Takuro Hosoi

• Technical Associate

Interest

• Network security

Publications

• Kanta Matsuura, Takurou Hosoi. Mechanism Design of Data Sharing for Cybersecurity Research, IPSI Transactions on Advanced Research, Vol.11, No.1, pp.35-40, 2015 [detail]

abstract

If we want to realize a scientific approach to cybersecurity, we need objective and reproducible evaluation of security. Although some of cryptographic technologies have rigorous security proofs, a lot of cybersecurity technologies rely on experimental evaluation which needs good datasets. One may expect that sharing such datasets would help at least the reproducibility of the evaluation. At the same time, one may be afraid that effective mechanism design is difficult because there have been a lot of studies on disincentive problems (e.g. free-riding) associated with information sharing in cybersecurity. However, the requirements and typical solutions for data sharing would be different from those for information sharing. In this paper, we comprehensively discuss the features of "data sharing for cybersecurity research" based on a systematic comparison with "information sharing for cybersecurity practice". We also report a Japanese case in the field of malware analysis. One important finding is that considering human resource development is an important factor in the activities associated with data sharing.
• Kanta Matsuura, Takurou Hosoi. Data Sharing for Cybersecurity Research and Information Sharing for Cybersecurity Practice, The 8th International Workshop on Security (IWSEC2013), 2013 [detail]

abstract

When we want to realize a scientific approach to cybersecurity, we need objective and reproducible evaluation of security properties. Although some of cryptographic technologies have rigorous security proofs, a lot of cybersecurity technologies rely on experimental security evaluation which needs good datasets. One may expect that sharing such datasets would help at least the reproducibility of the evaluation. At the same time, one may be afraid that effective mechanism design is not trivial because there have been a lot of studies on disincentive problems (e.g. free-riding) associated with information sharing for cybersecurity practice. However, the requirements and typical solutions for data sharing would be different from those for information sharing. In this poster, we comprehensively discuss the features of data sharing for cybersecurity research based on a systematic comparison with information sharing for cybersecurity practice. We also identify some intrinsic limitations of the data sharing approach.
• Takurou Hosoi, Kanta Matsuura. Effectiveness of a Change in TCP Retransmission Timer Management for Low-rate DoS Attack Mitigation and Attack Variants, The 8th International Workshop on Security (IWSEC2013), 2013 [detail]

abstract

The mechanism of TCP retransmission timeout is essential to the Internet congestion control. But existing research pointed out that this mechanism allows DoS attack with low-rate mean traffic. We proposed a change in TCP retransmission timeout management, in which length of TCP retransmission timer is increased not to precisely twice of the prior timer length in successive timeout waiting. We investigate its effectiveness in DoS attack mitigation analytically, and some attack variants under this countermeasure.
• Kanta Matsuura, Takurou Hosoi. Data Sharing for Cybersecurity Research: A Comparison with Information Sharing for Cybersecurity Practice, Ninth Annual Forum on Financial Information Systems and Cybersecurity: A Public Policy Perspective, 2013
• Takurou HOSOI, Kanta Matsuura. Evaluation of the Common Dataset Used in Anti-Malware Engineering Workshop 2009, Lecture Notes in Computer Science (Recent Advances in Intrusion Detection, 13th International Symposium on Recent Advances in Intrusion Detection: RAID 2010), Vol.6307, pp.496-497, 2010
• Takuro Hosoi, Kanta Matsuura, Hideki Imai. IP Trace Back by Packet Marking Method with Bloom Filters, Proceedings of the 2007 IEEE International Carnahan Conference on Security Technology (2007 ICCST) 41st Annual Conference, pp.255-263, 2007

