Pilot-scale exhaust gas treatment for a glass manufacturing system using a plasma combined semi-dry chemical process. - Hashira Yamamoto; Yuri Yamamoto; Tomoyuki Kuroki; Kota Yoshida; Hidekatsu Fujishima; Masaaki Okubo (IAS, 2015)

Neural Joking Machine : Humorous image captioning. - Kota Yoshida; Munetaka Minoguchi; Kenichiro Wani; Akio Nakamura; Hirokatsu Kataoka (CoRR, 2018)

Model-Extraction Attack Against FPGA-DNN Accelerator Utilizing Correlation Electromagnetic Analysis. - Kota Yoshida; Takaya Kubota; Mitsuru Shiozaki; Takeshi Fujino (FCCM, 2019)

Disabling Backdoor and Identifying Poison Data by using Knowledge Distillation in Backdoor Attacks on Deep Neural Networks. - Kota Yoshida; Takeshi Fujino (AISec@CCS, 2020)

Joking AI via Visual Cues. - Ryota Suzuki 006; Kota Yoshida; Munetaka Minoguchi; Kazuki Tsubura; Takumu Ikeya; Akio Nakamura; Hirokatsu Kataoka (HCI (37), 2020)

Model Reverse-Engineering Attack using Correlation Power Analysis against Systolic Array Based Neural Network Accelerator. - Kota Yoshida; Takaya Kubota; Shunsuke Okura; Mitsuru Shiozaki; Takeshi Fujino (ISCAS, 2020)

Model Evasion Attacks Against Partially Encrypted Deep Neural Networks in Isolated Execution Environment. - Kota Yoshida; Takeshi Fujino (ACNS Workshops, 2021)

Deep Learning Side-Channel Attacks Against Lightweight SCA Countermeasure RSM-AES. - Yuta Fukuda; Kota Yoshida; Hisashi Hashimoto; Takeshi Fujino (AsianHOST, 2021)

Towards Trusted IoT Sensing Systems: Implementing PUF as Secure Key Generator for Root of Trust and Message Authentication Code. - Kota Yoshida; Kuniyasu Suzaki; Takeshi Fujino (HASP@MICRO, 2021)

Model Reverse-Engineering Attack against Systolic-Array-Based DNN Accelerator Using Correlation Power Analysis. - Kota Yoshida; Mitsuru Shiozaki; Shunsuke Okura; Takaya Kubota; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2021)

Deep learning side-channel attack against hardware implementations of AES. - Takaya Kubota; Kota Yoshida; Mitsuru Shiozaki; Takeshi Fujino (Microprocess. Microsystems, 2021)

Fundamental Study of Adversarial Examples Created by Fault Injection Attack on Image Sensor Interface. - Tatsuya Oyama; Kota Yoshida; Shunsuke Okura; Takeshi Fujino (AsianHOST, 2022)

Deep Learning Side-Channel Attacks against Hardware-Implemented Lightweight Cipher Midori 64. - Madoka Sakou; Kunihiro Kuroda; Yuta Fukuda; Kota Yoshida; Takeshi Fujino (ATAIT, 2022)

Deep Learning-Based Side-Channel Attacks against Software-Implemented RSA using Binary Exponentiation with Dummy Multiplication. - Seiya Shimada; Kunihiro Kuroda; Yuta Fukuda; Kota Yoshida; Takeshi Fujino (ATAIT, 2022)

Fault Injection Attacks Utilizing Waveform Pattern Matching against Neural Networks Processing on Microcontroller. - Yuta Fukuda; Kota Yoshida; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2022)

Experimental Study of Fault Injection Attack on Image Sensor Interface for Triggering Backdoored DNN Models. - Tatsuya Oyama; Shunsuke Okura; Kota Yoshida; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2022)

Adversarial Scan Attack against Scan Matching Algorithm for Pose Estimation in LiDAR-Based SLAM. - Kota Yoshida; Masaya Hojo; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2022)

Evaluation of Membership Inference Attack Against Federated Learning With Differential Privacy on Edge Devices. - Rei Ueda; Tsunato Nakai; Kota Yoshida; Takeshi Fujino (GCCE, 2023)

