Kento Hasegawa

Orcid: 0000-0002-6517-1703

According to our database1, Kento Hasegawa authored at least 53 papers between 2016 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Initial Seeds Generation Based on Communication Logs Using LLM for IoT Device Fuzzing.
IEICE Trans. Inf. Syst., 2026

AISTIP: AI Security Threat Intelligence Platform to Gather Knowledge from Technical Documents.
Proceedings of the 18th International Conference on Agents and Artificial Intelligence, 2026

2025
AI Security Map: Holistic Organization of AI Security Technologies and Impacts on Stakeholders.
CoRR, August, 2025

Node-Wise Hardware Trojan Detection Based on Graph Learning.
IEEE Trans. Computers, March, 2025

Annealing Machine-assisted Learning of Graph Neural Network for Combinatorial Optimization.
CoRR, January, 2025

Prioritizing Vulnerability Assessment Items for IoT Devices Based on Suitability Evaluation Using LLMs.
IEICE Trans. Inf. Syst., 2025

PenGym: Realistic training environment for reinforcement learning pentesting agents.
Comput. Secur., 2025

Evaluation of Adversarial Input Attacks in Retrieval-Augmented Generation Using Large Language Models.
Proceedings of the Advances in Information and Computer Security, 2025

LLM-Based IoT Fuzzing with Format Consistency and Vulnerability-Aware Test Case Generation.
Proceedings of the 12th International Conference on Internet of Things: Systems, 2025

Automated Security Compliance Evaluation Using Hierarchical RAG for IoT Devices with Large-Scale Documentation.
Proceedings of the 12th International Conference on Internet of Things: Systems, 2025

Automated Test Input Generation Based on Web User Interfaces via Large Language Models.
Proceedings of the 10th International Conference on Internet of Things, 2025

Automating the Assessment of Japanese Cyber-Security Technical Assessment Requirements Using Large Language Models.
Proceedings of the 10th International Conference on Internet of Things, 2025

Performance Comparison of the LLM Models on LLM-Based Seed Generation Method for IoT Device Fuzzing.
Proceedings of the IEEE International Conference on Consumer Electronics, 2025

Autonomous Hardware-Trojan Generation Method Using Reinforcement Learning for Random Forest-Based Hardware-Trojan Detection.
Proceedings of the IEEE International Conference on Consumer Electronics, 2025

LLM-based Fuzzing Method Using UI-based Input Value Generation for IoT Devices.
Proceedings of the 14th IEEE International Conference on Consumer Electronics - Berlin, 2025

Security Conformance Scoring for IoT Devices Through Documentation Analysis Using Large Language Models.
Proceedings of the 14th IEEE International Conference on Consumer Electronics - Berlin, 2025

LLM-Guided Initial Seed Selection for Black-Box IoT Fuzzing to Enhance Vulnerability Detection.
Proceedings of the 2025 Computing, 2025

2024
EdgePruner: Poisoned Edge Pruning in Graph Contrastive Learning.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

Initial Seeds Generation Using LLM for IoT Device Fuzzing.
Proceedings of the 11th International Conference on Internet of Things: Systems, 2024

Prioritizing Vulnerability Assessment Items Using LLM Based on IoT Device Documentations.
Proceedings of the 11th International Conference on Internet of Things: Systems, 2024

RAG Certainty: Quantifying the Certainty of Context-Based Responses by LLMs.
Proceedings of the International Conference on Machine Learning and Applications, 2024

PenGym: Pentesting Training Framework for Reinforcement Learning Agents.
Proceedings of the 10th International Conference on Information Systems Security and Privacy, 2024

Vulnerability Information Sharing Platform for Securing Hardware Supply Chains.
Proceedings of the 10th International Conference on Information Systems Security and Privacy, 2024

AutoRed: Automating Red Team Assessment via Strategic Thinking Using Reinforcement Learning.
Proceedings of the Fourteenth ACM Conference on Data and Application Security and Privacy, 2024

2023
R-HTDetector: Robust Hardware-Trojan Detection Based on Adversarial Training.
IEEE Trans. Computers, February, 2023

Membership Inference Attacks against GNN-based Hardware Trojan Detection.
Proceedings of the 22nd IEEE International Conference on Trust, 2023

