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2022 Fiscal Year Final Research Report

IoT processor detecting cyber-attacks using operation information inside core as features

Research Project

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Project/Area Number 20K11818
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 60070:Information security-related
Research InstitutionKogakuin University

Principal Investigator

Kobayashi Ryotaro  工学院大学, 情報学部(情報工学部), 教授 (40324454)

Co-Investigator(Kenkyū-buntansha) 嶋田 創  名古屋大学, 情報基盤センター, 准教授 (60377851)
Project Period (FY) 2020-04-01 – 2023-03-31
Keywordsサイバーセキュリティ
Outline of Final Research Achievements

Research on countermeasures against unauthorized access using IoT processors has made it possible to achieve high-precision detection by using machine learning algorithms. In addition, research using decoy files has shown that it is possible to detect ransomware with low load and high accuracy. These achievements have greatly contributed to strengthening malware countermeasures for IoT.

Furthermore, for malware countermeasures for IoT, a hardware-implemented discriminator was placed adjacent to the core on the LSI. During program execution, it judges whether each instruction is malicious or benign, and makes a final judgment. In this research, a proposal was made to reduce the required space and power consumption of the necessary discriminator for IoT devices.

Free Research Field

サイバーセキュリティ

Academic Significance and Societal Importance of the Research Achievements

マルウェア対策の研究では、機械学習を使うことで高精度な検知が可能になり、デコイファイルによって低負荷かつ高精度なランサムウェア検知が可能となりました。これらの成果は、IoT機器への攻撃の脅威が高まる中で、プロセッサによる攻撃検知の重要性を示すものであり、IoT機器のセキュリティ強化に貢献すると言えます。更にLSI上のコアに隣接したハードウェア判別器は、IoTセキュリティにおける重要な一歩となり、今後も注目されることでしょう。IoTセキュリティの課題は多岐にわたり、今後も重要性が高まっていくと予想されます。

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Published: 2024-01-30  

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