{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T04:56:23Z","timestamp":1725857783890},"publisher-location":"Cham","reference-count":42,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319406664"},{"type":"electronic","value":"9783319406671"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-40667-1_21","type":"book-chapter","created":{"date-parts":[[2016,6,11]],"date-time":"2016-06-11T11:19:03Z","timestamp":1465643943000},"page":"419-439","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Adaptive Semantics-Aware Malware Classification"],"prefix":"10.1007","author":[{"given":"Bojan","family":"Kolosnjaji","sequence":"first","affiliation":[]},{"given":"Apostolis","family":"Zarras","sequence":"additional","affiliation":[]},{"given":"Tamas","family":"Lengyel","sequence":"additional","affiliation":[]},{"given":"George","family":"Webster","sequence":"additional","affiliation":[]},{"given":"Claudia","family":"Eckert","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,6,12]]},"reference":[{"key":"21_CR1","unstructured":"The Cuckoo Sandbox. https:\/\/www.cuckoosandbox.org\/"},{"key":"21_CR2","unstructured":"VirusTotal. http:\/\/www.virustotal.com"},{"key":"21_CR3","unstructured":"Alvarez, V.M.: Yara. http:\/\/plusvic.github.io\/yara\/"},{"key":"21_CR4","doi-asserted-by":"crossref","unstructured":"Anderson, B., Storlie, C., Lane, T.: Improving malware classification: bridging the static\/dynamic gap. In: Workshop on Security and Artificial Intelligence (AISec) (2012)","DOI":"10.1145\/2381896.2381900"},{"key":"21_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1007\/978-3-540-74320-0_10","volume-title":"Recent Advances in Intrusion Detection","author":"M Bailey","year":"2007","unstructured":"Bailey, M., Oberheide, J., Andersen, J., Mao, Z.M., Jahanian, F., Nazario, J.: Automated classification and analysis of internet malware. In: Kruegel, C., Lippmann, R., Clark, A. (eds.) RAID 2007. LNCS, vol. 4637, pp. 178\u2013197. Springer, Heidelberg (2007)"},{"key":"21_CR6","unstructured":"Bayer, U., Comparetti, P.M., Hlauschek, C., Kruegel, C., Kirda, E.: Scalable, behavior-based malware clustering. In: ISOC Network and Distributed System Security Symposium (NDSS) (2009)"},{"key":"21_CR7","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Chau, D.H., Nachenberg, C., Wilhelm, J., Wright, A., Faloutsos, C.: Polonium: tera-scale graph mining and inference for malware detection. In: SIAM International Conference on Data Mining (SDM) (2011)","DOI":"10.1137\/1.9781611972818.12"},{"key":"21_CR9","doi-asserted-by":"crossref","unstructured":"Dahl, G.E., Stokes, J.W., Deng, L., Yu, D.: Large-scale malware classification using random projections and neural networks. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2013)","DOI":"10.1109\/ICASSP.2013.6638293"},{"issue":"1","key":"21_CR10","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1002\/aris.1440380105","volume":"38","author":"ST Dumais","year":"2004","unstructured":"Dumais, S.T.: Latent semantic analysis. Ann. Rev. Inf. Sci. Technol. 38(1), 188\u2013230 (2004)","journal-title":"Ann. Rev. Inf. Sci. Technol."},{"key":"21_CR11","doi-asserted-by":"crossref","unstructured":"Dumitras, T., Shou, D.: Toward a standard benchmark for computer security research: the Worldwide Intelligence Network Environment (WINE). In: Workshop on Building Analysis Datasets and Gathering Experience Returns for Security (BADGERS) (2011)","DOI":"10.1145\/1978672.1978683"},{"key":"21_CR12","unstructured":"Ester, M., Kriegel, H.-P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Kdd (1996)"},{"issue":"1","key":"21_CR13","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.cose.2008.08.003","volume":"28","author":"P Garcia-Teodoro","year":"2009","unstructured":"Garcia-Teodoro, P., Diaz-Verdejo, J., Maci\u00e1-Fern\u00e1ndez, G., V\u00e1zquez, E.: Anomaly-based network intrusion detection: techniques, systems and challenges. Comput. Secur. 28(1), 18\u201328 (2009)","journal-title":"Comput. Secur."