{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T14:56:32Z","timestamp":1782140192038,"version":"3.54.5"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T00:00:00Z","timestamp":1602201600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T00:00:00Z","timestamp":1602201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871140"],"award-info":[{"award-number":["61871140"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mobile Netw Appl"],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1007\/s11036-020-01656-7","type":"journal-article","created":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T02:02:41Z","timestamp":1602208961000},"page":"1680-1689","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection"],"prefix":"10.1007","volume":"29","author":[{"given":"Zhihong","family":"Tian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiyuan","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4202-7802","authenticated-orcid":false,"given":"Jing","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanbin","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,10,9]]},"reference":[{"issue":"4","key":"1656_CR1","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/MWC.2008.4599222","volume":"15","author":"X Du","year":"2008","unstructured":"Du X, Chen HH (2008) Security in wireless sensor networks. IEEE Wirel Commun Mag 15(4):60\u201366","journal-title":"IEEE Wirel Commun Mag"},{"key":"1656_CR2","unstructured":"Gupta BB, Agrawal DP, Yamaguchi S (2014) Call for chapters: handbook of research on modern cryptographic solutions for computer and cyber security"},{"key":"1656_CR3","doi-asserted-by":"crossref","unstructured":"X. Xu, Z. Rong, Z.X. Wu, T. Zhou, and C. K. Tse. Phys Rev E, 95(5), id. 052302, 2017","DOI":"10.1103\/PhysRevE.95.052302"},{"key":"1656_CR4","doi-asserted-by":"crossref","unstructured":"Mao Y, Xu X, Rong Z, Wu Z-X (2018) The emergence of cooperation-extortion alliance on scale-free networks with normalized payoff. EPL Europhysics Lett 122(5)","DOI":"10.1209\/0295-5075\/122\/50005"},{"issue":"1","key":"1656_CR5","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1049\/iet-cps.2017.0010","volume":"2","author":"R Atat","year":"2017","unstructured":"Atat R, Liu L, Chen H et al (2017) Enabling cyber-physical communication in 5G cellular networks: challenges, spatial spectrum sensing, and cyber-security. IET Cyber-Phys Syst: Theory Appl 2(1):49\u201354","journal-title":"IET Cyber-Phys Syst: Theory Appl"},{"issue":"3","key":"1656_CR6","doi-asserted-by":"publisher","first-page":"1223","DOI":"10.1109\/TWC.2009.060598","volume":"8","author":"X Du","year":"2009","unstructured":"Du X, Guizani M, Xiao Y, Chen HH (2009) Transactions papers, A Routing-Driven Elliptic Curve Cryptography based Key Management Scheme for Heterogeneous Sensor Networks. IEEE Trans Wireless Commun 8(3):1223\u20131229","journal-title":"IEEE Trans Wireless Commun"},{"key":"1656_CR7","doi-asserted-by":"crossref","unstructured":"Plageras A P, Stergiou C, Psannis K E, et al (2017) Efficient IoT-based sensor BIG data collection-processing and analysis in smart buildings. Futur Gener Comput Syst","DOI":"10.1016\/j.future.2017.09.082"},{"key":"1656_CR8","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.ins.2019.04.011","volume":"491","author":"Z Tian","year":"2019","unstructured":"Tian Z, Li M, Qiu M, Sun Y, Shen S (2019) Block-DES: a secure digital evidence system using Blockchain. Inf Sci 