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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.

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:

19067

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.

Supported By:

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