Papers - OKAZAKI Naonobu
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並列性を考慮した通信システムの相互接続試験系列生成法 Reviewed
共著者：朴美娘，岡崎直宣，三上節子，高橋薫，白鳥則郎，野口正一
情報処理学会論文誌，34巻，6号，1336-1346頁 1993.6
Language：Japanese Publishing type：Research paper (scientific journal)
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プロセスの独立性を考慮した通信システムの相互接続試験系列生成法 Reviewed
共著者：朴美娘，岡崎直宣，太田正孝，高橋薫，白鳥則郎，野口正一
電子情報通信学会論文誌，J76-B-Ⅰ巻，3号，264-273頁 1993.3
Language：Japanese Publishing type：Research paper (scientific journal)
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LOTOS仕様からの効率的な試験系列の生成法 Reviewed
共著者：岡崎直宣，高橋薫，白鳥則郎，野口正一
電子情報通信学会論文誌，J74-B-Ⅰ巻，10号，733-747頁 1991.10
Language：Japanese Publishing type：Research paper (scientific journal)
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ユーザフレンドリープロトコル検証システム Reviewed
共著者：山本博章，相沢茂喜，岡崎直宣，高橋薫，白鳥則郎，野口正一
電子情報通信学会論文誌，J70-D巻，11号，2219-2227頁 1987.11
Language：Japanese Publishing type：Research paper (scientific journal)
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Investigation of an Authentication Method Using Vibration-Based Secret Cues and a Virtual Dial Interface Reviewed
Takumi Kido, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Nobuya Takahashi, Mirang Park, Naonobu Okazaki
Proc. The 31th International Symposium on Artificial Life and Robotics (AROB2026) 1248 - 1253 2026.1
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Malware Classification Using Transformer-Based Modeling of API Call Sequences Reviewed
Ryoga Sakai, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Nobuya Takahashi, Mirang Park, Naonobu Okazaki
Proc. The 31th International Symposium on Artificial Life and Robotics (AROB2026) 1254 - 1259 2026.1
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Usuzaki S., Iwasa K., Takahashi N., Aburada K., Yamaba H., Park M., Okazaki N.
Proceedings 9th International Conference on Information Technology Incit 2025 545 - 552 2025.11
Authorship：Last author Publishing type：Research paper (scientific journal) Publisher：Proceedings 9th International Conference on Information Technology Incit 2025
In this paper, we discuss a sketch-reconstructionbased In-band Network Telemetry (INT) method that can achieve practical flow count estimation accuracy during sketch collection. Measuring and aggregating per-flow information of network traffic helps to monitor the current network-wide status. Sketch-reconstruction-based INT methods were proposed to efficiently collect flow information measured by each device, which combine sketch techniques and INT. Sketch is a probabilistic algorithm that can estimate the count of entire flows with limited memory, and INT can carry measured data on the network device piggybacked in the business packet header. The combination of sketch and INT can reduce bandwidth consumption for collecting per-flow information, as the sketch can be regarded as a compact aggregation of the per-flow data. To minimize overhead, these methods split a sketch into smaller units called sketchlets and transmit them. The sent sketchlets are reconstructed into a sketch at the collection destination. However, existing methods have the disadvantage that they require a long time to collect sketchlets because they randomly select them, and the accuracy is low during the collection. In this study, we propose a new sketchlet algorithm, called HitFlow Sketchlet, that prioritizes sending buckets necessary for the sketch's query algorithm to function, which each method does not fully consider. We also propose the Flag data structure, aiming at the comprehensive sketchlet transmission. Evaluation experiments showed that HitFlow Sketchlet can output accurate estimates, especially in the earliest epochs, and that by combining it with Flag, comprehensiveness can be improved.
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Conjugate Gradient Based Multiplicative Update Rules for Nonnegative Matrix Factorization Reviewed
Takahashi N., Usuzaki S., Katayama T., Yokomichi M., Aburada K., Okazaki N.
