Published Papers - KUZE Naomi

Detection of Vulnerability Scanning Using Features of Collective Accesses Based on Information Collected from Multiple Honeypots

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

NOMS 2016 - 2016 IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM ( IEEE )    1067 - 1072   2016  [Refereed]

　View Summary

Attacks against websites are increasing rapidly with the expansion of web services. An increasing number of diversified web services make it difficult to prevent such attacks due to many known vulnerabilities in websites. To overcome this problem, it is necessary to collect the most recent attacks using decoy web honeypots and to implement countermeasures against malicious threats. Web honeypots collect not only malicious accesses by attackers but also benign accesses such as those by web search crawlers. Thus, it is essential to develop a means of automatically identifying malicious accesses from mixed collected data including both malicious and benign accesses. Specifically, detecting vulnerability scanning, which is a preliminary process, is important for preventing attacks. In this study, we focused on classification of accesses for web crawling and vulnerability scanning since these accesses are too similar to be identified. We propose a feature vector including features of collective accesses, e.g., intervals of request arrivals and the dispersion of source port numbers, obtained with multiple honeypots deployed in different networks for classification. Through evaluation using data collected from 37 honeypots in a real network, we show that features of collective accesses are advantageous for vulnerability scanning and crawler classification.

Website Vulnerability Scanning Detection Inspired by Biological Adaptation Toward Diversifying Communication Services

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

Computer Security Symposium 2015 (CSS 2015)   2015 ( 3 ) 512 - 519   2015.10

Crawler Classification using Ant-based Clustering Scheme

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

2015 10TH INTERNATIONAL CONFERENCE FOR INTERNET TECHNOLOGY AND SECURED TRANSACTIONS (ICITST) ( IEEE )    84 - 89   2015  [Refereed]

　View Summary

Attacks against websites are increasing rapidly with the expansion of web services. More and more diversified web services make it difficult to prevent such attacks due to many known vulnerabilities in websites. To overcome this problem, it is necessary to collect latest attacks using decoy web honeypots and to implement countermeasures against malicious threats. Web honeypots collect not only malicious accesses by attackers but also benign accesses such as those by web search crawlers. Thus, it is essential to develop a means of identifying malicious accesses automatically from mixed collected data including both malicious and benign accesses. In this study, we have focused on detection of crawlers whose accesses has been increasing rapidly. A related study proposed a crawler detection scheme in which crawlers are identified based on the features of well-known crawlers such as Google crawlers. However, the diversity of crawler accesses has been increasing rapidly, and adapting to that diversity is a challenging task. Therefore, we have adapted AntTree, a bio-inspired clustering scheme that has high scalability and adaptability, for crawler detection. Through our evaluations using data collected in a real network, we show that AntTree can detect crawlers more precisely than a conventional scheme.

Hierarchical optimal control method for controlling self-organized networks with light-weight cost

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

2015 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) ( IEEE )    1 - 7   2015  [Refereed]

　View Summary

Self-organization has potential for high scalability, adaptability, flexibility, and robustness, which are vital features for realizing future networks. Convergence of self-organizing control, however, is comparatively slow in some practical applications. It is therefore important to enhance convergence of self-organizing controls without sacrificing the above advantages. Controlled self-organization is one key idea for that, which introduces an external controller into self-organizing systems to guide them to a desired state. We previously designed an external controller that provided the optimal input for fast convergence, however, it suffered from scalability issues. In this paper, we propose a hierarchical control system where a network is partitioned into some sub-networks, sub-controllers manage respective sub-networks, and the top-level deals with the global network stability. The proposed system achieves fast convergence speed with low computational and communication cost.