},{"volume-title":"Binarypig: Scalable Static Binary Analysis Over Hadoop","year":"2013","author":"Z Hanif","key":"21_CR14","unstructured":"Hanif, Z., Calhoun, T., Trost, J.: Binarypig: Scalable Static Binary Analysis Over Hadoop. Black Hat, USA (2013)"},{"volume-title":"Internet-Scale File Analysis","year":"2015","author":"Z Hanif","key":"21_CR15","unstructured":"Hanif, Z., Lengyel, T.K., Webster, G.D.: Internet-Scale File Analysis. Black Hat, USA (2015)"},{"key":"21_CR16","unstructured":"Heller, K., Svore, K., Keromytis, A.D., Stolfo, S.: One class support vector machines for detecting anomalous windows registry accesses. In: Workshop on Data Mining for Computer Security (DMSEC) (2003)"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Jang, J., Brumley, D., Venkataraman, S.: Bitshred: feature hashing malware for scalable triage and semantic analysis. In: Conference on Computer and Communications Security (CCS) (2011)","DOI":"10.1145\/2046707.2046742"},{"key":"21_CR18","doi-asserted-by":"publisher","DOI":"10.1002\/0471660264","volume-title":"Combining Pattern Classifiers: Methods and Algorithms","author":"LI Kuncheva","year":"2004","unstructured":"Kuncheva, L.I.: Combining Pattern Classifiers: Methods and Algorithms. Wiley, New York (2004)"},{"key":"21_CR19","doi-asserted-by":"crossref","unstructured":"Lengyel, T.K., Maresca, S., Payne, B.D., Webster, G.D., Vogl, S., Kiayias, A.: Scalability, fidelity and stealth in the Drakvuf dynamic malware analysis system. In: Annual Computer Security Applications Conference (ACSAC) (2014)","DOI":"10.1145\/2664243.2664252"},{"key":"21_CR20","unstructured":"Leung, K., Leckie, C.: Unsupervised anomaly detection in network intrusion detection using clusters. In: Australasian Conference on Computer Science (2005)"},{"key":"21_CR21","unstructured":"Maxwell, K.: Maltrieve. https:\/\/github.com\/krmaxwell\/maltrieve"},{"key":"21_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/11760146_9","volume-title":"Intelligence and Security Informatics","author":"D Newman","year":"2006","unstructured":"Newman, D., Chemudugunta, C., Smyth, P., Steyvers, M.: Analyzing entities and topics in news articles using statistical topic models. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B., Wang, F.-Y. (eds.) ISI 2006. LNCS, vol. 3975, pp. 93\u2013104. Springer, Heidelberg (2006)"},{"key":"21_CR23","doi-asserted-by":"crossref","unstructured":"Perdisci, R., U, M.C.: VAMO: towards a fully automated malware clustering validity analysis. In: Annual Computer Security Applications Conference (ACSAC) (2012)","DOI":"10.1145\/2420950.2420999"},{"key":"21_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1007\/978-3-642-38631-2_16","volume-title":"Network and System Security","author":"J Pfoh","year":"2013","unstructured":"Pfoh, J., Schneider, C., Eckert, C.: Leveraging string kernels for malware detection. In: Lopez, J., Huang, X., Sandhu, R. (eds.) NSS 2013. LNCS, vol. 7873, pp. 206\u2013219. Springer, Heidelberg (2013)"},{"key":"21_CR25","doi-asserted-by":"crossref","unstructured":"Ramage, D., Hall, D., Nallapati, R., Manning, C.D.: Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora. In: Conference on Empirical Methods in Natural Language Processing (2009)","DOI":"10.3115\/1699510.1699543"},{"key":"21_CR26","unstructured":"\u0158eh\u016f\u0159ek, R., Sojka, P.: Software framework for topic modelling with large corpora. In: Workshop on New Challenges for NLP Frameworks (2010)"},{"key":"21_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1007\/978-3-540-70542-0_6","volume-title":"Detection of Intrusions and Malware, and Vulnerability Assessment","author":"K Rieck","year":"2008","unstructured":"Rieck, K., Holz, T., Willems, C., D\u00fcssel, P., Laskov, P.: Learning and classification of malware behavior. In: Zamboni, D. (ed.) DIMVA 2008. LNCS, vol. 5137, pp. 108\u2013125. Springer, Heidelberg (2008)"},{"key":"21_CR28","unstructured":"Roberts, J.