• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.742-746
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• 2010

In this paper, we propose new randomness testing methods based on approximate periods in order to improve the previous randomness testing method using exact pattern matching. Finding approximate periods of random sequences enables us to search similarly repeated parts, but it has disadvantages since it takes long time. In this paper we propose randomness testing methods whose time complexity is O($n^2$) by reducing the time complexity of computing approximate periods from O($n^3$) to O($n^2$). Moreover, we perform some experiments to compare pseudo random number generated by AES cryptographic algorithms and true random number.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.2.2-2
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• 2003

PRF(Pseudo Random Function)에 대한 랜덤성 검증은 pre-computation공격에 대해 알고리즘이 특별한 통계적 약점이 없이 적절하게 개발되었는지를 평가할 수 있다. 이 논문에서는 NIST에서 실시한 AES 후보 알고리즘 랜덤성 평가 기준을 적용하여 IEEE의 802.11i Draft에서 인증자와 요청자가 비밀키(PTK, GTK)를 생성하는데 사용되는 PRF의 랜덤성을 검증하였다. 랜덤성 테스트를 위해 표본 수는 300개, 표본 길이는 2$^{20}$ (= 1,048,576)으로 검정 표본을 생성하고, 유의 수준은 0.01로 선택하였다. 랜덤성 검증 방법으로는 NIST의 16가지 통계 테스트를 사용하였다.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.19-28
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• 2011

Adaptive Random Testing (ART) aims to enhance the performance of pure random testing by detecting failure region in a software. The ART algorithm generates effective test cases which requires less number of test cases than that of pure random testing. However, all ART algorithms currently proposed are designed for the tests of monolithic system or unit level. In case of integrated system tests, ART approaches do not achieve same performances as those of ARTs applied to the unit or monolithic system. In this paper, we propose an extended ART algorithm which can be applied to the integrated system testing environment without degradation of performance. The proposed approach investigates an input distribution of the unit under a test with limited number of seed input data and generates information to be used to resizing input domain partitions. The simulation results show that our approach in an integration environment could achieve similar level of performance as an ART is applied to a unit testing. Results also show resilient effectiveness for various failure rates.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.531-540
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• 2008

An Adaptive Random Testing(ART) is one of test case generation algorithms, which was designed to get better performance in terms of fault-detection capability than that of Random Testing(RT) algorithm by locating test cases in evenly spreaded area. Two ART algorithms, such as Distance-based ART(D-ART) and Restricted Random Testing(RRT), had been indicated that they have significant drawbacks in computations, i.e., consuming quadratic order of runtime. To reduce the amount of computations of D-ART and RRT, iterative partitioning of input domain strategy was proposed. They achieved, to some extent, the moderate computation cost with relatively high performance of fault detection. Those algorithms, however, have yet the patterns of non-uniform distribution in test cases, which obstructs the scalability. In this paper we analyze the distribution of test cases in an iterative partitioning strategy, and propose a new method of input domain enlargement which makes the test cases get much evenly distributed. The simulation results show that the proposed one has about 3 percent of improvement in terms of mean relative F-measure for 2-dimension input domain, and shows 10 percent improvement for 3-dimension space.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.5
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• pp.137-145
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• 2003

Nowadays, people can communicate with each other on any time at my place by development of wireless communications. But, the openness of mobile communications Poses serious security threats and the security is necessary on mobile communications to support the secure communication channel. The most commonly method is stream cipher for mobile communications. Generally, this stream cipher is implemented by LFSR(Linear Feedback Shift Register). On this paper proposes the modified mechanism of the S box is usually used in block cipher to advance security og the stream cipher and this mechanism is the modified three one in consideration og the randomness. Generally, S box that is function with nonlinear property makes data more strong by attack. The randomness test of the proposed algorithm is used Ent Pseudorandom Number Sequence Test Program and by the test result it proves that it has better randomness and serial correlation value than the based stream cipher on respective test.