Potential-based routing with optimal feedback using reduced order model for controlled self-organizing networks

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

Technical Report of IEICE (IN2014-32)   114 ( 139 ) 13 - 18   2014.07

Robustness of potential-based routing with model predictive control

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

Technical Report of IEICE (IN2013-195)   113 ( 473 ) 305 - 310   2014.03

A predictive mechanism for enhancing adaptability of self-organised routing

Naomi Kuze

International Journal of Bio-Inspired Computation ( Inderscience Publishers )  6 ( 6 ) 384 - 384   2014.01

DOI

Enhancing Convergence with Optimal Feedback for Controlled Self-Organizing Networks

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

2014 IEEE 80TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL) ( IEEE )    1 - 7   2014  [Refereed]

　View Summary

To tackle with problems emerging with rapid growth of information networks in scale and complexity, self-organization is one of promising design principles for future networks. Convergence of self-organizing controls, however, is pointed out to be comparatively slow in some practical applications. Therefore, it is important to reveal and enhance convergence of self-organizing controls. In controlled self-organization, which introduces an external observer/controller into self-organizing systems, systems are controlled in order to guide them to the desired state. Although previous controlled self-organization schemes could achieve this feature, convergence speed for reaching an optimal or a semi-optimal solution is still a challenging task. In this paper, we take potential-based self-organizing routing and provide an optimal feedback for faster convergence using the future state of the system. Simulation results show that the convergence speed of potentials is improved by 7.3 times with a proposed mechanism.

Proposal and evaluation of a predictive mechanism for ant-based routing

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

Proceedings of International Conference on Emerging Network Intelligence (EMERGING 2013)     7 - 12   2013.09  [Refereed]

Proposal and evaluation of a predictive mechanism for controlled self-organization based routing

Naomi Kuze

Graduate School of Information Science and Technology, Osaka University     2013.02

Proposal and evaluation of ant-based routing with prediction

Naomi Kuze, Naoki Wakamiya, Masayuki Murata

Proceedings of the Fifth International Workshop on Guided Self-Organization (GSO-2012)     2012.09  [Refereed]

Proposal and Evaluation of AntNet Routing Mechanism with Autonomous Zoning

KUZE Naomi, WAKAMIYA Naoki, MURATA Masayuki

IEICE technical report. Information networks ( The Institute of Electronics, Information and Communication Engineers )  111 ( 469 ) 353 - 358   2012.03

　View Summary

To tackle problems emerging with rapid growth of information networks in scale and complexity, bio-inspired self-organization is considered one of promising design principles of a new generation network which is scalable, robust, adaptive, and sustainable. However, self-organizing systems would fall into local optimum or never converge under some environmental conditions. Controlled or guided self-organization is a novel concept attracting many researchers in these years, where loose and moderate control is imposed on a self-organizing system to push it toward a desired state. In this paper, we take AntNet, an ant-based routing protocol, as an example and consider a mechanism to accelerate convergence by limiting the search space. Controlled self-organization can accelerate convergence to a shorter path than AntNet.

Proposal and evaluation of ant-based routing with autonomous zoning for convergence improvement

Naomi Kuze, Naoki Wakamiya, Masayuki Murata

Proceedings of the 2012 15th International Conference on Network-Based Information Systems, NBIS 2012     290 - 297   2012  [Refereed]

　View Summary

To tackle problems emerging with rapid growth of information networks in scale and complexity, bio-inspired self organization is considered one of promising design principles of a new generation network which is scalable, robust, adaptive, and sustainable. However, self-organizing systems would fall into a local optimum or never converge under some environmental conditions. Controlled or guided self-organization is a novel concept attracting many researchers in these years, where loose and moderate control is imposed on a self-organizing system to push it toward a desired state. In this paper, we take Ant Net, an ant-based routing protocol, as an example and consider a mechanism to accelerate convergence by limiting the search space. The proposed mechanism is compared with Ant Net and HOPNET from viewpoints of the convergence time, path length, and control overhead. Simulation results show that our proposal can accelerate convergence of ant-based routing to a shorter path than Ant Net and with lower control overhead than HOPNET. © 2012 IEEE.

DOI