-M.: Virus Share. https:\/\/virusshare.com\/"},{"key":"21_CR29","unstructured":"Schultz, M.G., Eskin, E., Zadok, E., Stolfo, S.J.: Data mining methods for detection of new malicious executables. In: Symposium on Security and Privacy (2001)"},{"key":"21_CR30","unstructured":"Stringhini, G., Egele, M., Zarras, A., Holz, T., Kruegel, C., Vigna, G.: B@bel: leveraging email delivery for spam mitigation. In: USENIX Security Symposium (2012)"},{"key":"21_CR31","doi-asserted-by":"crossref","unstructured":"Tegeler, F., Fu, X., Vigna, G., Kruegel, C.: Botfinder: finding bots in network traffic without deep packet inspection. In: International Conference on Emerging Networking Experiments and Technologies (CoNEXT) (2012)","DOI":"10.1145\/2413176.2413217"},{"issue":"476","key":"21_CR32","doi-asserted-by":"publisher","first-page":"1566","DOI":"10.1198\/016214506000000302","volume":"101","author":"YW Teh","year":"2006","unstructured":"Teh, Y.W., Jordan, M.I., Beal, M.J., Blei, D.M.: Hierarchical Dirichlet processes. J. Am. Stat. Assoc. 101(476), 1566\u20131581 (2006)","journal-title":"J. Am. Stat. Assoc."},{"key":"21_CR33","unstructured":"The MITRE Corporation. CRITS. https:\/\/crits.github.io\/"},{"key":"21_CR34","unstructured":"VirusTotal. File Statistics. https:\/\/www.virustotal.com\/en\/statistics\/"},{"key":"21_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000001","volume":"1","author":"MJ Wainwright","year":"2008","unstructured":"Wainwright, M.J., Jordan, M.I.: Graphical models, exponential families, and variational inference. Found. Trends Mach. Learn. 1, 1\u2013305 (2008)","journal-title":"Found. Trends Mach. Learn."},{"key":"21_CR36","unstructured":"Wang, C., Paisley, J.W., Blei, D.M.: Online variational inference for the hierarchical Dirichlet process. In: International Conference on Artificial Intelligence and Statistics (2011)"},{"key":"21_CR37","unstructured":"Warrender, C., Forrest, S., Pearlmutter, B.: Detecting intrusions using system calls: alternative data models. In: Symposium on Security and Privacy (1999)"},{"key":"21_CR38","unstructured":"Wicherski, G.: Pehash: a novel approach to fast malware clustering. In: USENIX Workshop on Large-Scale Exploits and Emergent Threats (LEET) (2009)"},{"key":"21_CR39","doi-asserted-by":"crossref","unstructured":"Xiao, H., Eckert, C.: Efficient online sequence prediction with side information. In: IEEE International Conference on Data Mining (ICDM) (2013)","DOI":"10.1109\/ICDM.2013.31"},{"key":"21_CR40","doi-asserted-by":"crossref","unstructured":"Xiao, H., Stibor, T.: A supervised topic transition model for detecting malicious system call sequences. In: Workshop on Knowledge Discovery, Modeling and Simulation (2011)","DOI":"10.1145\/2023568.2023577"},{"key":"21_CR41","doi-asserted-by":"crossref","unstructured":"Zarras, A., Papadogiannakis, A., Gawlik, R., Holz, T.: Automated generation of models for fast and precise detection of HTTP-based malware. In: Annual Conference on Privacy, Security and Trust (PST) (2014)","DOI":"10.1109\/PST.2014.6890946"},{"issue":"16","key":"21_CR42","first-page":"321","volume":"16","author":"D Zhou","year":"2004","unstructured":"Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Sch\u00f6lkopf, B.: Learning with local and global consistency. Adv. Neural Inf. Process. Syst. 16(16), 321\u2013328 (2004)","journal-title":"Adv. Neural Inf. Process. Syst."}],"container-title":["Lecture Notes in Computer Science","Detection of Intrusions and Malware, and Vulnerability Assessment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-40667-1_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T10:28:55Z","timestamp":1710325735000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-40667-1_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319406664","9783319406671"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-40667-1_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]},"assertion":[{"value":"12 June 2016","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}