Published Papers - KUZE Naomi

False injection攻撃耐性を考慮したネットワーク化ドローン制御システムにおけるフォールバック制御

久世尚美, 藤川雄斗, 潮俊光

電子情報通信学会 技術研究報告 (NLP2020-30)   120 ( 165 ) 39 - 44   2020.09

UAV操作支援システムと軌道生成器の提案

早川裕基, 坂口聡範, 潮俊光, 久世尚美, 安積卓也

2019電子情報通信学会基礎・境界ソサイエティ／NOLTAソサイエティ大会     78   2020.06

WiP Abstract: Detection of False Injection Attacks Based on LTL for Fallback Control

Naomi Kuze, Ami Sakakibara, Toshimitsu Ushio

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) ( IEEE )    194 - 195   2020.04  [Refereed]

DOI

Network Control Mechanism Using Uncertain Information inspired by Collective Decision Making

志垣沙衣子, 久世尚美, 小南大智, 加嶋健司, 村田正幸

電子情報通信学会技術研究報告   119 ( 461 ) 297 - 302   2020.03

需要予測を考慮した非同期タクシー経路支援システム

高島相太, 久世尚美, 潮俊光

2020年電子情報通信学会総合大会講演論文集     271   2020.03

Anti-jamming mobile control using QoS-based reinforcement learning

Naomi Kuze, Taishi Nakashima, Toshimitsu Ushio

IEICE Communications Express ( Institute of Electronics, Information and Communications Engineers ({IEICE}) )  8 ( 12 ) 501 - 506   2019.12  [Refereed]

DOI

An application of reinforcement learning in anti-jamming mechanism of mobile robot path planning with co-safe temporal logic specifications

宓建, 久世尚美, 潮俊光

電子情報通信学会技術報告書（複雑コミュニケーションサイエンス研究会）   119 ( 289 ) 23 - 28   2019.09

WiP abstract: hierarchical taxi dispatch system with local coordination among micro-level components

Sota Takashima, Naomi Kuze, Toshimitsu Ushio

Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS 2019)     306 - 307   2019.04  [Refereed]

Anti-jamming mobile control using QoS-based reinforcement learning

Taishi Nakashima, Naomi Kuze, Toshimitsu Ushio

IEICE General Conference 2019 ( Institute of Electronics, Information and Communications Engineers (IEICE) )  8 ( 12 ) 501 - 506   2019.03

DOI

Self-Organizing Reliability Decision of Controller inspired by Collective Decision Making

Saeko Shigaki, Naomi Kuze, Daichi Kominami, Kenji Kashima, Masayuki Murata

Technical Report of IEICE (IN2018-108)   118 ( 466 ) 145 - 150   2019.03

Self-organizing control mechanism based on collective decision-making for information uncertainty

Naomi Kuze, Daichi Kominami, Kenji Kashima, Tomoaki Hashimoto, Masayuki Murata

ACM Transactions on Autonomous and Adaptive Systems   13 ( 1 ) 7:1 - 7:21   2018.04  [Refereed]

　View Summary

© 2018 Duke University.All right reserved. Because of the rapid growth in the scale and complexity of information networks, self-organizing systems are increasingly being used to realize novel network control systems that are highly scalable, adaptable, and robust. However, the uncertainty of information (with regard to incompleteness, vagueness, and dynamics) in self-organizing systems makes it difficult for them to work appropriately in accordance with the network state. In this study, we apply a model of the collective decision-making of animal groups to enable self-organizing control mechanisms to adapt to information uncertainty. Specifically, we apply a mathematical model of collective decision-making that is known as the effective leadership model (ELM). In the ELM, informed individuals (those who are experienced or well-informed) take the role of leading the others. In contrast, uninformed individuals (those who perceive only local information) follow neighboring individuals. As a result of the collective behavior of informed/uninformed individuals, the animal group achieves consensus. We consider a self-organizing control mechanism using potential-based routing with an optimal control, and propose a mechanism for determining a data-packet forwarding scheme based on the ELM. Through evaluation by simulation, we show that, in a situation in which the perceived information is incomplete and dynamic, nodes can forward data packets in accordance with the network state by applying the ELM.

DOI

Channel Selection Mechanism with Uncertain Information Inspired by Collective Decision Making

Naomi Kuze, Daichi Kominami, Kenji Kashima, Tomoaki Hashimoto, Masayuki Murata

Technical Report of IEICE (IN2017-118) ( 電子情報通信学会 )  117 ( 460 ) 171 - 176   2018.03

Self-Organized Network Control Using Uncertain Information Inspired by Collective Decision Making

Saeko Shigaki, Naomi Kuze, Daichi Kominami, Kenji Kashima, Masayuki Murata

Technical Report of IEICE (IN2017-118) ( 電子情報通信学会 )  117 ( 460 ) 225 - 230   2018.03

Self-Organizing Control Mechanisms According to Information Confidence for Improving Performance

Naomi Kuze, Daichi Kominami, Kenji Kashima, Tomoaki Hashimoto, Masayuki Murata

2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings     1 - 6   2018  [Refereed]

　View Summary

© 2018 IEEE. Self-organizing systems are focused on to realize novel network control systems that are highly scalable, adaptable, and robust. However, the uncertainty of information makes it difficult for self-organizing systems to work appropriately, thereby degrading their performance. It is necessary to improve the performance of self-organizing systems while retaining their advantages. Therefore, we apply the concept of flexible leadership of the collective decision-making in human groups to self-organizing control mechanisms. By incorporating this concept, agents dynamically and flexibly change their role (leader or follower) according to the confidence of their own information, which increases decision accuracy under information uncertainty. We propose a channel-selection mechanism based on collective decision-making in accordance with information confidence. Simulation experiments show that the proposed mechanism improves the performance of network systems while retaining the high adaptability.

DOI

Hierarchical Optimal Control Method for Controlling Large-Scale Self-Organizing Networks

Naomi Kuze

ACM Transactions on Autonomous and Adaptive Systems   12 ( 4 ) 22:1 - 22:23   2017.10  [Refereed]

DOI

Self-organizing wireless sensor networks based on biological collective decision making for treating information uncertainty

Saeko Shigaki, Naomi Kuze, Daichi Kominami, Kenji Kashima, Masayuki Murata

Proceedings of The Tenth IEEE International Workshop on Selected Topics in Wireless and Mobile Computing (STWiMob 2017)     167 - 174   2017.10  [Refereed]

Self-organized multi-agent control method inspired by collective decision making

Saeko Shigaki, Naomi Kuze, Daichi Kominami, Kenji Kashima, Masayuki Murata

Technical Report of IEICE (IN2016-145) ( 電子情報通信学会 )  116 ( 485 ) 287 - 292   2017.03

Controlling Large-Scale Self-Organized Networks with Lightweight Cost for Fast Adaptation to Changing Environments

Naomi Kuze

ACM Transactions on Autonomous and Adaptive Systems   11 ( 2 ) 9:1 - 9:25   2016.06  [Refereed]

DOI

Detection of vulnerability scanning using features of collective accesses collected from several honeypots

Naomi Kuze, Shu Ishikura, Takeshi Yagi, Daiki Chiba, Masayuki Murata

Technical Report of IEICE (ICSS2015-55)   115 ( 488 ) 47 - 52   2016.03

Managed self-organizing control method inspired by adaptive biological behavior

Naomi Kuze

Graduate School of Information Science and Technology, Osaka University     2016.01