491:151\u2013165. https:\/\/doi.org\/10.1016\/j.ins.2019.04.011","journal-title":"Inf Sci"},{"key":"1656_CR9","doi-asserted-by":"publisher","unstructured":"Zhu L, Li M, Zhang Z, Qin Z (2018) ASAP: An Anonymous Smart-Parking and Payment Scheme in Vehicular Networks. IEEE Trans Dependable Secure Comput. https:\/\/doi.org\/10.1109\/TDSC.2018.2850780","DOI":"10.1109\/TDSC.2018.2850780"},{"key":"1656_CR10","doi-asserted-by":"publisher","unstructured":"Tian Y, Guo J, Wu Y, Lin H (2019) Towards Attack and Defense Views of Rational Delegation of Computation. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2019.2908858","DOI":"10.1109\/ACCESS.2019.2908858"},{"key":"1656_CR11","doi-asserted-by":"publisher","unstructured":"Tian Z, Shi W, Wang Y, Zhu C, Du X, Su S, Sun Y, Guizani N (2019) Real Time Lateral Movement Detection based on Evidence Reasoning Network for Edge Computing Environment. IEEE Trans Ind Inform. https:\/\/doi.org\/10.1109\/TII.2019.2907754","DOI":"10.1109\/TII.2019.2907754"},{"key":"1656_CR12","doi-asserted-by":"publisher","unstructured":"Zhihong Tian, Shen Su, Wei Shi, Xiang Yu, Xiaojiang Du, and Mohsen Guizani. A Data-driven Model for Future Internet Route Decision Modeling. Future Gen Comput Syst. 2019. https:\/\/doi.org\/10.1016\/j.future.2018.12.054","DOI":"10.1016\/j.future.2018.12.054"},{"key":"1656_CR13","doi-asserted-by":"publisher","first-page":"35355","DOI":"10.1109\/ACCESS.2018.2846590","volume":"6","author":"Z Tian","year":"2018","unstructured":"Tian Z, Cui Y, An L, Su S, Yin X, Yin L, Cui X (2018) A Real-Time Correlation of Host-Level Events in Cyber Range Service for Smart Campus. IEEE Access 6:35355\u201335364. https:\/\/doi.org\/10.1109\/ACCESS.2018.2846590","journal-title":"IEEE Access"},{"key":"1656_CR14","doi-asserted-by":"publisher","unstructured":"Qingfeng Tan, Yue Gao, Jinqiao Shi, Xuebin Wang, Binxing Fang, and ZhiHong Tian. Towards a Comprehensive Insight into the Eclipse Attacks of Tor Hidden Services. IEEE Internet Things J. 2018https:\/\/doi.org\/10.1109\/JIOT.2018.2846624","DOI":"10.1109\/JIOT.2018.2846624"},{"issue":"3","key":"1656_CR15","doi-asserted-by":"publisher","first-page":"628","DOI":"10.1109\/JSAC.2018.2815442","volume":"36","author":"L Zhu","year":"2018","unstructured":"Zhu L, Tang X, Shen M, Xiaojiang D, Guizani M (2018) Privacy-preserving DDoS attack detection using cross-domain traffic in software defined networks. IEEE J Select Areas Commun 36(3):628\u2013643","journal-title":"IEEE J Select Areas Commun"},{"key":"1656_CR16","doi-asserted-by":"crossref","unstructured":"Tian Z, Wang Y, Sun Y, Qiu J (2019) Location privacy challenges in Mobile edge computing: classification and exploration. IEEE Netw","DOI":"10.1109\/ICC.2019.8761370"},{"issue":"11\u201312","key":"1656_CR17","doi-asserted-by":"publisher","first-page":"2314","DOI":"10.1016\/j.comcom.2007.04.009","volume":"30","author":"Y Xiao","year":"2007","unstructured":"Xiao Y, Rayi V, Sun B, Du X, Hu F, Galloway M (2007) A survey of key management schemes in wireless sensor networks. J Comput Commun 30(11\u201312):2314\u20132341","journal-title":"J Comput Commun"},{"issue":"1","key":"1656_CR18","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.adhoc.2006.05.012","volume":"5","author":"X Du","year":"2007","unstructured":"Du X, Xiao Y, Guizani M, Chen HH (2007) An effective key management scheme for heterogeneous sensor networks. Ad Hoc Networks Elsevier 5(1):24\u201334","journal-title":"Ad Hoc Networks