Hardware Trojans classification for gate-level netlists based on machine learning. - Kento Hasegawa; Masaru Oya; Masao Yanagisawa; Nozomu Togawa (IOLTS, 2016)

Designing hardware trojans and their detection based on a SVM-based approach. - Tomotaka Inoue; Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (ASICON, 2017)

Hardware Trojans classification for gate-level netlists using multi-layer neural networks. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (IOLTS, 2017)

Trojan-feature extraction at gate-level netlists and its application to hardware-Trojan detection using random forest classifier. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (ISCAS, 2017)

A Hardware-Trojan Classification Method Using Machine Learning at Gate-Level Netlists Based on Trojan Features. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017)

Trojan-Net Feature Extraction and Its Application to Hardware-Trojan Detection for Gate-Level Netlists Using Random Forest. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017)

Capacitance Measurement of Running Hardware Devices and its Application to Malicious Modification Detection. - Makoto Nishizawa; Kento Hasegawa; Nozomu Togawa (APCCAS, 2018)

Designing Subspecies of Hardware Trojans and Their Detection Using Neural Network Approach. - Tomotaka Inoue; Kento Hasegawa; Yuki Kobayashi; Masao Yanagisawa; Nozomu Togawa (ICCE-Berlin, 2018)

A hardware-Trojan classification method utilizing boundary net structures. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (ICCE, 2018)

Detecting the Existence of Malfunctions in Microcontrollers Utilizing Power Analysis. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (IOLTS, 2018)

A Trojan-invalidating Circuit Based on Signal Transitions and Its FPGA Implementation. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (ISCAS, 2018)

Hardware Trojan Detection Utilizing Machine Learning Approaches. - Kento Hasegawa; Youhua Shi; Nozomu Togawa (TrustCom/BigDataSE, 2018)

Empirical Evaluation and Optimization of Hardware-Trojan Classification for Gate-Level Netlists Based on Multi-Layer Neural Networks. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2018)

Adversarial Examples for Hardware-Trojan Detection at Gate-Level Netlists. - Kohei Nozawa; Kento Hasegawa; Seira Hidano; Shinsaku Kiyomoto; Kazuo Hashimoto; Nozomu Togawa (CyberICPS/SECPRE/SPOSE/ADIoT@ESORICS, 2019)

Implementation of a ROS-Based Autonomous Vehicle on an FPGA Board. - Kento Hasegawa; Kazunari Takasaki; Makoto Nishizawa; Ryota Ishikawa; Kazushi Kawamura; Nozomu Togawa (FPT, 2019)

Empirical Evaluation on Anomaly Behavior Detection for Low-Cost Micro-Controllers Utilizing Accurate Power Analysis. - Kento Hasegawa; Kiyoshi Chikamatsu; Nozomu Togawa (IOLTS, 2019)

FPGA-based Heterogeneous Solver for Three-Dimensional Routing. - Kento Hasegawa; Ryota Ishikawa; Makoto Nishizawa; Kazushi Kawamura; Masashi Tawada; Nozomu Togawa (ASP-DAC, 2020)

Evaluation on Hardware-Trojan Detection at Gate-Level IP Cores Utilizing Machine Learning Methods. - Tatsuki Kurihara; Kento Hasegawa; Nozomu Togawa (IOLTS, 2020)

An Anomalous Behavior Detection Method for IoT Devices by Extracting Application-Specific Power Behaviors. - Kazunari Takasaki; Kento Hasegawa; Ryoichi Kida; Nozomu Togawa (IOLTS, 2020)

A Capacitance Measurement Device for Running Hardware Devices and Its Evaluations. - Makoto Nishizawa; Kento Hasegawa; Nozomu Togawa (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2020)

Trojan-Net Classification for Gate-Level Hardware Design Utilizing Boundary Net Structures. - Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa (IEICE Trans. Inf. Syst., 2020)

Toward Learning Robust Detectors from Imbalanced Datasets Leveraging Weighted Adversarial Training. - Kento Hasegawa; Seira Hidano; Shinsaku Kiyomoto; Nozomu Togawa (CANS, 2021)

Data Augmentation for Machine Learning-Based Hardware Trojan Detection at Gate-Level Netlists. - Kento Hasegawa; Seira Hidano; Kohei Nozawa; Shinsaku Kiyomoto; Nozomu Togawa (IOLTS, 2021)

A Two-Stage Hardware Trojan Detection Method Considering the Trojan Probability of Neighbor Nets. - Kento Hasegawa; Tomotaka Inoue; Nozomu Togawa (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2021)

Generating Adversarial Examples for Hardware-Trojan Detection at Gate-Level Netlists. - Kohei Nozawa; Kento Hasegawa; Seira Hidano; Shinsaku Kiyomoto; Kazuo Hashimoto; Nozomu Togawa (J. Inf. Process., 2021)

