Physical Unclonable Functions Data Set
Download: Data Folder, Data Set Description
Abstract: The dataset is generated from Physical Unclonable Functions (PUFs) simulation, specifically XOR Arbiter PUFs. PUFs are used for authentication purposes. For more info, refer to our paper below.
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Data Set Characteristics: |
Multivariate |
Number of Instances: |
6000000 |
Area: |
Computer |
Attribute Characteristics: |
Integer |
Number of Attributes: |
129 |
Date Donated |
2018-10-08 |
Associated Tasks: |
Classification |
Missing Values? |
N/A |
Number of Web Hits: |
23390 |
Source:
Ahmad O. Aseeri (a.aseeri '@' psau.edu.sa), Yu Zhuang (yu.zhuang '@' ttu.edu) - Department of Computer Science, Texas Tech University, United States
Mohammed Saeed Alkatheiri (msalkatheri '@' uj.edu.sa) - Faculty of Computing and Information Technology, University of Jeddah, Saudi Arabia
Data Set Information:
Attribute Information:
There are two datasets generated from k-XOR Arbiter PUFs simulation:
(1) 5-XOR_128bit dataset:
This dataset is generated using 5-XOR arbiters of 128bit stages PUF. It consists of 6 million rows and 129 attributes where the last attribute is the class label (1 or -1). It is divided into two sets: training set (5 million) and testing set (1 million).
(1) 6-XOR_64bit dataset:
This dataset is generated using 6-XOR arbiters of 64bit stages PUF. It consists of 2.4 million rows and 65 attributes where the last attribute is the class label (1 or -1). It is divided into two sets: training set (2 million) and testing set (400K).
Relevant Papers:
[1] Aseeri, A. O., Zhuang, Y., & Alkatheiri, M. S. (2018, July). A Machine Learning-Based Security Vulnerability Study on XOR PUFs for Resource-Constraint Internet of Things. In 2018 IEEE International Congress on Internet of Things (ICIOT) (pp. 49-56). IEEE.
Citation Request:
The use of this dataset in publications should be acknowledged by referencing publication [1] listed above.
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