We conduct information security research
with a focus on access control.

Hashimoto Laboratory has just started in October 2015 at the Graduate School of Information Security. Our main research subjects are Access Control, Intrusion Detection and Prevention, and Operating System Security. Our aim is to contribute to the development of a more secure, pleasant, and prosperous information society through our research on theoretical and practical aspects of Access Control; we believe Access Control is one of the most important technical elements for the protection of information and communications.

Keywords related to our research involve: Information Flow Control, OSINT/Intelligence Mining, Cyber Attack and Hacking Techniques, Digital Forensics, Honeypot, Knowledge Processing, Policy Description Language, Logic Programming, SELinux, and TOMOYO Linux.

Additionally, we actively promote collaboration between industry, government and academia. Collaborative researches with the Japan Cybercrime Control Center (JC3), Ines Research Institute Inc., Deloitte Tohmatsu Risk Service Co., Ltd., etc. are ongoing.

Alumni & Master's Theses

  • 2019
    Masato Inoue: A research of HTTP request and an identification method of fake User-Agent values
    Masashi Kadoguchi: Exploring the Dark Web for Cyber Threat Intelligence using Machine Learning
    Atsushi kanda: Identifying Encrypted Communication Using Randomness
    Hanae Kobayashi: Development of an expert system for automatic classification of illegal and harmful information on the dark web
  • 2018
    Hiroki Inoue: Access Control Policy Protection Empowered by the TrustZone Technology
    Yuka Ogura: A Visualization Method for Understanding the Effect of Intrusion Detection using the Processing 3
    Naoki Kurihara: Spoofed Website Detection using Machine Learning
    Masaki Sugiu: Verification of Deception Technique using Decoy System
    Shuhei Segawa: A Initial Study on a Vulnerability Testing Tool for Short-range Wireless Communication
    Yasuhiro Mitsuishi: Current Status and Issues of Maritime Cyber Security
  • 2017
    Makoto Ashitsu: Research on an Evaluation Method for Memory Forensics Tools
    Takuya Koike: A Linking Method of Malignant Activity Based on Process and File Access Information
    Tadashi Shimomura: A Malware Detection Method by Machine Learning Focused on Malignant Activity
    Moriyo Tamura: A Malware Detection Method by Function Similarity in PE Files using Convolution Neural Network
    Shota Hayashi: Exploring Darkweb for Cyber Threat Intelligence using Machine Learning
    Akemi Mizuta: A Study of Utilization and Management of Confidential Information in Connected Industries
  • 2016
    Nobuki Suetsugu: A Study of Malware Behavior Based on Function Classification using Frequency of API Calls
    Ikuo Tanaka: Evaluation of Memory Image Acquisition / Analysis Function in Forensic Tools
  • 2015
    Yudai Tomaru: A Linkage Analysis among Process Behavior for Intrusion Prevention
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