, pp 75:1\u201375:4. \nhttp:\/\/doi.org\/10.1145\/1968613.1968704","DOI":"10.1145\/1968613.1968704"},{"key":"978_CR32","doi-asserted-by":"publisher","unstructured":"Leistner C, Saffari A, Santner J, Bischof H (2009) Semi-supervised random forests. In: 2009 IEEE 12th international conference on computer vision. IEEE, pp 506\u2013513. \nhttps:\/\/doi.org\/10.1109\/ICCV.2009.5459198","DOI":"10.1109\/ICCV.2009.5459198"},{"key":"978_CR33","doi-asserted-by":"crossref","unstructured":"Lengyel TK, Maresca S, Payne BD, Webster GD, Vogl S, Kiayias A (2014) Scalability, fidelity and stealth in the DRAKVUF dynamic malware analysis system. In: Proceedings of the 30th annual computer security applications conference. ACM, pp 386\u2013395. \nhttp:\/\/doi.org\/10.1145\/2664243.2664252","DOI":"10.1145\/2664243.2664252"},{"key":"978_CR34","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.cose.2017.11.010","volume":"73","author":"CH Lin","year":"2018","unstructured":"Lin CH, Pao HK, Liao JW (2018) Efficient dynamic malware analysis using virtual time control mechanics. Comput Secur 73:359\u2013373","journal-title":"Comput Secur"},{"issue":"1","key":"978_CR35","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/s10796-007-9054-3","volume":"10","author":"MM Masud","year":"2008","unstructured":"Masud MM, Khan L, Thuraisingham B (2008) A scalable multi-level feature extraction technique to detect malicious executables. Inform Syst Front 10(1):33\u201345","journal-title":"Inform Syst Front"},{"key":"978_CR36","doi-asserted-by":"crossref","first-page":"S48","DOI":"10.1016\/j.diin.2017.06.007","volume":"22","author":"C Miller","year":"2017","unstructured":"Miller C, Glendowne D, Cook H, Thomas D, Lanclos C, Pape P (2017) Insights gained from constructing a large scale dynamic analysis platform. Digit Investig 22:S48\u2013S56","journal-title":"Digit Investig"},{"key":"978_CR37","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.cose.2015.04.001","volume":"52","author":"A Mohaisen","year":"2015","unstructured":"Mohaisen A, Alrawi O, Mohaisen M (2015) Amal: High-fidelity, behavior-based automated malware analysis and classification. Comput Secur 52:251\u2013266","journal-title":"Comput Secur"},{"key":"978_CR38","doi-asserted-by":"crossref","unstructured":"Moser A, Kruegel C, Kirda E (2007) Limits of static analysis for malware detection. In: Twenty-third annual computer security applications conference (ACSAC 2007). IEEE, pp 421\u2013430. \nhttp:\/\/doi.org\/10.1109\/ACSAC.2007.21","DOI":"10.1109\/ACSAC.2007.21"},{"issue":"9","key":"978_CR39","doi-asserted-by":"crossref","first-page":"4544","DOI":"10.1016\/j.csda.2008.01.028","volume":"52","author":"R Moskovitch","year":"2008","unstructured":"Moskovitch R, Elovici Y, Rokach L (2008) Detection of unknown computer worms based on behavioral classification of the host. Comput Statist Data Anal 52(9):4544\u20134566","journal-title":"Comput Statist Data Anal"},{"issue":"18","key":"978_CR40","doi-asserted-by":"crossref","first-page":"3311","DOI":"10.1002\/sec.1255","volume":"8","author":"M Narouei","year":"2015","unstructured":"Narouei M, Ahmadi M, Giacinto G, Takabi H, Sami A (2015) Dllminer: structural mining for malware detection. Secur Commun Netw 8(18):3311\u20133322","journal-title":"Secur Commun Netw"},{"key":"978_CR41","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-642-31537-4_13","volume-title":"Machine Learning and Data Mining in Pattern Recognition","author":"Thais Mayumi Oshiro","year":"2012","unstructured":"Oshiro TM, Perez PS, Baranauskas JA (2012) How many trees in a Rando forest? In: Machine learning and data mining in pattern recognition, vol 7376. Springer, Berlin, Heidelberg, pp 154\u2013168. \nhttps:\/\/doi.org\/10.1007\/978-3-642-31537-4_13"},{"issue":"8","key":"978_CR42","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","volume":"27","author":"H Peng","year":"2005","unstructured":"Peng H, Long F, Ding C (2005) Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell 