Birthmark based identification of software piracy using Haar wavelet
Piracy of software is an increasing problem of modern day software industry. Piracy of software is the unlawful use of software or part of it without proper permission as described in license agreement. Software piracy is a serious crime but not taken seriously by most people....
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/80830/1/BIRTH.pdf |
| _version_ | 1825951346326503424 |
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| author | Nazir, Shah Shahzad, Sara Wirza, Rahmita Amin, Rohul Ahsan, Muhammad Mukhtar, Neelam Garcia-Magarino, Ivan Lloret, Jaime |
| author_facet | Nazir, Shah Shahzad, Sara Wirza, Rahmita Amin, Rohul Ahsan, Muhammad Mukhtar, Neelam Garcia-Magarino, Ivan Lloret, Jaime |
| author_sort | Nazir, Shah |
| collection | UPM |
| description | Piracy of software is an increasing problem of modern day software industry. Piracy of software is the unlawful use of software or part of it without proper permission as described in license agreement. Software piracy is a serious crime but not taken seriously by most people. Preventing software piracy is very important for the growing software industry. Efforts are being made to prevent and detect software piracy. Several techniques have been developed most important of which is software birthmark. The birthmark of a software is the intrinsic properties of software. A recent research shows that a features based software birthmark can be used as a strong mechanism to detect piracy of a software and how much piracy performed has been performed on it. An objective measure is needed to overcome this problem and to compare features based birthmark of a software which efficiently and precisely detect piracy in reproduction of software. The proposed study presents Haar wavelet collocation method for software features (birthmark) to detect piracy. The proposed method gives an exclusive solution for the features based birthmark of software and is then further used for comparisons of birthmark. The results of the proposed study show the effectiveness in terms of accuracy and efficiency to compare the features based software. |
| first_indexed | 2024-03-06T10:28:38Z |
| format | Article |
| id | upm.eprints-80830 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:28:38Z |
| publishDate | 2019 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | upm.eprints-808302020-10-15T22:15:18Z http://psasir.upm.edu.my/id/eprint/80830/ Birthmark based identification of software piracy using Haar wavelet Nazir, Shah Shahzad, Sara Wirza, Rahmita Amin, Rohul Ahsan, Muhammad Mukhtar, Neelam Garcia-Magarino, Ivan Lloret, Jaime Piracy of software is an increasing problem of modern day software industry. Piracy of software is the unlawful use of software or part of it without proper permission as described in license agreement. Software piracy is a serious crime but not taken seriously by most people. Preventing software piracy is very important for the growing software industry. Efforts are being made to prevent and detect software piracy. Several techniques have been developed most important of which is software birthmark. The birthmark of a software is the intrinsic properties of software. A recent research shows that a features based software birthmark can be used as a strong mechanism to detect piracy of a software and how much piracy performed has been performed on it. An objective measure is needed to overcome this problem and to compare features based birthmark of a software which efficiently and precisely detect piracy in reproduction of software. The proposed study presents Haar wavelet collocation method for software features (birthmark) to detect piracy. The proposed method gives an exclusive solution for the features based birthmark of software and is then further used for comparisons of birthmark. The results of the proposed study show the effectiveness in terms of accuracy and efficiency to compare the features based software. Elsevier 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/80830/1/BIRTH.pdf Nazir, Shah and Shahzad, Sara and Wirza, Rahmita and Amin, Rohul and Ahsan, Muhammad and Mukhtar, Neelam and Garcia-Magarino, Ivan and Lloret, Jaime (2019) Birthmark based identification of software piracy using Haar wavelet. Mathematics and Computers in Simulation, 166. pp. 144-154. ISSN 0378-4754; ESSN: 1872-7166 https://www.sciencedirect.com/science/article/pii/S0378475419301478 10.1016/j.matcom.2019.04.010 |
| spellingShingle | Nazir, Shah Shahzad, Sara Wirza, Rahmita Amin, Rohul Ahsan, Muhammad Mukhtar, Neelam Garcia-Magarino, Ivan Lloret, Jaime Birthmark based identification of software piracy using Haar wavelet |
| title | Birthmark based identification of software piracy using Haar wavelet |
| title_full | Birthmark based identification of software piracy using Haar wavelet |
| title_fullStr | Birthmark based identification of software piracy using Haar wavelet |
| title_full_unstemmed | Birthmark based identification of software piracy using Haar wavelet |
| title_short | Birthmark based identification of software piracy using Haar wavelet |
| title_sort | birthmark based identification of software piracy using haar wavelet |
| url | http://psasir.upm.edu.my/id/eprint/80830/1/BIRTH.pdf |
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