Multispectral Pedestrian Detection with Visible and Far-infrared Images Under Drifting Ambient Light and Temperature. - Masato Okuda; Kota Yoshida; Takeshi Fujino (SENSORS, 2023)

Evaluation of Model Quantization Method on Vitis-AI for Mitigating Adversarial Examples. - Yuta Fukuda; Kota Yoshida; Takeshi Fujino (IEEE Access, 2023)

Backdoor Attack on Deep Neural Networks Triggered by Fault Injection Attack on Image Sensor Interface. - Tatsuya Oyama; Shunsuke Okura; Kota Yoshida; Takeshi Fujino (Sensors, 2023)

Profiling Deep Learning Side-Channel Attacks Using Multi-Label against AES Circuits with RSM Countermeasure. - Yuta Fukuda; Kota Yoshida; Hisashi Hashimoto; Kunihiro Kuroda; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2023)

Practical aspects on non-profiled deep-learning side-channel attacks against AES software implementation with two types of masking countermeasures including RSM. - Kunihiro Kuroda; Yuta Fukuda; Kota Yoshida; Takeshi Fujino (J. Cryptogr. Eng., 2023)

Incorporating Cluster Analysis of Feature Vectors for Non-profiled Deep-learning-Based Side-Channel Attacks. - Yuta Fukuda; Kota Yoshida; Takeshi Fujino (ACNS Workshops (1), 2024)

Model Extraction Attack Without Natural Images. - Kota Yoshida; Takeshi Fujino (ACNS Workshops (2), 2024)

Evaluation of Accuracy and Security on Deep Learning Model by Utilizing K-Anonymization With Attribute Selection for Reducing Computational Cost. - Rei Ueda; Kota Yoshida; Takeshi Fujino (GCCE, 2024)

Lightweight Object Detection Model for a CMOS Image Sensor with Binary Feature Extraction. - Keiichiro Kuroda; Yudai Morikaku; Yu Osuka; Ryoya Iegaki; Kota Yoshida; Shunsuke Okura (IEEE SENSORS, 2024)

Defense Method Against Adversarial Example Attacks using Thermal Noise of a CMOS Image Sensor. - Yuki Rogi; Kota Yoshida; Tatsuya Oyama; Takeshi Fujino; Shunsuke Okura (IEEE SENSORS, 2024)

Can KANs Do It? Toward Interpretable Deep Learning-based Side-channel Analysis. - Kota Yoshida; Sengim Karayalcin; Stjepan Picek (IACR Cryptol. ePrint Arch., 2024)

Adversarial Examples Created by Fault Injection Attack on Image Sensor Interface. - Tatsuya Oyama; Kota Yoshida; Shunsuke Okura; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2024)

SEDMA: Self-Distillation with Model Aggregation for Membership Privacy. - Tsunato Nakai; Ye Wang; Kota Yoshida; Takeshi Fujino (Proc. Priv. Enhancing Technol., 2024)

Data Poisoning Attack against Neural Network-Based On-Device Learning Anomaly Detector by Physical Attacks on Sensors. - Takahito Ino; Kota Yoshida; Hiroki Matsutani; Takeshi Fujino (Sensors, 2024)

Operation Shuffling with Multiple S-Boxes Against Power Analysis Attacks. - Shota Kajiya; Hiroki Nishikawa; Kota Yoshida; Ittetsu Taniguchi; Takao Onoye (ICEIC, 2025)

Multi-Bit DDLA: Non-Profiled Deep Learning Side-Channel Attacks Using Multi-Bit Label against Hardware-Implemented AES. - Yuta Fukuda; Kota Yoshida; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2025)

CA-SCA: Non-Profiled Deep Learning-Based Side-Channel Attacks by Using Cluster Analysis. - Yuta Fukuda; Kota Yoshida; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2025)

Mitigation of Membership Inference Attack by Knowledge Distillation on Federated Learning. - Rei Ueda; Tsunato Nakai; Kota Yoshida; Takeshi Fujino (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2025)