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- W4362503722 abstract "IoT malware analysis is a challenging task for researchers worldwide because of its difficulty. IoT devices lack homogeneous processor architecture and security design, making malware analysis challenging. Therefore, IoT malware detection is a prime focus of research. Various researches have been underway for adequate solutions, adapted in all frames and under a single umbrella. This paper looked at advanced IoT malware detection requirements and proposed a hybrid model to solve the existing problem. We have also provided a background overview of IoT malware, concerning two famous malware samples Mirai and Darlloz, and future research challenges. Furthermore, we have collected, compared, and analyzed the key research in IoT security specifically for malware analysis and attempted to provide critical decision points during the development of security architecture." @default.
- W4362503722 created "2023-04-05" @default.
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- W4362503722 date "2023-01-01" @default.
- W4362503722 modified "2023-09-25" @default.
- W4362503722 title "A Hybrid Mechanism for Advance IoT Malware Detection" @default.
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- W4362503722 doi "https://doi.org/10.1007/978-981-19-8136-4_21" @default.
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