Deep learning and big data technologies for IoT security
Mohamed Ahzam Amanullah,Riyaz Ahamed Ariyaluran Habeeb,Riyaz Ahamed Ariyaluran Habeeb,Fariza Hanum Nasaruddin,Abdullah Gani,Abdullah Gani,Ejaz Ahmed,Abdul Salam Mohamed Nainar,Nazihah Md Akim,Muhammad Imran +9 more
TLDR
A comprehensive survey on state-of-the-art deep learning, IoT security, and big data technologies is conducted and a thematic taxonomy is derived from the comparative analysis of technical studies of the three aforementioned domains.About:
This article is published in Computer Communications.The article was published on 2020-02-01 and is currently open access. It has received 193 citations till now. The article focuses on the topics: Big data.read more
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References
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Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Journal ArticleDOI
A fast learning algorithm for deep belief nets
TL;DR: A fast, greedy algorithm is derived that can learn deep, directed belief networks one layer at a time, provided the top two layers form an undirected associative memory.
Journal ArticleDOI
Backpropagation applied to handwritten zip code recognition
Yann LeCun,Bernhard E. Boser,John S. Denker,D. Henderson,Richard Howard,W. Hubbard,Lawrence D. Jackel +6 more
TL;DR: This paper demonstrates how constraints from the task domain can be integrated into a backpropagation network through the architecture of the network, successfully applied to the recognition of handwritten zip code digits provided by the U.S. Postal Service.
Journal ArticleDOI
Interrater reliability: the kappa statistic
TL;DR: While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.
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Evaluation: from Precision, Recall and F-measure to ROC, Informedness, Markedness and Correlation
TL;DR: E elegant connections between the concepts of Informedness, Markedness, Correlation and Significance as well as their intuitive relationships with Recall and Precision are demonstrated.