The Security Infrastructure Technology
for Integrated Utilization of Big Data

[J-1] Atsuko Miyaji and Kazumasa Omote, "Self-healing wireless sensor networks", Concurrency and Computation: Practice and Experience, Vol. 27 No.10, 2547-2568, 2015

[J-2] Steven Gordon, Atsuko Miyaji, Chunhua Su and Karin Sumongkayothin, "M-ORAM: A Matrix ORAM with logN bandwidth cost", The 16th International Workshop on Information Security Applications (WISA 2015), Lecture Notes in Computer Science, 9503, Springer-Verlag, 3-15, 2015.

[J-3] Jiageng Chen, Atsuko Miyaji, Chunhua Su and Liang Zhao, "A New Statistical Approach For Integral Attack", The 9th International Conference on Network and System Security (NSS 2015), Lecture Notes in Computer Science, 9408, 345-358, 2015.

[J-4] Atsuko Miyaji and Syouhei Nishida, "A Scalable and Efficient Multiparty Private Set Intersection ", The 9th International Conference on Network and System Security(NSS 2015), Lecture Notes in Computer Science, 9408(2015), Springer-Verlag, 376-385.

Both scalability and flexibility become crucial for privacy preserving protocols in the age of Big Data. Private Set Intersection (PSI) is one of important privacy preserving protocols. Usually, PSI is executed by 2-parties, a client and a server, where both a client and a server compute jointly the intersection of their private sets and at the end only the client learns the intersection and the server learns nothing. From the scalable point of view, however, the number of parties are not limited to two. In this paper, we propose a scalable and flexible multiparty PSI (MPSI) for the first time: the data size of each party is independent to each other and the computational complexity is independent to the number of parties. We also propose d-and-over MPSI for the first time.

Keywords

Multi party, PSI

[J-5] Ryoma Ito and Atsuko Miyaji, "How TKIP induces biases of internal states of generic RC4", The 20th Australasian Conference on Information Security and Privacy(ACISP 2015), Lecture Notes in Computer Science, 9144(2015), Springer-Verlag, 329-342.

In 2014, Sen Gupta et al. found linear correlations between the keystream byte and known RC4 key bytes. In 2015, Our previous work extended linear correlations to include unknown internal states as well as the keystream byte and known RC4 key bytes. They found more than 150 linear correlations experimentally, and proved only 6 cases theoretically. In this paper, we will provide theoretical proof of 15 cases out of their unproven linear correlations. These theoretical results demonstrated how TKIP key generation procedure in WPA induces biases on internal states different from generic RC4.

Keywords

RC4, WPA, linear correlation

[J-6] Steven Gordon, Atsuko Miyaji, Chunhua Su and Karin Sumongkayothin, "Analysis of Path ORAM toward Practical Utilization", 18th International Conference on Network-Based Information Systems(NBiS), 646-651, 2015.

Oblivious RAM is known as a secure protocol for hiding client's access pattern from an untrusted server. However, the current ORAM algorithms still incur large computation, storage and communication overheads. For this reason, investigation of the ORAM limitations and methods to improve efficiency in real-world environments is necessary. In this paper we focus on one of the leading algorithms, Path ORAM, and propose an efficient implementation. Specifically we analyse the selection of encryption algorithms, concluding the use of AES-GCM to avoid duplication of blocks on the server. Also we propose extending Path ORM by using local caching on the client to reduce communication overhead. Experimental results from our Python implementation show key tradeoffs for ORAM design.

Keywords

ORAM

[J-7] Jiageng Chen, Atsuko Miyaji, Hiroyuki Sato and Chunhua Su, "Improved Lightweight Pseudo-Random Number Generators for the Low-Cost RFID Tags", The 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom'15), IEEE, 500-508, 2015.

EPC Gen2 tags are working as international RFID standards for the use in the supply chain worldwide, such tags are computationally weak devices and unable to perform even basic symmetric-key cryptographic operations. For this reason, to implement robust and secure pseudo-random number generators (PRNG) is a challenging issue for low-cost Radio-frequency identification (RFID) tags. In this paper, we study the security of LFSR-based PRNG implemented on EPC Gen2 tags and exploit LFSR-based PRNG to provide a better constructions. We provide a cryptanalysis against the J3Gen which is LFSR-based PRNG and proposed by Sugei et al. for EPC Gen2 tags using distinguish attack and make observations on its input using NIST randomness test. We also test the PRNG in EPC Gen2 RFID Tags by using the NIST SP800-22. As a counter-measure, we propose two modified models based on the security analysis results. We show that our results perform better than J3Gen in terms of computational and statistical property.

Keywords

light weight pseudo random number generators，RFID tag，randomness test

[J-8] Atsuko Miyaji and Xiaonan Shi and Satoru Tanaka, "Extended Explicit Relations Between Trace, Definition Field, and Embedding Degree", 6th International Conference on Algebraic Informatics (CAI 2015), Lecture Notes in Computer Science, 9270(2015), Springer-Verlag, 165-175.

An elliptic curve cryptosystem (ECC) is one of public key cryptosystem, whose security is based on elliptic curve discrete logarithm problem (ECDLP). An elliptic curve is uniquely determined by mathematical parameters such as j-invariant of an elliptic curve. By giving trace of elliptic curve, t, a definition field F_p , and discriminant D , an elliptic curve with order E(F_p) = n is determined. Therefore it is an open problem to determine explicit relations between the mathematical parameters and the embedding degrees k. Hirasawa and Miyaji presented concrete relations between the mathematical parameters and the embedding degrees. In this research, a new explicit relation between elliptic-curve parameters and embedding degrees is investigated by generalizing their research.