Proceedings 9th International Conference on Information Technology Incit 2025 639 - 644 2025.11
Authorship：Last author Publishing type：Research paper (scientific journal) Publisher：Proceedings 9th International Conference on Information Technology Incit 2025
In this paper, we propose a general solution for nonnegative matrix factorization (NMF), a technique widely used in the field of machine learning. NMF is a type of matrix factorization used for dimensionality reduction. By approximating a nonnegative matrix as the product of two nonnegative matrices, it is possible to extract frequent patterns in the data matrix into the basis matrix together with their corresponding weights. Since many types of information, such as images, spectrograms of acoustic signals, and text data, are represented by nonnegative values, NMF is a useful algorithm applicable across a wide range of fields. Standard approaches to solving NMF include algorithms based on multiplicative update rules. However, because the applicable algorithm depends on the problem structure, extending NMF to new problem settings can be challenging. Another approach is the gradient method, which is an additive iterative procedure for solving a nonlinear optimization problem. The update direction of the state is given by the gradient of the objective function. The gradient method is versatile. It can be applied to any optimization problem with an available gradient, regardless of the problem structure. However, when applying it to the NMF problem, it is necessary to maintain the nonnegativity of the matrices throughout the iterative computation. As a result, several issues must be addressed, including vanishing gradients, proper tuning of the learning rate, and the need for gradient clipping. In this paper, we propose a new algorithm based on a multiplicative update rule incorporating the gradient. A multiplier function consisting of the hyperbolic tangent function and the linear functions is used. This function ensures that the pair of factor matrices remain nonnegative throughout the entire computation process. As with general gradient methods, the proposed algorithm has the advantage of being widely applicable to NMF problems formulated in a differentiable form. Furthermore, the convergence speed is improved by utilizing the nonlinear conjugate gradient method. Numerical experiments show that the decomposed matrices have a property specified by the penalty terms and confirming the effectiveness of the proposed method.
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Slow HTTP POST DDoS Attack Prevention Method that Monitors Payload Size and Number of Connections Reviewed
Yuya Ozaki, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Mirang Park, Naonobu Okazaki
Proc. The 28-th International Conference on Network-Based Information Systems (NBiS-2025) 22 - 31 2025.9
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Yamaba H., Komori N., Usuzaki S., Aburada K., Katayama T., Okazaki N.
Icce Taiwan 2025 12th IEEE International Conference on Consumer Electronics Taiwan Generative AI in Innovative Consumer Technology Proceedings 111 - 112 2025.7
Authorship：Last author Language：English Publishing type：Research paper (scientific journal) Publisher：Icce Taiwan 2025 12th IEEE International Conference on Consumer Electronics Taiwan Generative AI in Innovative Consumer Technology Proceedings
Mobile devices such as smartphones and tablets are now deeply integrated into daily life. To prevent shoulder surfing attacks, we propose a user authentication method for mobile devices based on surface electromyogram (s-EMG) signals. The method uses a “pass-gesture,” a sequence of hand gestures that can be changed like a password. Fingerspelling was adopted as the source of gesture candidates. Previous studies confirmed high accuracy in identifying gestures performed by the same subject. This paper focuses on evaluating subject specificity-specifically, confirming that a model trained on one user fails to recognize gestures performed by another. Experimental results show that the system does not generalize across users, indicating robustness against impersonation.
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Evacuation Support System for Tsunami Disasters that Considers Shelter Congestion
Nishi H., Nabeyama K., Usuzaki S., Aburada K., Yamaba H., Katayama T., Park M., Okazaki N.
Lecture Notes in Electrical Engineering 1322 LNEE 51 - 62 2025.2
Authorship：Last author Publishing type：Research paper (scientific journal) Publisher：Lecture Notes in Electrical Engineering
When a tsunami occurs, an evacuation support system capable of providing information on evacuation routes and shelter locations would enable evacuations to be conducted more swiftly and safely. In previous research, a proposal was made for an evacuation support system using low-power, long-distance communication. However, a challenge arose when shelter locations reached full capacity, requiring information to be shared, which in turn necessitated redirection of evacuees to alternative shelters. Therefore, in this study, a method for sharing shelter congestion information at an earlier stage was developed. The method of sharing based on the remaining capacity of shelters increased evacuation completion by up to 29 evacuees in an evacuee population of 1000.