• Journal of KIISE:Software and Applications
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• v.36 no.6
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• pp.451-461
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• 2009

The Adaptive Random Testing(ART) aims to improve the performance of traditional Random Testing(RT) by reducing the number of test cases to find the failure region which is located in the input domain. Such enhancement can be obtained by efficient selection algorithms of test cases. The ART through Iterative Partitioning(IP-ART) is one of ART techniques and it uses an iterative input domain partitioning method to improve the performance of early-versions of ART which have significant drawbacks in computation time. And the IP-ART with Enlarged Input Domain(EIP-ART), an improved version of IP-ART, is known to make additional performance improvement with scalability by expanding to virtual test space beyond real input domain of IP-ART. The EIP-ART algorithm, however, have the drawback of heavy cost of computation time to generate test cases mainly due to the virtual input domain enlargement. For this reason, two algorithms are proposed in this paper to mitigate the computation overhead of the EIP-ART. In the experiments by simulations, the tiling technique of input domain, one of two proposed algorithms, showed significant improvements in terms of computation time and testing performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.180-191
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• 2008

An Adaptive Random Testing (ART) is one of test case generation algorithms that are designed to detect common failure patterns within input domain. The ART algorithm shows better performance than that of pure Random Testing (RT). Distance-bases ART (D-ART) and Restriction Random Testing (RRT) are well known examples of ART algorithms which are reported to have good performances. But significant drawbacks are observed as quadratic runtime and non-uniform distribution of test case. They are mainly caused by a huge amount of distance computations to generate test case which are distance based method. ART through Iterative Partitioning (IP-ART) significantly reduces the amount of computation of D-ART and RRT with iterative partitioning of input domain. However, non-uniform distribution of test case still exists, which play a role of obstacle to develop a scalable algerian. In this paper we propose a new ART method which mitigates the drawback of IP-ART while achieving improved fault-detection capability. Simulation results show that the proposed one has about 9 percent of improved F-measures with respect to other algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.141-143
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• 2012

RFID 미들웨어의 평가를 위한 방법으로서, 테스트 데이터셋을 이용한 시뮬레이션은 일반적으로 사용되는 평가 방법이다. 태그 식별자에 따라 순차생성된 가상 데이터셋이나 랜덤 생성된 데이터셋의 경우 미들웨어의 단순 처리량을 평가하기에는 유용하나 미들웨어의 정확성이나 실행 가능성를 평가하기에는 한계가 있다. 테스트 데이터셋은 실제 리더에서 생성된 데이터셋과 매우 유사하여야 함에도 불구하고, 테스트 데이터셋의 품질 기준이 정의되어 있지 않음에 따라 테스트 데이터셋이 얼마만큼 실제 데이터셋과 유사한 지를 평가하기가 어려운 문제가 있다. 이를 위해 본 논문에서는 RFID 미들웨어의 평가에 사용되는 테스트 데이터셋의 품질을 평가하기 위한 품질 지표를 제안한다. 제안하는 품질 지표는 실제 RFID 리더에 태그가 통과할 때 생성되는 데이터 셋을 기반으로 하여 정의하였으며, RFID 무선 인식의 고유의 특성, 즉 중복성과 불확실성을 수치화해서 표현하는 특징이 있다. 또한 제안한 품질 지표를 실제 RFID 리더를 통해 생성한 데이터셋에 적용하여 비교 검토함으로써 품질 지표의 유용성을 입증한다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.223-225
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• 2004

이동통신의 지속적인 발달은 사용자들에게 많은 편리성을 제공해주고 있다. 이와 반면에, 이동통신의 개방성은 무선공격에 심각하게 노출되어 있으며, 안전한 통신을 위해 이동통신망의 보안은 필수적이다. 본 논문서는 이동통신상에 전송되는 데이터를 보다 안전하게 보호하기 위한 메커니즘으로서 스트림 암호알고리즘에 두개의 S박스를 사용하고, 두 개의 S박스 사용에 따른 메커니즘을 제안한다. 먼저, DES의 각 S박스에 대한 랜덤성을 테스트하여 랜덤특성이 좋은 두개의 S박스를 고찰한다. 두 개의 S박스는 제안하는 메커니즘에 따라 스트림 암호알고리즘에 적용하며, 이 때 두개의 S박스는 비트가 0이면 S박스를 통과하고, 1이면 통과하지 않는 메커니즘을 사용한다. 이에 대한 실험은 기존 모델과의 비교분석을 통해 제안한 모델의 효율성을 증명한다.

• The KIPS Transactions:PartD
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• v.8D no.1
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• pp.81-86
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• 2001

one key goal of software testing is to generate a 'good' test data set, which is consideres as the most difficult and time-consuming task. This paper discusses how genetic algorithns can be used for automatic generation of test data set for software testing. We employ mutation testing to show the effectiveness of genetic algorithms (GAs) in automatic test data generation. The approach presented in this paper is different from other in that test generation process requireas no lnowledge of implementation details of a program under test. In addition, we have conducted some experiments and compared our approach with random testing which is also regarded as a black-box test generation technique to show its effectiveness.