Faculty Profiles - YAMAUCHI Toshihiro

MISC - YAMAUCHI Toshihiro

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Performance Evaluation Focusing on Control Transitions between VMM and OS on VM

2022 ( 1 ) 119 - 120 2022.1

Analysis by Clustering Focusing on Telnet Connection Log Commands to IoT Devices

2021 692 - 696 2021.10

カーネルにおけるMemory Protection Keyを用いた権限情報保護機構の提案

葛野弘樹, 山内利宏

コンピュータセキュリティシンポジウム 2021 (CSS2021) 論文集 2021 647 - 654 2021.10

Tenderにおけるプロセス間通信データ域を利用したコンテナボックス通信の性能分析

菰田志城, 山内利宏, 谷口秀夫

2021年度電気・情報関連学会中国支部第72回連合大会 2021.10

N/A

2021 697 - 704 2021.10

Investigation of Threats in the Secure World of OP-TEE

2021 661 - 667 2021.10

Evaluation of Function for Tracing Diffusion of Classified Information to Support VMs Running on Multiple Cores on KVM

2021 403 - 410 2021.10

Large-scale Survey on Secure Development of IoT Devices by Software Analysis and Vendor Interview Invited

Shugo Shiraishi, Akifumi Fukumoto, Ryota Yoshimoto, Eitaro Shioji, Mitsuaki Akiyama, Toshihiro Yamauchi

The 16th International Workshop on Security (IWSEC 2021), Invited session 2021.9

Selective Usage Method of Resource Pooling Function on Tender

林里咲, 山内利宏, 谷口秀夫

情報科学技術フォーラム講演論文集 4 171 - 172 2021.8

Malware Classification by Deep Learning Using the Characteristics of Hash Functions

馬場隆寛, 馬場謙介, 山内利宏

情報科学技術フォーラム講演論文集 4 43 - 46 2021.8

Authorship：Last author,　Corresponding author Language：Japanese Publisher：Springer

As the Internet develops, the number of Internet of Things (IoT) devices increases. Simultaneously, the risk of IoT devices being infected with malware also increases. Thus, malware detection has become an important issue. Dynamic analysis logs are effective at detecting malware, but it takes time to collect a large amount of data because the malware must be executed at least once before the logs can be collected. Moreover, dynamic analysis logs are affected by external factors such as the execution environment. A malware detection method that uses a static property analysis log could solve these problems. In this study, deep learning (DL) was used as a machine learning method because DL is effective for large-scale data and can automatically extract features. Research has been conducted on malware detection using static properties of portable executable (PE) files, establishing that such detection is possible. However, research on malware detection using hash functions such as Fuzzy hash and peHash is lacking. Therefore, we investigated the characteristics of hash values in malware classification. Moreover, when the surface analysis log is viewed in chronological order, that the data are considered have concept drift characteristics. Therefore, we compared malware detection performance using data with the concept drift property. We found that the hash function could be used to prevent performance degradation even with concept drift data. In an experiment combining PE surface information and hash values, concept drift showed the highest performance for certain data.

DOI： 10.1007/978-3-030-99587-4_40

Scopus

J-GLOBAL

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Other Link： https://dblp.uni-trier.de/db/conf/aina/aina2022-2.html#BabaBY22

Evaluation of Memory Access Performance in NUMA Architecture

島谷隼生, 山内利宏, 谷口秀夫, 佐藤将也

情報科学技術フォーラム講演論文集 4 169 - 170 2021.8