27(8):1226\u20131238","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"978_CR43","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/978-3-642-37832-4_21","volume-title":"Advances in Intelligent Systems and Computing","author":"Yong Qiao","year":"2013","unstructured":"Qiao Y, Yang Y, He J, Tang C, Liu Z (2014) CBM: free, automatic malware analysis framework using API call sequences. In: Knowledge engineering and management, vol 214. Springer, Berlin, Heidelberg, pp 225\u2013236. \nhttps:\/\/doi.org\/10.1007\/978-3-642-37832-4_21"},{"issue":"1","key":"978_CR44","first-page":"1","volume":"14","author":"E Raff","year":"2016","unstructured":"Raff E, Zak R, Cox R, Sylvester J, Yacci P, Ward R, Tracy A, McLean M, Nicholas C (2016) An investigation of byte n-gram features for malware classification. J Comput Virol Hacking Tech 14(1):1\u201320","journal-title":"J Comput Virol Hacking Tech"},{"issue":"3","key":"978_CR45","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/s11416-006-0027-8","volume":"2","author":"DKS Reddy","year":"2006","unstructured":"Reddy DKS, Pujari AK (2006) N-gram analysis for computer virus detection. J Comput Virol 2(3):231\u2013239","journal-title":"J Comput Virol"},{"issue":"4","key":"978_CR46","doi-asserted-by":"crossref","first-page":"639","DOI":"10.3233\/JCS-2010-0410","volume":"19","author":"K Rieck","year":"2011","unstructured":"Rieck K, Trinius P, Willems C, Holz T (2011) Automatic analysis of malware behavior using machine learning. J Comput Secur 19(4):639\u2013668","journal-title":"J Comput Secur"},{"issue":"3","key":"978_CR47","doi-asserted-by":"crossref","first-page":"3432","DOI":"10.1016\/j.eswa.2011.09.031","volume":"39","author":"CO Sakar","year":"2012","unstructured":"Sakar CO, Kursun O, Gurgen F (2012) A feature selection method based on kernel canonical correlation analysis and the minimum redundancy-maximum relevance filter method. Expert Syst Appl 39(3):3432\u20133437","journal-title":"Expert Syst Appl"},{"key":"978_CR48","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/S1361-3723(14)70531-7","volume":"9","author":"Z Salehi","year":"2014","unstructured":"Salehi Z, Sami A (2014) Ghiasi M (2014) Using feature generation from api calls for malware detection. Comput Fraud Secur 9:9\u201318","journal-title":"Comput Fraud Secur"},{"key":"978_CR49","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.engappai.2016.12.016","volume":"59","author":"Z Salehi","year":"2017","unstructured":"Salehi Z, Sami A, Ghiasi M (2017) Maar: Robust features to detect malicious activity based on api calls, their arguments and return values. Eng Appl Artif Intell 59:93\u2013102","journal-title":"Eng Appl Artif Intell"},{"key":"978_CR50","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.ins.2011.08.020","volume":"231","author":"I Santos","year":"2013","unstructured":"Santos I, Brezo F, Ugarte-Pedrero X, Bringas PG (2013) Opcode sequences as representation of executables for data-mining-based unknown malware detection. Inform Sci 231:64\u201382","journal-title":"Inform Sci"},{"key":"978_CR51","doi-asserted-by":"publisher","unstructured":"Schultz MG, Eskin E, Zadok F, Stolfo SJ (2001) Data mining methods for detection of new malicious executables. In: Proceedings 2001 IEEE symposium on security and privacy. S&P 2001. IEEE,\u00a0pp 38\u201349. \nhttps:\/\/doi.org\/10.1109\/SECPRI.2001.924286","DOI":"10.1109\/SECPRI.2001.924286"},{"key":"978_CR52","doi-asserted-by":"crossref","unstructured":"Sethi K, Chaudhary SK, Tripathy BK, Bera P (2018) A novel malware analysis framework for malware detection and classification using machine learning approach. In: Proceedings of the 19th international conference on distributed computing and networking. ACM, pp 49:1\u201349:4. \nhttp:\/\/doi.org\/10.1145\/3154273.3154326","DOI":"10.1145\/3154273.3154326"},{"issue":"1","key":"978_CR53","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.istr.2009.03.003","volume":"14","author":"A Shabtai","year":"2009","unstructured":"Shabtai A, Moskovitch R, Elovici Y, Glezer C (2009) Detection of malicious code by applying