An increased use of JavaScript in web development has also increased the theft of JavaScript programs. Code of JavaScript program can be easily obtained as most of the browsers provide the simplest way to access it. Watermarking and code obfuscation are the techniques used to safeguard the software. A potential attacker can easily deface watermark and hence watermark cannot completely protect the code. Code obfuscation cannot avoid copy of code. It only prevents others by understanding the logic of the program. Aim is to secure the intellectual property rights of JavaScript developers. Even if the code is obfuscated or a watermark is added in it, this system can easily detect theft. Heap Graph is used to depict the behavior of a JavaScript program as how it calls other objects to fulfil the desired functionality. Agglomerative clustering is used to efficiently merge the heap graphs formed at various points of time. Frequent Subgraph Mining is used to find the subgraph that represents the unique behavior of the program. Finally the subgraph of the genuine program is searched against the graph of the suspected one. The system was made to run on 3000 combinations of websites.
| Autorius: | Swati Patel |
| Leidėjas: | Scholars' Press |
| Išleidimo metai: | 2018 |
| Knygos puslapių skaičius: | 96 |
| ISBN-10: | 6137995968 |
| ISBN-13: | 9786137995969 |
| Formatas: | 220 x 150 x 6 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
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