M. Abdelsalam, R. Krishnan, and R. Sandhu, Clustering-based IaaS cloud monitoring, 10th IEEE CLOUD, 2017.

M. Abdelsalam, R. Krishnan, and R. Sandhu, Malware detection in cloud infrastructures using convolutional neural networks. In: 11th IEEE CLOUD, 2018.

M. Alazab, S. Venkatraman, P. Watters, and M. Alazab, Zero-day malware detection based on supervised learning algorithms of api call signatures, Proceedings of the Ninth Australasian Data Mining Conference, vol.121, pp.171-182, 2011.

F. Azmandian, M. Moffie, M. Alshawabkeh, J. Dy, J. Aslam et al., Virtual machine monitor-based lightweight intrusion detection, ACM SIGOPS Operating Systems Review, vol.45, 2011.

K. Dahbur, B. Mohammad, and A. B. Tarakji, A survey of risks, threats and vulnerabilities in cloud computing, 2011.

J. A. Dawson, J. T. Mcdonald, L. Hively, T. R. Andel, M. Yampolskiy et al., Phase space detection of virtual machine cyber events through hypervisor-level system call analysis, 2018 1st International Conference on Data Intelligence and Security (ICDIS), pp.159-167, 2018.

J. Demme, On the feasibility of online malware detection with performance counters, ACM SIGARCH Computer Architecture News, vol.41, 2013.

G. Dini, F. Martinelli, A. Saracino, and D. Sgandurra, Madam: a multi-level anomaly detector for android malware, International Conference on Mathematical Methods, Models, and Architectures for Computer Network Security, pp.240-253, 2012.

A. Gholami and E. Laure, Security and privacy of sensitive data in cloud computing: a survey of recent developments, 2016.

B. Grobauer, T. Walloschek, and E. Stocker, Understanding cloud computing vulnerabilities, IEEE Security & Privacy, vol.9, 2011.

N. Gruschka and M. Jensen, Attack surfaces: A taxonomy for attacks on cloud services, pp.276-279, 2010.

M. Jensen, J. Schwenk, N. Gruschka, and L. L. Iacono, On technical security issues in cloud computing, 2009.

Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, Gradient-based learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998.

P. Luckett, J. T. Mcdonald, and J. Dawson, Neural network analysis of system call timing for rootkit detection, 2016 Cybersecurity Symposium (CYBERSEC), pp.1-6, 2016.

P. Mell and T. Grance, The nist definition of cloud computing, 2011.

M. Ozsoy, C. Donovick, I. Gorelik, N. Abu-ghazaleh, and D. Ponomarev, Malware-aware processors: A framework for efficient online malware detection, High Performance Computer Architecture (HPCA), pp.651-661, 2015.

H. S. Pannu, J. Liu, and S. Fu, Aad: Adaptive anomaly detection system for cloud computing infrastructures, Reliable Distributed Systems (SRDS), 2012 IEEE 31st Symposium on, pp.396-397, 2012.

R. S. Pirscoveanu, S. S. Hansen, T. M. Larsen, M. Stevanovic, J. M. Pedersen et al., Analysis of malware behavior: Type classification using machine learning, Cyber Situational Awareness, pp.1-7, 2015.

S. Tobiyama, Y. Yamaguchi, H. Shimada, T. Ikuse, and T. Yagi, Malware detection with deep neural network using process behavior, COMPSAC. vol, vol.2, 2016.

C. Wang, EbAT: online methods for detecting utility cloud anomalies, Proc. of the 6th Middleware Doctoral Symp, 2009.

M. R. Watson, Malware detection in cloud computing infrastructures, IEEE TDSC, vol.13, 2016.

Z. Xiao and Y. Xiao, Security and privacy in cloud computing, IEEE Communications Surveys & Tutorials, vol.15, 2013.

Z. Xu, S. Ray, P. Subramanyan, and S. Malik, Malware detection using machine learning based analysis of virtual memory access patterns, 2017 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.