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- W4210848556 abstract "The biggest invention of 21st century is the social media. It is biggest platform which is using to share data, files and documents. Even it is using to share thoughts, ideas and feelings using different tools and techniques. People are hyper connected with each other and they are continuously sharing the information. For criminals, deploying malware in such scenario is very easy and propagating malware through JPEG images and QR Code is one of the best and most advanced method. Using steganography techniques, criminals embedded the malicious codes with legitimate or innocent looking images. This malicious content is just few line of codes which exploit the vulnerability of application. It give remote access of this system to the attacker which can do criminal act. In this framework, our primary purpose is to find the presence of any code or data in image. After it, the major section of this framework based upon the finding of code and its adverse effects. This framework shows the corresponding solution to the malicious code presence in JPEG images and QR code which are spreading through online social networking sites." @default.
- W4210848556 created "2022-02-09" @default.
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- W4210848556 date "2021-04-30" @default.
- W4210848556 modified "2023-09-26" @default.
- W4210848556 title "Machine Learning Based Solution for the Detection of Malicious JPEG Image and QR Code" @default.
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- W4210848556 doi "https://doi.org/10.48175/ijarsct-1071" @default.
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