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An Attempt to Solve Fill in the Missing Letters CAPTCHA Using Generative AI Reviewed
Yamaba H., Usuzaki S., Aburada K., Mukunoki M., Park M., Okazaki N.
Lecture Notes in Electrical Engineering 1322 LNEE 385 - 395 2025.2
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Electrical Engineering
This paper reports an attempt to solve the fill in the missing letters type CAPTCHA using generative AI. Many websites have adopted CAPTCHA to prevent bots and other automated programs from engaging in malicious activities such as posting comment spam. Text-based CAPTCHA is the most common and earliest form of CAPTCHA. However, as optical character recognition (OCR) technology has improved, the intensity of distortions applied to a CAPTCHA to keep it unrecognizable by OCR has also increased. This has reached a point where humans are having difficulty recognizing CAPTCHA text. The CAPTCHA proposed in the previous study asks users to spell a word by filling in some blanks. Since the number of letters displayed is minimal, it is challenging to identify the correct word. However, one or more images that can serve as hints to help users guess the answer word are also provided. It is expected that the ability to guess can distinguish between humans and computers. However, it is conceivable that generative AI, which has been advancing in recent years, can substitute for this ability. A series of experiments was carried out to evaluated the performance of the generative AI’s ability to solve the proposed CAPTCHA. First, we examined whether a well-known image recognition system could accurately identify the images used in the CAPTCHA problems. Next, we used the recognition results to have the generative AI solve the CAPTCHA problems and determined the accuracy rate. Additionally, we evaluated the performance of the generative AI itself by solving the problems using the correct identification of each image. From the experimental results, it was found that the CAPTCHA is relatively robust against attack techniques using generative AI.
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A study of Collaborative malware detection using item response theory Reviewed
Takuro Inada, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Tetsuro Katayama, Mirang Park, Naonobu Okazaki
Proc. The 30th International Symposium on Artificial Life and Robotics (AROB2025) 1070 - 1073 2025.1
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Introducing Generative AI into Unrealistic Image CAPTCHA for Effective Image Generation Reviewed
Kana Saiki, Hisaaki Yamaba, Shotaro Usuzaki, Kentaro Aburada, Masayuki Mukunoki, Mirang Park, Naonobu Okazaki
Proc. The 30th International Symposium on Artificial Life and Robotics (AROB2025) 1085 - 1090 2025.1
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Introduction of Feature Points in Images for Improvement of Finding Letters Type CAPTCHA Based on Neural Style Transfer Reviewed
Ramu Kiura, Hisaaki Yamaba, Shotaro Usuzaki, Kentaro Aburada, Masayuki Mukunoki, Mirang Park, Naonobu Okazaki
Proc. The 30th International Symposium on Artificial Life and Robotics (AROB2025) 1079 - 1084 2025.1
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Investigation of Detection Methods for Trojaned DNNs under Specific Conditions Reviewed
Shunya Izaki, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Tetsuro Katayama, Mirang Park, Naonobu Okazaki
Proc. The 30th International Symposium on Artificial Life and Robotics (AROB2025) 1074 - 1078 2025.1
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Park M., Chang Z., Usuzaki S., Aburada K., Okazaki N.
Proceedings - 2024 12th International Symposium on Computing and Networking Workshops, CANDARW 2024 293 - 299 2024.11
Authorship：Last author Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - 2024 12th International Symposium on Computing and Networking Workshops, CANDARW 2024
In recent years, with the number of users utilizing online services increasing, there is growing demand for more secure authentication methods. Existing authentication methods such as passwords, PINs, and pattern locks, while highly operational and convenient, have issues such as vulnerability to brute force attacks and voyeuristic attacks. As a solution to these problems, gaze authentication has been proposed, where a user draws pre-defined characters or symbols with their gaze, and the features obtained from the trajectory information are used for personal identification. Gaze-based authentication is resistant to attacks such as voyeuristic attacks, thermal attacks, and smudge attacks because it is difficult for a third party to observe the authentication process. However, it also has drawbacks, such as a low authentication success rate and a long authentication time. Therefore, this study proposes a personal authentication system that combines gaze-based image selection and gaze trajectory features to address the issues of authentication rate and authentication time in gaze-based authentication. Additionally, to verify the effectiveness of the proposed system, we collected eye movement trajectory data from users using a gaze detection device, performed data preprocessing and feature extraction, and then calculated the personal authentication rate using several machine learning algorithms. We confirmed that XGBoost had the highest authentication accuracy with an F-measure of 67.5%. Furthermore, in the evaluation of anomaly detection algorithms, Isolation Forest demonstrated superior performance compared to other algorithms.
