Machine learning estimation of signal in laser timing probing for hardware security applications
Laser Timing Probe (LTP, also known as laser voltage probing, LVP) is a failure analysis technique that is widely used in fault isolation and product debugging. Electrical waveforms at a location of the probed site can be predicted when given a change of properties of a reflected beam of light due t...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/147371 |
| _version_ | 1826123939028402176 |
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| author | Leong, Chang Peng |
| author2 | Gan Chee Lip |
| author_facet | Gan Chee Lip Leong, Chang Peng |
| author_sort | Leong, Chang Peng |
| collection | NTU |
| description | Laser Timing Probe (LTP, also known as laser voltage probing, LVP) is a failure analysis technique that is widely used in fault isolation and product debugging. Electrical waveforms at a location of the probed site can be predicted when given a change of properties of a reflected beam of light due to the regular change of biasing of a device that has been brightened by light. The output of the signal to noise ratio is very low. Thus, multiple traces are necessary as it will be averaged to produce a readable waveform. Many applications of LTP have proven its superiority in recovering encrypted or sensitive data. However, the reliance on regular test sequences is imminent. As such, if waveforms from LTP can be predicted with a minimum number of traces, it will be able to reduce the need for counter measures. Machine learning has been around for a while and it has tremendous capabilities especially in the field of pattern recognition. In this project, the primary goal is to use machine learning on MATLAB platform and the knowledge of supervised machine learning to help reduce the number of traces. |
| first_indexed | 2024-10-01T06:12:31Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/147371 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:12:31Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1473712023-03-04T15:47:09Z Machine learning estimation of signal in laser timing probing for hardware security applications Leong, Chang Peng Gan Chee Lip School of Materials Science and Engineering CLGan@ntu.edu.sg Engineering::Materials Laser Timing Probe (LTP, also known as laser voltage probing, LVP) is a failure analysis technique that is widely used in fault isolation and product debugging. Electrical waveforms at a location of the probed site can be predicted when given a change of properties of a reflected beam of light due to the regular change of biasing of a device that has been brightened by light. The output of the signal to noise ratio is very low. Thus, multiple traces are necessary as it will be averaged to produce a readable waveform. Many applications of LTP have proven its superiority in recovering encrypted or sensitive data. However, the reliance on regular test sequences is imminent. As such, if waveforms from LTP can be predicted with a minimum number of traces, it will be able to reduce the need for counter measures. Machine learning has been around for a while and it has tremendous capabilities especially in the field of pattern recognition. In this project, the primary goal is to use machine learning on MATLAB platform and the knowledge of supervised machine learning to help reduce the number of traces. Bachelor of Engineering (Materials Engineering) 2021-04-01T07:21:40Z 2021-04-01T07:21:40Z 2021 Final Year Project (FYP) Leong, C. P. (2021). Machine learning estimation of signal in laser timing probing for hardware security applications. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147371 https://hdl.handle.net/10356/147371 en MSE/20/032 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Materials Leong, Chang Peng Machine learning estimation of signal in laser timing probing for hardware security applications |
| title | Machine learning estimation of signal in laser timing probing for hardware security applications |
| title_full | Machine learning estimation of signal in laser timing probing for hardware security applications |
| title_fullStr | Machine learning estimation of signal in laser timing probing for hardware security applications |
| title_full_unstemmed | Machine learning estimation of signal in laser timing probing for hardware security applications |
| title_short | Machine learning estimation of signal in laser timing probing for hardware security applications |
| title_sort | machine learning estimation of signal in laser timing probing for hardware security applications |
| topic | Engineering::Materials |
| url | https://hdl.handle.net/10356/147371 |
| work_keys_str_mv | AT leongchangpeng machinelearningestimationofsignalinlasertimingprobingforhardwaresecurityapplications |