Document Type
Article
Publication Date
6-2023
Abstract
Intellectual Property (IP) includes ideas, innovations, methodologies, works of authorship (viz., literary and artistic works), emblems, brands, images, etc. This property is intangible since it is pertinent to the human intellect. Therefore, IP entities are indisputably vulnerable to infringements and modifications without the owner’s consent. IP protection regulations have been deployed and are still in practice, including patents, copyrights, contracts, trademarks, trade secrets, etc., to address these challenges. Unfortunately, these protections are insufficient to keep IP entities from being changed or stolen without permission. As for this, some IPs require hardware IP protection mechanisms, and others require software IP protection techniques. To secure these IPs, researchers have explored the domain of Intellectual Property Protection (IPP) using different approaches. In this paper, we discuss the existing IP rights and concurrent breakthroughs in the field of IPP research; provide discussions on hardware IP and software IP attacks and defense techniques; summarize different applications of IP protection; and lastly, identify the challenges and future research prospects in hardware and software IP security.
Recommended Citation
Tauhid, Ashraful, et al. "A survey on security analysis of machine learning-oriented hardware and software intellectual property." High-Confidence Computing (2023): 100114. https://doi.org/10.1016/j.hcc.2023.100114
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Title
High-Confidence Computing
DOI
https://doi.org/10.1016/j.hcc.2023.100114
Comments
© 2023 The Author(s). Published by Elsevier B.V. on behalf of Shandong University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).