Automating XSS Vulnerability Testing Using Reinforcement Learning.
Proceedings of the 9th International Conference on Information Systems Security and Privacy, 2023

2022
Effective Hardware-Trojan Feature Extraction Against Adversarial Attacks at Gate-Level Netlists.
Proceedings of the 28th IEEE International Symposium on On-Line Testing and Robust System Design, 2022

2021
Generating Adversarial Examples for Hardware-Trojan Detection at Gate-Level Netlists.
J. Inf. Process., 2021

A Two-Stage Hardware Trojan Detection Method Considering the Trojan Probability of Neighbor Nets.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2021

Data Augmentation for Machine Learning-Based Hardware Trojan Detection at Gate-Level Netlists.
Proceedings of the 27th IEEE International Symposium on On-Line Testing and Robust System Design, 2021

Toward Learning Robust Detectors from Imbalanced Datasets Leveraging Weighted Adversarial Training.
Proceedings of the Cryptology and Network Security - 20th International Conference, 2021

2020
Trojan-Net Classification for Gate-Level Hardware Design Utilizing Boundary Net Structures.
IEICE Trans. Inf. Syst., 2020

A Capacitance Measurement Device for Running Hardware Devices and Its Evaluations.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2020

An Anomalous Behavior Detection Method for IoT Devices by Extracting Application-Specific Power Behaviors.
Proceedings of the 26th IEEE International Symposium on On-Line Testing and Robust System Design, 2020

Evaluation on Hardware-Trojan Detection at Gate-Level IP Cores Utilizing Machine Learning Methods.
Proceedings of the 26th IEEE International Symposium on On-Line Testing and Robust System Design, 2020

FPGA-based Heterogeneous Solver for Three-Dimensional Routing.
Proceedings of the 25th Asia and South Pacific Design Automation Conference, 2020

2019
Empirical Evaluation on Anomaly Behavior Detection for Low-Cost Micro-Controllers Utilizing Accurate Power Analysis.
Proceedings of the 25th IEEE International Symposium on On-Line Testing and Robust System Design, 2019

Implementation of a ROS-Based Autonomous Vehicle on an FPGA Board.
Proceedings of the International Conference on Field-Programmable Technology, 2019

Adversarial Examples for Hardware-Trojan Detection at Gate-Level Netlists.
Proceedings of the Computer Security - ESORICS 2019 International Workshops, 2019

2018
Empirical Evaluation and Optimization of Hardware-Trojan Classification for Gate-Level Netlists Based on Multi-Layer Neural Networks.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2018

Hardware Trojan Detection Utilizing Machine Learning Approaches.
Proceedings of the 17th IEEE International Conference On Trust, 2018

A Trojan-invalidating Circuit Based on Signal Transitions and Its FPGA Implementation.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2018

Detecting the Existence of Malfunctions in Microcontrollers Utilizing Power Analysis.
Proceedings of the 24th IEEE International Symposium on On-Line Testing And Robust System Design, 2018

A hardware-Trojan classification method utilizing boundary net structures.
Proceedings of the IEEE International Conference on Consumer Electronics, 2018

Designing Subspecies of Hardware Trojans and Their Detection Using Neural Network Approach.
Proceedings of the 8th IEEE International Conference on Consumer Electronics - Berlin, 2018

Capacitance Measurement of Running Hardware Devices and its Application to Malicious Modification Detection.
Proceedings of the 2018 IEEE Asia Pacific Conference on Circuits and Systems, 2018

2017
Trojan-Net Feature Extraction and Its Application to Hardware-Trojan Detection for Gate-Level Netlists Using Random Forest.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017

A Hardware-Trojan Classification Method Using Machine Learning at Gate-Level Netlists Based on Trojan Features.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017

Trojan-feature extraction at gate-level netlists and its application to hardware-Trojan detection using random forest classifier.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

Hardware Trojans classification for gate-level netlists using multi-layer neural networks.
Proceedings of the 23rd IEEE International Symposium on On-Line Testing and Robust System Design, 2017

Designing hardware trojans and their detection based on a SVM-based approach.
Proceedings of the 12th IEEE International Conference on ASIC, 2017

2016
Hardware Trojans classification for gate-level netlists based on machine learning.
Proceedings of the 22nd IEEE International Symposium on On-Line Testing and Robust System Design, 2016


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