Keywords

elliptic curve, embedding degree, trace

[A-1] Koji Kitamura, Kenta Imai, Yoshifumi Nishida, Hiroshi Takemura, Tatsuhiro Yamanaka, "Potential Risk Assessment System by Integrating Injury Data at Multiple Schools", The 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015), 1991-1998, July 2015.

A large number of injuries occur in Japanese school environments. To prevent injuries in schools, it is important to understand high-risk injuries based on injury data. In this paper, "high-risk" injuries indicate a high risk of leading to serious or fatal injuries. However, it is difficult to understand these injuries from the injury data of just a single school because a single school does accumulate much data. In this study, we developed a system for predicting serious injuries at individual schools by using injury data from multiple schools. The prediction process is as follows. First, the system registers injury situations with the feature values that express them by using a text mining technique to the database. Second, for a given injury data at target school, the system searches for similar injury situations in the registered data. Finally, it reports the particularly serious injuries from the viewpoint of medical cost from among the data covering similar situations. The effectiveness of the system was confirmed using the data of 5,817 school injuries.

[J-1] Atsuko Miyaji and Mazumder Rashed, "A new (n, 2n) Double Block Length Hash Function based on Single Key Scheduling", The 29th IEEE International Conference on Advanced Information Networking and Applications (AINA 2015), IEEE, 1-8

In this paper we propose a double block length hash function called MR-MMO. Our scheme satisfies two calls of (n; 2n) blockcipher and can compress 3n bits to 2n bits (n = 128 bits). The Collision Resistance (CR) and Preimage Resistance (PR) of MR-MMO are respectively 2^126.70 and 2^252.5. Surprisingly, the collision security bound of our scheme is the best in compare with other existing schemes. We use a single key scheduling for each compression function which is great in respect of cost and time. Additionally, it can be said that the proof technique of Weimar-DM, Tandem-DM, Hirose-DM are based on Ideal Cipher Model (ICM while we use Weak Cipher Model (WCM) tool. Davies Meyer (DM) mode is used in the above all schemes, we also made a change using Matyas Meyer Oseas (MMO) mode. It is also obvious that the proof technique of our scheme is very simple, straightforward and easy to understand.

Keywords

Hash function, Blockcipher, SBL, DBL, Collision resistance (CR), Preimage resistance (PR), ICM, WCM

[J-2] Ryoma Ito and Atsuko Miyaji, "New Linear Correlations related to State Information of RC4 PRGA", The 22nd International Workshop on Fast Software Encryption (FSE 2015), Lecture Notes in Computer Science, Springer-Verlag, to appear.

RC4 is a stream cipher designed by Ron Rivest in 1987, and is widely used in various applications. WPA is one of these applications, where TKIP is used for a key scheduling procedure to avoid weak IV generated by WEP. In FSE 2014, two different attacks against WPA were proposed by Sen Gupta et al. and Paterson et al. Both focused correlations between the keystream bytes and the first three bytes of the RC4 key in WPA. In this paper, we focus on linear correlations between unknown internal state and the first three bytes of the RC4 key in both generic RC4 and WPA, where the first three bytes of the RC4 key is known in WPA. As a result, we could discover various new linear correlations, and prove these correlations theoretically.

Keywords

RC4, WPA, linear correlations

[K-1] Kiyomoto, Y. Miyake, "Data Value Estimation for Privacy-Preserving Big/Personal Data Businesses", FMfI2014 Post-proceedings, 2015, accepted.

"Value Proposition" is a key factor when designing a business model. In personalized services, data value should be estimated using a certain model of data valuation. Generally, the data value depends on the size and precision of data, and it is expected to reflect the parameter $k$ in the size of $k$-anonymized data sets and its data precision. A data set is said to have \textit{$k$-anonymity} if each record is indistinguishable from at least $k-1$ other records with respect to certain identifying attributes called \textit{quasi-identifiers}. The parameter $k$ influences not only the re-identification risk of the published data but also its value. When $k$ is large, many attributes in the published data are replaced with uncharacteristic values in order to satisfy $k$-anonymity. On the other hand, a small $k$ involves a serious risk of re-identification. There is a trade-off between privacy level and data value in the generation of $k$-anonymized data sets. Based only on the privacy requirement for reducing the re-identification risk, many people may assent to distribution of their private data in the form of a $k$-anonymized table when $k$ is large enough or where as large $k$ as possible is chosen.

In this paper, we present a model for finding an appropriate $k$ in $k$-anonymization. The model suggests that an optimal $k$ exists that is appropriate to achieve a balance between value and anonymity when personal data are published.

Keywords

k-anonymity, Data Value, Personal Data

[A-1] Y. Nishida, D. Nakazato, K. Kitamura, H. Mizoguchi, T. Yamanaka, "Childhood Home-Injury-Situation Simulation for Individual Environments Based on Child Physical Model and Injury Semantic Structure Model", the 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) , 2015 (in press)

Most accidents involving children below the age of five occur within their homes. Since it is important to maintain a safe home environment for children, it is imperative to be able to predict what kinds of accidents may occur in a particular environment, and then to find ways to improve that environment. However, the various and scattered statistical data sources and scientific knowledge related to accident prediction have not been structured for integrative utilization. In this paper, the authors report on the development of a new simulation technology that can be used to predict the kinds of accidents that may occur in a particular environment by means of a hybrid memory- and model-based approach. The system consists of a graph-structuralized accident database created from large-scale accident data (which enables the memory-based approach), and a development behavior model which describes the statistical relationship between a body interaction abilities and the age of children.