Elsevier"},{"key":"1656_CR19","doi-asserted-by":"publisher","unstructured":"Ma Y, Wu Y, Li J, Ge J (2020) APCN: a scalable architecture for balancing accountability and privacy in large-scale content-based networks. Inf Sci. https:\/\/doi.org\/10.1016\/j.ins.2019.01.054, In Press","DOI":"10.1016\/j.ins.2019.01.054"},{"issue":"10","key":"1656_CR20","doi-asserted-by":"publisher","first-page":"2218","DOI":"10.1109\/JSAC.2018.2869958","volume":"36","author":"X Cheng","year":"2018","unstructured":"Cheng X, Wu Y, Min G, Zomaya AY (2018) Network function virtualization in dynamic networks: a stochastic perspective. IEEE J Select Areas Commun 36(10):2218\u20132232","journal-title":"IEEE J Select Areas Commun"},{"key":"1656_CR21","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.future.2018.09.043","volume":"92","author":"Y Zuo","year":"2019","unstructured":"Zuo Y, Wu Y, Min G, Cui L (2019) Learning-based network path planning for traffic engineering. Futur Gener Comput Syst 92:59\u201367. https:\/\/doi.org\/10.1016\/j.future.2018.09.043","journal-title":"Futur Gener Comput Syst"},{"key":"1656_CR22","doi-asserted-by":"publisher","first-page":"14451","DOI":"10.1109\/ACCESS.2018.2806483","volume":"6","author":"Y Ma","year":"2018","unstructured":"Ma Y, Wu Y, Ge J, Li J (2018) An architecture for accountable anonymous access in the internet-of-things network. IEEE Access 6:14451\u201314461","journal-title":"IEEE Access"},{"key":"1656_CR23","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.ins.2013.10.005","volume":"262","author":"G Katz","year":"2014","unstructured":"Katz G, Elovici Y, Shapira B (2014) CoBAn: A context based model for data leakage prevention. J Inf Sci: Int J Arch 262:137\u2013158","journal-title":"J Inf Sci: Int J Arch"},{"issue":"11","key":"1656_CR24","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1109\/MCOM.2007.4378332","volume":"45","author":"Y Xiao","year":"2007","unstructured":"Xiao Y, Du X, Zhang J, Guizani S (2007) Internet protocol television (IPTV): the killer application for the next generation internet. IEEE Commun Mag 45(11):126\u2013134","journal-title":"IEEE Commun Mag"},{"key":"1656_CR25","unstructured":"Singh A, Patel SS (2014) Applying Modified K-Nearest Neighbor to Detect Insider Threat in Collaborative Information Systems. Int J Innovativ Res Sci Eng Technol 3(6)"},{"key":"1656_CR26","doi-asserted-by":"crossref","unstructured":"Parveen P, Weger ZR, Thuraisingham B, Hamlen K, Khan L (2011) Supervised Learning for Insider Threat Detection Using Stream Mining. In: Proceeding of 23rd IEEE International Conference on Tools with Artificial Intelligence","DOI":"10.1109\/ICTAI.2011.176"},{"key":"1656_CR27","doi-asserted-by":"crossref","unstructured":"Stolfo SJ, Apap F, Eskin E, Heller K, Hershkop S, Honig A, Svore K (2005) A comparative evaluation of two algorithms for Windows Registry Anomaly Detection. J Comput Secur 13 (4)","DOI":"10.3233\/JCS-2005-13403"},{"key":"1656_CR28","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TII.2017.2769106","volume":"14","author":"K Hamedani","year":"2018","unstructured":"Hamedani K, Liu L, Rachad A, Wu J, Yi Y (2018) Reservoir Computing Meets Smart Grids: Attack Detection Using Delayed Feedback Networks. IEEE Trans Ind Inform 14:734\u2013743. https:\/\/doi.org\/10.1109\/TII.2017.2769106","journal-title":"IEEE Trans Ind Inform"},{"key":"1656_CR29","doi-asserted-by":"crossref","unstructured":"Hodo E, Bellekens X, Hamilton A, Dubouilh P-L (2016) Threat analysis of IoT networks using artificial neural network intrusion detection system. Int Sympos Netw Comput Commun (ISNCC) 17","DOI":"10.1109\/ISNCC.2016.7746067"},{"key":"1656_CR30","doi-asserted-by":"publisher","unstructured":"Panda, M., Abraham, A. & Patra, M. R. Discriminative multinomial naive bayes for network intrusion detection. 