Effective Hardware-Trojan Feature Extraction Against Adversarial Attacks at Gate-Level Netlists. - Kazuki Yamashita; Tomohiro Kato; Kento Hasegawa; Seira Hidano; Kazuhide Fukushima; Nozomu Togawa (IOLTS, 2022)

Automating XSS Vulnerability Testing Using Reinforcement Learning. - Kento Hasegawa; Seira Hidano; Kazuhide Fukushima (ICISSP, 2023)

Membership Inference Attacks against GNN-based Hardware Trojan Detection. - Kento Hasegawa; Kazuki Yamashita; Seira Hidano; Kazuhide Fukushima; Kazuo Hashimoto; Nozomu Togawa (TrustCom, 2023)

R-HTDetector: Robust Hardware-Trojan Detection Based on Adversarial Training. - Kento Hasegawa; Seira Hidano; Kohei Nozawa; Shinsaku Kiyomoto; Nozomu Togawa (IEEE Trans. Computers, 2023)

AutoRed: Automating Red Team Assessment via Strategic Thinking Using Reinforcement Learning. - Kento Hasegawa; Seira Hidano; Kazuhide Fukushima (CODASPY, 2024)

Vulnerability Information Sharing Platform for Securing Hardware Supply Chains. - Kento Hasegawa; Katsutoshi Hanahara; Hiroshi Sugisaki; Minoru Kozu; Kazuhide Fukushima; Yosuke Murakami; Shinsaku Kiyomoto (ICISSP, 2024)

PenGym: Pentesting Training Framework for Reinforcement Learning Agents. - Huynh Phuong Thanh Nguyen; Zhi Chen; Kento Hasegawa; Kazuhide Fukushima; Razvan Beuran (ICISSP, 2024)

RAG Certainty: Quantifying the Certainty of Context-Based Responses by LLMs. - Kento Hasegawa; Seira Hidano; Kazuhide Fukushima (ICMLA, 2024)

Prioritizing Vulnerability Assessment Items Using LLM Based on IoT Device Documentations. - Yuka Ikegami; Ryotaro Negishi; Kento Hasegawa; Seira Hidano; Kazuhide Fukushima; Kazuo Hashimoto; Nozomu Togawa (IOTSMS, 2024)

Initial Seeds Generation Using LLM for IoT Device Fuzzing. - Hibiki Nakanishi; Kota Hisafuru; Kento Hasegawa; Seira Hidano; Kazuhide Fukushima; Kazuo Hashimoto; Nozomu Togawa (IOTSMS, 2024)

EdgePruner: Poisoned Edge Pruning in Graph Contrastive Learning. - Hiroya Kato; Kento Hasegawa; Seira Hidano; Kazuhide Fukushima (SaTML, 2024)

Autonomous Hardware-Trojan Generation Method Using Reinforcement Learning for Random Forest-Based Hardware-Trojan Detection. - Yuka Ikegami; Kento Hasegawa; Seira Hidano; Kazuhide Fukushima; Nozomu Togawa (ICCE, 2025)

Performance Comparison of the LLM Models on LLM-Based Seed Generation Method for IoT Device Fuzzing. - Hibiki Nakanishi; Kento Hasegawa; Seira Hidano; Kazuhide Fukushima; Kazuo Hashimoto; Nozomu Togawa (ICCE, 2025)

Automating the Assessment of Japanese Cyber-Security Technical Assessment Requirements Using Large Language Models. - Kento Hasegawa; Yuka Ikegami; Seira Hidano; Kazuhide Fukushima; Kazuo Hashimoto; Nozomu Togawa (IoTBDS, 2025)

Automated Test Input Generation Based on Web User Interfaces via Large Language Models. - Kento Hasegawa; Hibiki Nakanishi; Seira Hidano; Kazuhide Fukushima; Kazuo Hashimoto; Nozomu Togawa (IoTBDS, 2025)

PenGym: Realistic training environment for reinforcement learning pentesting agents. - Huynh Phuong Thanh Nguyen; Kento Hasegawa; Kazuhide Fukushima; Razvan Beuran (Comput. Secur., 2025)

Annealing Machine-assisted Learning of Graph Neural Network for Combinatorial Optimization. - Pablo Loyola; Kento Hasegawa; Andres Hoyos-Idobro; Kazuo Ono; Toyotaro Suzumura; Yu Hirate; Masanao Yamaoka (CoRR, 2025)

Node-Wise Hardware Trojan Detection Based on Graph Learning. - Kento Hasegawa; Kazuki Yamashita; Seira Hidano; Kazuhide Fukushima; Kazuo Hashimoto; Nozomu Togawa (IEEE Trans. Computers, 2025)