We designed an FPGA-based parallel machine called "RASH"(Reconfigurable Architecture based on Scalable Hardware) for high speed and flexible signal/data processing. Cryptanalysis is one of the killer applications for FPGA-based machines because huge amounts of logical and/or simple arithmetic operations are required and FPGA is suitable for this. One of the well-known activities in cryptanalysis is the DES (Data Encryption Standard) cracking contest conducted by RSA Data Security. TMTO (Time-Memory Trade-Off) Cryptanalysis is a practical method to dramatically shorten the time for key search when plaintext is given in advance. A string of ASCII characters is used as the key much like a password. The ASCII character is 7-bit character and is changed to 96 kinds of value. The 56-bit DES key is given with a string of 8 ASCII characters. Although the DES key has 64 trillion(=256) possibilities, the key that is given with a string has only 6.4 trillion(=968) possibilities. Therefore, we improve TMTO cryptanalysis so that we search only the limited key by ASCII characters and reduce the quantity of computation. In this paper, we demonstrate how TMTO cryptanalysis for limited key is well suited to our FPGA-based RASH machine. By limiting the key to a string, DES key will be found at 80% probability within 45 minutes after ciphertext is given on 10 units of RASH. The precomputation before starting key search takes 3 weeks on the same RASH configuration.

Secret sharing scheme (SS) has been extensively studied since SSs are important not only for secure data storage but also as a fundamental building block for multiparty computation (MPC). For an application to secure data storage, the share size of SS is an important factor. For an application to a building block for MPC, the extendibility to MPC is needed. Computationally secure SSs and a ramp scheme have a small share size but there have been few studies concerning their MPC. In contrast, there have been many studies about MPC on Shamir's and replicated SSs while their share size is large. We consider an application scenario of SS such as applying SSs to secure data storage service with MPC. In this application, users store their data in servers through SS, and sometimes the servers perform MPC as an optional feature. In this case, the extendibility to MPC is needed and good code-efficiency is preferable. We propose a new computational SS, and show how to convert shares of our SS and a ramp SS to those of multiparty-friendly SS such as Shamir's and replicated SS. This enables one to secretly-share data compactly and extend secretly-shared data to MPC if needed.

Simulation based education and training, especially wargame simulations, are being used widely in the field of defense modeling and in simulation communities. In order to efficiently train students and trainees, the wargame simulations must have both high performance and high fidelity. In this paper, we discuss design and implementation issues for a prototype of a parallel and distributed wargame simulation system. This wargame simulation system is based on High Level Architecture (HLA) and employs some optimization to achieve both high performance and high fidelity in the simulation system. The results show that the proposed optimization method is effective when optimization is applied to 93.5% or less of the moving objects (PFs) within the range of detection (RofD) of both the red and blue teams. Specifically, when each team has 1000 PFs we found that if the percentage of PFs within RofD is less than 50% for both teams, our method is over two times better than for the situation where there is no optimization.