machine learning classifiers on static features: a state-of-the-art survey. Inform Secur Tech Rep 14(1):16\u201329","journal-title":"Inform Secur Tech Rep"},{"key":"978_CR54","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1016\/j.procs.2015.02.149","volume":"46","author":"P Shijo","year":"2015","unstructured":"Shijo P, Salim A (2015) Integrated static and dynamic analysis for malware detection. Proc Comput Sci 46:804\u2013811","journal-title":"Proc Comput Sci"},{"key":"978_CR55","doi-asserted-by":"crossref","unstructured":"Tsyganok K, Tumoyan E, Babenko L, Anikeev M (2012) Classification of polymorphic and metamorphic malware samples based on their behavior. In: Proceedings of the fifth international conference on security of information and networks. ACM, pp 111\u2013116. \nhttp:\/\/doi.org\/10.1145\/2388576.2388591","DOI":"10.1145\/2388576.2388591"},{"key":"978_CR56","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1007\/978-3-642-22709-7_55","volume-title":"Advances in Computing and Communications","author":"P. Vinod","year":"2011","unstructured":"Vinod P, Laxmi V, Gaur MS (2011) Scattered feature space for malware analysis. In: Advances in computing and communications, vol 190. Springer, Berlin, Heidelberg, pp 562\u2013571. \nhttps:\/\/doi.org\/10.1007\/978-3-642-22709-7_55"},{"key":"978_CR57","doi-asserted-by":"publisher","unstructured":"Vyas R, Luo X, McFarland N, Justice C (2017) Investigation of malicious portable executable file detection on the network using supervised learning techniques. In: 2017 IFIP\/IEEE symposium on integrated network and service management (IM). IEEE, pp 941\u2013946. \nhttps:\/\/doi.org\/10.23919\/INM.2017.7987416","DOI":"10.23919\/INM.2017.7987416"},{"issue":"2","key":"978_CR58","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MSP.2007.45","volume":"5","author":"C Willems","year":"2007","unstructured":"Willems C, Holz T, Freiling F (2007) Toward automated dynamic malware analysis using cwsandbox. IEEE Secur Priv 5(2):32\u201339","journal-title":"IEEE Secur Priv"},{"key":"978_CR59","first-page":"41","volume-title":"Detection of Intrusions and Malware, and Vulnerability Assessment","author":"Guanhua Yan","year":"2013","unstructured":"Yan G, Brown N, Kong D (2013) Exploring discriminatory features for automated malware classification. In: International conference on detection of intrusions and malware, and vulnerability assessment. Springer, New York, pp 41\u201361"},{"key":"978_CR60","unstructured":"Yang Y, Pedersen JO (1997) A comparative study on feature selection in text categorization. In: Proceedings of the fourteenth international conference on machine learning. Morgan Kaufmann Publishers Inc., pp 412\u2013420. \nhttp:\/\/dl.acm.org\/citation.cfm?id=645526.657137"},{"issue":"4","key":"978_CR61","doi-asserted-by":"crossref","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(4):323\u2013334","journal-title":"J Comput Virol"},{"issue":"4","key":"978_CR62","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1007\/s11416-008-0108-y","volume":"5","author":"Y Ye","year":"2009","unstructured":"Ye Y, Chen L, Wang D, Li T, Jiang Q, Zhao M (2009) Sbmds: an interpretable string based malware detection system using svm ensemble with bagging. J Comput Virol 5(4):283\u2013293","journal-title":"J Comput Virol"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00978-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-019-00978-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00978-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:16:48Z","timestamp":1593562608000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-019-00978-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,2]]},"references-count":62,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["978"],"URL":"https:\/\/doi.org\/10.1007\/s13042-019-00978-7","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2019,7,2]]},"assertion":[{"value":"4 May 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 June 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}