Kensuke Tamura

• Lecturer

Interest

• Digital forensics, Control system security

Publications

• Kensuke Tamura, Kanta Matsuura. Improvement of Anomaly Detection Performance using Packet Flow Regularity in Industrial Control Networks, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E102-A, No.1, pp.65-73, 2019 [detail]

abstract

Since cyber attacks such as cyberterrorism against Industrial Control Systems (ICSs) and cyber espionage against companies managing them have increased, the techniques to detect anomalies in early stages are required. To achieve the purpose, several studies have developed anomaly detection methods for ICSs. In particular, some techniques using packet flow regularity in industrial control networks have achieved high-accuracy detection of attacks disrupting the regularity, i.e. normal behavior, of ICSs. However, these methods cannot identify scanning attacks employed in cyber espionage because the probing packets assimilate into a number of normal ones. For example, the malware called Havex is customized to clandestinely acquire information from targeting ICSs using general request packets. The techniques to detect such scanning attacks using widespread packets await further investigation. Therefore, the goal of this study was to examine high performance methods to identify anomalies even if elaborate packets to avoid alert systems were employed for attacks against industrial control networks. In this paper, a novel detection model for anomalous packets concealing behind normal traffic in industrial control networks was proposed. For the proposal of the sophisticated detection method, we took particular note of packet flow regularity and employed the Markov-chain model to detect anomalies. Moreover, we regarded not only original packets but similar ones to them as normal packets to reduce false alerts because it was indicated that an anomaly detection model using the Markov-chain suffers from the ample false positives affected by a number of normal, irregular packets, namely noise. To calculate the similarity between packets based on the packet flow regularity, a vector representation tool called word2vec was employed. Whilst word2vec is utilized for the calculation of word similarity in natural language processing tasks, we applied the technique to packets in ICSs to calculate packet similarity. As a result, the Markov-chain with word2vec model identified scanning packets assimilating into normal packets in higher performance than the conventional Markov-chain model. In conclusion, employing both packet flow regularity and packet similarity in industrial control networks contributes to improving the performance of anomaly detection in ICSs.

Kaname Shimada

• Associate Research Fellow

Interest

• Anonymous communication system

Ryuya Hayashi

• Doctor Course 3

Interest

• Cryptography

Publications

• Ryuya Hayashi, Taiki Asano, Junichiro Hayata, Takahiro Matsuda, Shota Yamada, Shuichi Katsumata, Yusuke Sakai, Tadanori Teruya, Jacob C. N. Schuldt, Nuttapong Attrapadung, Goichiro Hanakoka, Kanta Matsuura, Tsutomu Matsumoto. Signature for Objects: Formalizing How to Authenticate Physical Data and More, Lecture Notes in Computer Science (The 27th International Conference on Financial Cryptography and Data Security: FC2023), Vol.13950, pp.182-199, 2023 [detail]

abstract

While the integrity of digital data can be ensured via digital signatures, ensuring the integrity of physical data, i.e., objects, is a more challenging task. For example, constructing a digital signature on data extracted from an object does not necessarily guarantee that an adversary has not tampered with the object or replaced this with a cleverly constructed counterfeit. This paper proposes a new concept called signatures for objects to guarantee the integrity of objects cryptographically. We first need to consider a mechanism that allows us to mathematically treat objects which exist in the physical world. Thus, we define a model called an object setting in which we define physical actions, such as a way to extract data from objects and test whether two objects are identical. Modeling these physical actions via oracle access enables us to naturally enhance probabilistic polynomial-time algorithms to algorithms having access to objects - we denote these physically enhanced algorithms (PEAs). Based on the above formalization, we introduce two security definitions for adversaries modeled as PEAs. The first is unforgeability, which is the natural extension of EUF-CMA security, meaning that any adversary cannot forge a signature for objects. The second is confidentiality, which is a privacy notion, meaning that signatures do not leak any information about signed objects. With these definitions in hand, we show two generic constructions: one satisfies unforgeability by signing extracted data from objects; the other satisfies unforgeability and confidentiality by combining a digital signature with obfuscation.

Iifan Tyou

• Doctor Course 1*

Interest

• Blockchain

Yuichi Tanishita

• Doctor Course 1

Interest

• Cryptography

Yusuke Hirosawa

• Master Course 2

Interest

• Cryptography

Shinsaku Naitou

• Master Course 2

Interest

• Blockchain, Network Security

Kotei Jiang

• Master Course 1

Interest

• Blockchain

Haruki Nishii

• Master Course 1

Interest

• Blockchain

Nyan Win Htike

• Research Student

Interest

• Blockchain