Abstract
With the advent of the 4th industrial era, ICT technologies such as artificial intelligence and autonomous driving are rapidly developing. However, unlike these positive aspects, malicious hackers target IoT devices around us using malwares such as viruses, worms, and Trojan horses to steal confidential information or prevent IoT devices from operating normally. In addition, malicious hackers are developing and using intelligent and advanced malwares so that malware cannot be easily detected. In recent years, studied/development of malware detection technology using machine learning and deep learning technologies has been conducted to detect intelligent and advanced variants of malwares. In this paper, based on the KISA Data Challenge Dataset, basic machine learning based malware detection is performed and the limitations that have occurred are analyzed.
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