Privacy filters for smartphones
The smartphone adoption has been on a rise. Smartphone manufacturers are designing and building more sophisticated variants of smartphone to grow their market share and meet growing demands. More sensors are incorporated into smartphones to increase and improve smartphone functionalities. Indiscrimi...
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2019
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sg-ntu-dr.10356-773622023-07-07T16:28:20Z Privacy filters for smartphones Lee, William Wei Chien Tay Wee Peng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering The smartphone adoption has been on a rise. Smartphone manufacturers are designing and building more sophisticated variants of smartphone to grow their market share and meet growing demands. More sensors are incorporated into smartphones to increase and improve smartphone functionalities. Indiscriminate collection of smartphone sensor data poses a risk on user privacy. This project aims to implement a filter for preserving privacy. The implementation uses accelerometer data collected from the author’s smartphone. The author classifies the state parameters into two groups, the private parameters and the public parameters. The filter protects privacy of the private parameters while minimising the estimation error of public parameters. Bachelor of Engineering (Information Engineering and Media) 2019-05-27T09:21:21Z 2019-05-27T09:21:21Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77362 en Nanyang Technological University 49 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Lee, William Wei Chien Privacy filters for smartphones |
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The smartphone adoption has been on a rise. Smartphone manufacturers are designing and building more sophisticated variants of smartphone to grow their market share and meet growing demands. More sensors are incorporated into smartphones to increase and improve smartphone functionalities. Indiscriminate collection of smartphone sensor data poses a risk on user privacy. This project aims to implement a filter for preserving privacy. The implementation uses accelerometer data collected from the author’s smartphone. The author classifies the state parameters into two groups, the private parameters and the public parameters. The filter protects privacy of the private parameters while minimising the estimation error of public parameters. |
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Tay Wee Peng |
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Tay Wee Peng Lee, William Wei Chien |
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Final Year Project |
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Lee, William Wei Chien |
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Lee, William Wei Chien |
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Privacy filters for smartphones |
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Privacy filters for smartphones |
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Privacy filters for smartphones |
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Privacy filters for smartphones |
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Privacy filters for smartphones |
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privacy filters for smartphones |
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2019 |
url |
http://hdl.handle.net/10356/77362 |
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1772828130413641728 |