2010 6th international conference on information assurance and security, IAS 2010 5\u201310 (2010). https:\/\/doi.org\/10.1109\/ISIAS.2010.5604193","DOI":"10.1109\/ISIAS.2010.5604193"},{"issue":"4","key":"1656_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.proeng.2012.01.827","volume":"30","author":"M Panda","year":"2012","unstructured":"Panda M, Abraham A, Patra MR (2012) A hybrid intelligent approach for network intrusion detection. Procedia Eng 30(4):1\u20139","journal-title":"Procedia Eng"},{"key":"1656_CR32","doi-asserted-by":"crossref","unstructured":"Heba FE, Darwish A, Hassanien AE, et al (2010) Principle components analysis and Support Vector Machine based Intrusion Detection System. In Proceedings of International Conference on Intelligent Systems Design and Applications. IEEE:363\u2013367","DOI":"10.1109\/ISDA.2010.5687239"},{"key":"1656_CR33","doi-asserted-by":"crossref","unstructured":"Syarif I, Prugelbennett A, Wills G (2012) Unsupervised Clustering Approach for Network Anomaly Detection","DOI":"10.1007\/978-3-642-30507-8_13"},{"key":"1656_CR34","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1007\/978-3-642-32129-0_34","volume-title":"Proceedings of International Conference on Contemporary Computing","author":"P Gogoi","year":"2012","unstructured":"Gogoi P, Bhuyan MH, Bhattacharyya DK et al (2012) Packet and Flow Based Network Intrusion Dataset. In: Proceedings of International Conference on Contemporary Computing. Springer, Berlin, pp 322\u2013334"},{"key":"1656_CR35","doi-asserted-by":"crossref","unstructured":"Eid HF, Salama MA, Hassanien AE, et al. (2011) Bi-layer behavioral-based feature selection approach for network intrusion classification","DOI":"10.1007\/978-3-642-27189-2_21"},{"key":"1656_CR36","doi-asserted-by":"crossref","unstructured":"Al-Ayyoub M, Nuseir A, Alsmearat K, et al. (2017) Deep learning for Arabic NLP: a survey. Journal of Computational Science","DOI":"10.1016\/j.jocs.2017.11.011"},{"key":"1656_CR37","first-page":"1","volume":"99","author":"AM Elmisery","year":"2017","unstructured":"Elmisery AM, Sertovic M, Gupta BB (2017) Cognitive Privacy Middleware for Deep Learning Mashup in Environmental IoT. IEEE Access 99:1\u20131","journal-title":"IEEE Access"},{"key":"1656_CR38","doi-asserted-by":"crossref","unstructured":"Al-Smadi M, Qawasmeh O, Al-Ayyoub M, et al. (2017) Deep Recurrent Neural Network vs. Support Vector Machine for Aspect-Based Sentiment Analysis of Arabic Hotels\u2019 Reviews. J Comput Sci","DOI":"10.1016\/j.jocs.2017.11.006"},{"key":"1656_CR39","unstructured":"Mozer MC (1995) A focused backpropagation algorithm for temporal pattern recognition. Backpropagation. L. Erlbaum Associates Inc.: 349\u2013381"},{"issue":"10","key":"1656_CR40","doi-asserted-by":"publisher","first-page":"1550","DOI":"10.1109\/5.58337","volume":"78","author":"PJ Werbos","year":"1990","unstructured":"Werbos PJ (1990) Backpropagation through time: what it does and how to do it. Proc IEEE 78(10):1550\u20131560","journal-title":"Proc IEEE"},{"key":"1656_CR41","volume-title":"Supervised Sequence Labelling with Recurrent Neural Networks | Springer","author":"Deutsch","year":"2012","unstructured":"Deutsch (2012) Supervised Sequence Labelling with Recurrent Neural Networks | Springer. Springer-Verlag, Berlin Heidelberg"},{"key":"1656_CR42","doi-asserted-by":"publisher","first-page":"74854","DOI":"10.1109\/ACCESS.2018.2881422","volume":"6","author":"J Qiu","year":"2018","unstructured":"Qiu J, Chai Y, Liu Y, ZhaoQuan G, Li S, Tian Z (2018) Automatic Non-Taxonomic Relation Extraction from Big Data in Smart City. IEEE Access 6:74854\u201374864. https:\/\/doi.org\/10.1109\/ACCESS.2018.2881422","journal-title":"IEEE Access"},{"key":"1656_CR43","doi-asserted-by":"crossref","unstructured":"Javaid A, Niyaz Q, Sun W, et al. (2016) A Deep Learning Approach for Network Intrusion Detection System. In Proceedings of International Conference on Bio-Inspired Information and Communications Technologies. ICST Inst Comput Sci Social-Inform Telecommun Eng:21\u201326","DOI":"10.4108\/eai.3-12-2015.2262516"},{"key":"1656_CR44","unstructured":"Jiang F, Y Fu, Gupta BB, Lou F, Rho S (2018) Deep Learning based Multi-channel intelligent attack detection for Data Security. IEEE Trans Sustain Comput"},{"key":"1656_CR45","doi-asserted-by":"crossref","unstructured":"Kim J, Kim J, Thu H L T, et al. (2016) Long Short Term Memory Recurrent Neural Network Classifier for Intrusion Detection. In: Proceedings of International Conference on Platform Technology and Service. IEEE:1\u20135","DOI":"10.1109\/PlatCon.2016.7456805"},{"key":"1656_CR46","unstructured":"Vaswani A, Shazeer N, Parmar N, et al. (2017) Attention is all you need. Proc Adv Neural Inform Process Syst:5998\u20136008"},{"key":"1656_CR47","unstructured":"Abadi M, Agarwal A (2015) Tensor Flow: Large-scale machine learning on heterogeneous systems. Software available from tensorflow.org"},{"issue":"1","key":"1656_CR48","first-page":"106","volume":"20","author":"J Inglis","year":"1976","unstructured":"Inglis J (1976) A mathematical theory of evidence. Technometrics 20(1):106\u2013106","journal-title":"Technometrics"},{"issue":"2","key":"1656_CR49","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1109\/72.279181","volume":"5","author":"Y Bengio","year":"2002","unstructured":"Bengio Y, Simard P, Frasconi P (2002) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Netw 5(2):157\u2013166","journal-title":"IEEE Trans Neural Netw"},{"key":"1656_CR50","unstructured":"Chae H-s, Jo B-h, Choi S-H, Park T-k (2013) Feature Selection for Intrusion Detection using NSL-KDD. Recent Adv Comput Sci"}],"container-title":["Mobile Networks and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11036-020-01656-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11036-020-01656-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11036-020-01656-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T13:20:47Z","timestamp":1744204847000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11036-020-01656-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,9]]},"references-count":50,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["1656"],"URL":"https:\/\/doi.org\/10.1007\/s11036-020-01656-7","relation":{},"ISSN":["1383-469X","1572-8153"],"issn-type":[{"value":"1383-469X","type":"print"},{"value":"1572-8153","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,9]]},"assertion":[{"value":"23 September 2020","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 October 2020","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}