Journal ArticleDOI
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
TLDR
The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/ DM for cyber security is presented, and some recommendations on when to use a given method are provided.Abstract:
This survey paper describes a focused literature survey of machine learning (ML) and data mining (DM) methods for cyber analytics in support of intrusion detection. Short tutorial descriptions of each ML/DM method are provided. Based on the number of citations or the relevance of an emerging method, papers representing each method were identified, read, and summarized. Because data are so important in ML/DM approaches, some well-known cyber data sets used in ML/DM are described. The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/DM for cyber security is presented, and some recommendations on when to use a given method are provided.read more
Citations
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Proceedings ArticleDOI
A Framework for Collaborative Learning in Secure High-Dimensional Space
Mohsen Imani,Yeseong Kim,M. Sadegh Riazi,John Messerly,Patric Liu,Farinaz Koushanfar,Tajana Rosing +6 more
TL;DR: A novel framework, called SecureHD, is proposed, which provides a secure learning solution based on the idea of high-dimensional (HD) computing, which can send data to the cloud with no security concerns, while the cloud can perform the offloaded tasks without additional decryption steps.
Journal ArticleDOI
Data-Driven Cyber Security in Perspective—Intelligent Traffic Analysis
TL;DR: A new research methodology of data-driven cyber security (DDCS) and its application in social and Internet traffic analysis is demonstrated and challenges and future directions in this field are discussed.
Proceedings ArticleDOI
Intrusion Detection System for NSL-KDD Dataset Using Convolutional Neural Networks
Yalei Ding,Yuqing Zhai +1 more
TL;DR: The model improves the accuracy of the intrusion detection and provides a new research direction for intrusion detection using a typical deep learning methodology.
Proceedings ArticleDOI
Generalization of Deep Learning for Cyber-Physical System Security: A Survey
TL;DR: This paper intends to provide a concise survey of the regularization methods for DL algorithms used in security-related applications in CPSs and thus could be used to improve the generalization capability of DL based cyber-physical system based security applications.
Posted Content
IoT Security Techniques Based on Machine Learning.
TL;DR: The attack model for IoT systems is investigated, the IoT security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning are reviewed, and the challenges that need to be addressed are discussed.
References
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