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Machine Learning based Malware Detection with the 2019 KISA Data Challenge Dataset

Published: 27 September 2021 Publication History

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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Cited By

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  • (2024)Machine Learning and Transformers for Malware Analysis: Overview2024 New Trends in Signal Processing (NTSP)10.23919/NTSP61680.2024.10726311(1-7)Online publication date: 16-Oct-2024
  • (2024)Static Multi Feature-Based Malware Detection Using Multi SPP-net in Smart IoT EnvironmentsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335037919(2487-2500)Online publication date: 2024

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  1. Machine Learning based Malware Detection with the 2019 KISA Data Challenge Dataset

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    cover image ACM Conferences
    ACM ICEA '20: Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications
    December 2020
    219 pages
    ISBN:9781450383042
    DOI:10.1145/3440943
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 27 September 2021

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    Author Tags

    1. Machine Learning
    2. Malware
    3. Malware Detection
    4. System Security

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    View all
    • (2024)Machine Learning and Transformers for Malware Analysis: Overview2024 New Trends in Signal Processing (NTSP)10.23919/NTSP61680.2024.10726311(1-7)Online publication date: 16-Oct-2024
    • (2024)Static Multi Feature-Based Malware Detection Using Multi SPP-net in Smart IoT EnvironmentsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335037919(2487-2500)Online publication date: 2024

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