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Proposal of Fill in the Missing Letters CAPTCHA Using Associations from Images Reviewed
Yamaba H., Mustaza M.N.F.B., Usuzaki S., Aburada K., Mukunoki M., Park M., Okazaki N.
Lecture Notes in Electrical Engineering 1114 LNEE 206 - 217 2024.1
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Electrical Engineering
This paper proposes a new fill in the missing letters type CAPTCHA using associations from images. Many web sites have adopted CAPTCHA to prevent bots and other automated programs from malicious activities such as posting comment spam. Text-based CAPTCHA is the most common and earliest CAPTCHA. But as optical character recognition (OCR) technology has improved, the intensity of distortions that must be applied to a CAPTCHA for it to remain unrecognizable by OCR has increased. This has reached a point where humans are having difficulty recognizing CAPTCHA text. The idea of the proposed CAPTCHA asks users to spell a word by filling some blanks. Since the number of shown letters are few, it is difficult to answer the correct word. But one or more images that can be used as hints to guess what is the answer word are also shown to the users. A series of experiments was carried out to evaluated the performance of the proposed CAPTCHA. First, a computer program was developed with various software languages for the usability evaluation. The system was used for the experiments to find the suitable parameters of the CAPTCHA such as numbers of letters that will be disclosed, position of disclosed letters. Next, security evaluation experiments were carried out using the system under the obtained parameters. The results of the experiments showed that the performance and limitation of the proposed CAPTCHA.
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Study of an Image-Based CAPTCHA that is Resistant to Attacks Using Image Recognition Systems Reviewed
Nishikawa S., Usuzaki S., Aburada K., Yamaba H., Katayama T., Park M., Okazaki N.
Lecture Notes in Electrical Engineering 1114 LNEE 175 - 184 2024.1
Authorship：Last author Publishing type：Research paper (scientific journal) Publisher：Lecture Notes in Electrical Engineering
In today’s digital age, image-based CAPTCHAs are increasingly vulnerable to attacks using annotation services, which tag images and classify images according to their contents, or reverse image search services. To prevent such attacks, an image-based CAPTCHA was proposed that takes advantage of the fact that humans can correctly recognize images containing many discontinuous points, while existing image recognition systems misrecognize them. However, this CAPTCHA proved susceptible to attacks using noise reduction filters. The objective of the present study is to create a CAPTCHA using images that are resistant to such filters. Images used in the new CAPTCHA were realized by increasing the proportion of lines forming discontinuous surfaces in images. Experimental results demonstrated a human recognition rate of 95.8%, with the image recognition systems successfully identifying only one image overall. Moreover, when a noise reduction filter was applied, the recognition rate was lower than those reported in previous studies.
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Proposal of a DDoS Attack Detection Method Using the Communication Interval Reviewed
Iwasa K., Usuzaki S., Aburada K., Yamaba H., Katayama T., Park M., Okazaki N.
Lecture Notes in Electrical Engineering 1114 LNEE 165 - 174 2024.1
Authorship：Last author Publishing type：Research paper (scientific journal) Publisher：Lecture Notes in Electrical Engineering
As the scale of Distributed Denial of Service (DDoS) attacks has been escalating in recent years, the need for real-time detection of attacks has increased. Existing intrusion detection systems (IDSs) perform detection with a fixed window size (assumed to be in hours). In previous research, attack detection was performed by preparing windows of multiple sizes, selecting the appropriate window based on the state of the data, and using features learned in advance for that window size. Although this method yielded a high DDoS attack detection rate of 98.30%, it exhibited a considerable false-positive rate of 7.37%. The proposed method measures the communication intervals of identical packets within the window, identified as attack-related in the previous survey, and classifies those packets with an average communication interval below a set threshold as attacks. The experiment resulted in a 50.2% decrease in the false-positive rate.