Sequence-Based Analysis of Static Probe Instrumentation Data for a VMM-Based Anomaly Detection System
暂无分享,去创建一个
[1] Tal Garfinkel,et al. A Virtual Machine Introspection Based Architecture for Intrusion Detection , 2003, NDSS.
[2] Bernhard Plattner,et al. Network anomaly detection in the cloud: The challenges of virtual service migration , 2014, 2014 IEEE International Conference on Communications (ICC).
[3] Kanishka Bhaduri,et al. Detecting Abnormal Machine Characteristics in Cloud Infrastructures , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.
[4] Marius Kloft,et al. Hidden Markov Anomaly Detection , 2015, ICML.
[5] Karama Kanoun,et al. An Anomaly Detection Approach for Scale-Out Storage Systems , 2014, 2014 IEEE 26th International Symposium on Computer Architecture and High Performance Computing.
[6] Antonio Gomariz,et al. VMSP: Efficient Vertical Mining of Maximal Sequential Patterns , 2014, Canadian Conference on AI.
[7] Lei Liu,et al. An LOF-Based Adaptive Anomaly Detection Scheme for Cloud Computing , 2013, 2013 IEEE 37th Annual Computer Software and Applications Conference Workshops.
[8] L. Baum,et al. Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .
[9] Daniele Sgandurra,et al. Evolution of Attacks, Threat Models, and Solutions for Virtualized Systems , 2016, ACM Comput. Surv..
[10] Youki Kadobayashi,et al. Leveraging Static Probe Instrumentation for VM-based Anomaly Detection System , 2015, ICICS.
[11] Youki Kadobayashi,et al. Network-based mimicry anomaly detection using divergence measures , 2015, 2015 International Symposium on Networks, Computers and Communications (ISNCC).
[12] Xiaohui Gu,et al. UBL: unsupervised behavior learning for predicting performance anomalies in virtualized cloud systems , 2012, ICAC '12.
[13] Engin Kirda,et al. A security analysis of Amazon's Elastic Compute Cloud service , 2012, IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN 2012).
[14] Stephen D. Wolthusen,et al. Anomaly Detection for Ephemeral Cloud IaaS Virtual Machines , 2013, NSS.
[15] Vanish Talwar,et al. Statistical techniques for online anomaly detection in data centers , 2011, 12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops.
[16] David Lie,et al. Using VMM-based sensors to monitor honeypots , 2006, VEE '06.
[17] Hong Liu,et al. A behavioral anomaly detection strategy based on time series process portraits for desktop virtualization systems , 2015, Cluster Computing.
[18] Zhi Wang,et al. DKSM: Subverting Virtual Machine Introspection for Fun and Profit , 2010, 2010 29th IEEE Symposium on Reliable Distributed Systems.
[19] Min Chen,et al. Statistical Learning for Anomaly Detection in Cloud Server Systems: A Multi-Order Markov Chain Framework , 2018, IEEE Transactions on Cloud Computing.
[20] Charu C. Aggarwal,et al. Outlier Analysis , 2013, Springer New York.
[21] Helen J. Wang,et al. SubVirt: implementing malware with virtual machines , 2006, 2006 IEEE Symposium on Security and Privacy (S&P'06).
[22] Martin Knahl,et al. Anomaly Detection in IaaS Clouds , 2013, 2013 IEEE 5th International Conference on Cloud Computing Technology and Science.
[23] Luca De Angelis,et al. Model selection in hidden Markov models: a simulation study , 2010 .
[24] Arun Kejariwal,et al. A Novel Technique for Long-Term Anomaly Detection in the Cloud , 2014, HotCloud.
[25] Dongxia Wang,et al. DAC‐Hmm: detecting anomaly in cloud systems with hidden Markov models , 2015, Concurr. Comput. Pract. Exp..
[26] I. Vajda,et al. A new class of metric divergences on probability spaces and its applicability in statistics , 2003 .