Delayered IC chip image analysis

Reverse engineering (RE) of an IC is essential for intellectual property (IP) protection and hardware security. It is a process of unpacking a manufactured IC and obtaining its original schematic or netlists in order to examine for its connections, functionality and quality. Current industrial solut...

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主要作者: Hong, Xue Nong
其他作者: Gwee Bah Hwee
格式: Final Year Project
語言:English
出版: 2018
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在線閱讀:http://hdl.handle.net/10356/74634
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spelling sg-ntu-dr.10356-746342023-07-07T16:58:38Z Delayered IC chip image analysis Hong, Xue Nong Gwee Bah Hwee School of Electrical and Electronic Engineering Temasek Laboratories @ NTU DRNTU::Engineering Reverse engineering (RE) of an IC is essential for intellectual property (IP) protection and hardware security. It is a process of unpacking a manufactured IC and obtaining its original schematic or netlists in order to examine for its connections, functionality and quality. Current industrial solutions mostly depend on human work. However, as IC complexity increases dramatically each year, a fully automatic solution for the most work-intensive part of RE process is in urgent need. The objective of this project was to develop an automatic software solution for RE. In this project, an algorithm was developed to stich IC images automatically based on their phase differences. Three different approaches for circuit extraction in IC images, including image processing, classifiers and convolutional neural networks (CNN), were explored and compared. Detailed procedures for each of the approach were also discussed and included in the report. At the end of the project, a Matlab based image stitching algorithm was developed and a python based CNN model for feature extraction was trained and tested. The model performed semantic segmentation on IC images with a precision of 99.924% and the inference only took half a second for an IC image. Bachelor of Engineering 2018-05-22T07:20:08Z 2018-05-22T07:20:08Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74634 en Nanyang Technological University 67 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Hong, Xue Nong
Delayered IC chip image analysis
description Reverse engineering (RE) of an IC is essential for intellectual property (IP) protection and hardware security. It is a process of unpacking a manufactured IC and obtaining its original schematic or netlists in order to examine for its connections, functionality and quality. Current industrial solutions mostly depend on human work. However, as IC complexity increases dramatically each year, a fully automatic solution for the most work-intensive part of RE process is in urgent need. The objective of this project was to develop an automatic software solution for RE. In this project, an algorithm was developed to stich IC images automatically based on their phase differences. Three different approaches for circuit extraction in IC images, including image processing, classifiers and convolutional neural networks (CNN), were explored and compared. Detailed procedures for each of the approach were also discussed and included in the report. At the end of the project, a Matlab based image stitching algorithm was developed and a python based CNN model for feature extraction was trained and tested. The model performed semantic segmentation on IC images with a precision of 99.924% and the inference only took half a second for an IC image.
author2 Gwee Bah Hwee
author_facet Gwee Bah Hwee
Hong, Xue Nong
format Final Year Project
author Hong, Xue Nong
author_sort Hong, Xue Nong
title Delayered IC chip image analysis
title_short Delayered IC chip image analysis
title_full Delayered IC chip image analysis
title_fullStr Delayered IC chip image analysis
title_full_unstemmed Delayered IC chip image analysis
title_sort delayered ic chip image analysis
publishDate 2018
url http://hdl.handle.net/10356/74634
_version_ 1772826387679281152