• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3384-3400
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• 2021

With the advent of the data era, people pay much more attention to data corruption. Aiming at the problem that the majority of existing schemes do not support corruption detection of ciphertext data stored in cloud environment, this paper proposes a data corruption detection scheme based on ciphertexts in cloud environment (DCDC). The scheme is based on the anomaly detection method of Gaussian model. Combined with related statistics knowledge and cryptography knowledge, the encrypted detection index for data corruption and corruption detection threshold for each type of data are constructed in the scheme according to the data labels; moreover, the detection token for data corruption is generated for the data to be detected according to the data labels, and the corruption detection of ciphertext data in cloud storage is realized through corresponding tokens. Security analysis shows that the algorithms in the scheme are semantically secure. Efficiency analysis and simulation results reveal that the scheme shows low computational cost and good application prospect.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.149-156
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• 2023

OOXML-based MS-Office digital files are extensively utilized by businesses and organizations worldwide. However, OOXML-based MS-Office digital files are vulnerable to forgery and corruption attack by including hidden suspicious information, which can lead to activating malware or shell code being hidden in the file. Such malicious code can cause a computer system to malfunction or become infected with ransomware. To prevent such attacks, it is necessary to analyze and detect the corruption of OOXML-based MS-Office files. In this paper, we examine the weaknesses of the existing OOXML-based MS-Office file structure and analyzes how concealment and forgery are performed on MS-Office digital files. As a result, we propose a system to detect hidden data effectively and proactively respond to ransomware attacks exploiting MS-Office security vulnerabilities. Proposed system is designed to provide reliable and efficient detection of hidden data in OOXML-based MS-Office files, which can help organizations protect against potential security threats.

• ETRI Journal
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• 제31권4호
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• pp.451-453
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• 2009

This letter proposes the use of vowel sound detection for voice activity detection. Vowels have distinctive spectral peaks. These are likely to remain higher than their surroundings even after severe corruption. Therefore, by developing a method of detecting the spectral peaks of vowel sounds in corrupted signals, voice activity can be detected as well even in low signal-to-noise ratio (SNR) conditions. Experimental results indicate that the proposed algorithm performs reliably under various noise and low SNR conditions. This method is suitable for mobile environments where the characteristics of noise may not be known in advance.

• Structural Engineering and Mechanics
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• 제55권6호
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• pp.1223-1239
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• 2015

A method for structural damage identification based on Chaotic Artificial Bee Colony (CABC) algorithm is presented. ABC is a heuristic algorithm with simple structure, ease of implementation, good robustness but with slow convergence rate. To overcome the shortcoming, the tournament selection mechanism is chosen instead of the roulette mechanism and chaotic search mechanism is also introduced. Residuals of natural frequencies and modal assurance criteria (MAC) are used to establish the objective function, ABC and CABC are utilized to solve the optimization problem. Two numerical examples are studied to investigate the efficiency and correctness of the proposed method. The simulation results show that the CABC algorithm can identify the local damage better compared with ABC and other evolutionary algorithms, even with noise corruption.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1383-1391
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• 2018

A new nonlinear filtering algorithm for effectively denoising images corrupted by the random-valued impulse noise, called dual sliding statistics switching median (DSSSM) filter is presented in this paper. The proposed DSSSM filter is made up of two subunits; i.e. Impulse noise detection and noise filtering. Initially, the impulse noise detection stage of DSSSM algorithm begins by processing the statistics of a localized detection window in sorted order and non-sorted order, simultaneously. Next, the median of absolute difference (MAD) obtained from both sorted statistics and non-sorted statistics will be further processed in order to classify any possible noise pixels. Subsequently, the filtering stage will replace the detected noise pixels with the estimated median value of the surrounding pixels. In addition, fuzzy based local information is used in the filtering stage to help the filter preserves the edges and details. Extensive simulations results conducted on gray scale images indicate that the DSSSM filter performs significantly better than a number of well-known impulse noise filters existing in literature in terms of noise suppression and detail preservation; with as much as 30% impulse noise corruption rate. Finally, this DSSSM filter is algorithmically simple and suitable to be implemented for electronic imaging products.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.649-664
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• 2011

Cooperative spectrum sensing (CSS) with decision fusion is considered as a key technology for tackling the challenges caused by fading/shadowing effects and noise uncertainty in spectrum sensing in cognitive radio. However, most existing solutions assume an error-free decision transmission, which is obviously not the case in realistic scenarios. This paper extends the general decision-fusion-based CSS scheme by considering the fading/shadowing effects and noise corruption in the common control channels. With this more practical model, the fusion centre first estimates the local decisions using a binary minimum error probability detector, and then combines them to get the final result. Theoretical analysis and simulation of this CSS scheme are performed over typical channels, which suggest some performance deterioration compared with the pure case that assumes an error-free decision transmission. Furthermore, the fusion strategy optimization in the proposed cooperation model is also investigated using the Bayesian criteria. The numerical results show that the total error rate of noisy CSS is higher than that of the pure case, and the optimal values of fusion parameter in the counting rule under both cases decrease as the local detection threshold increases.

• 한국정보통신학회논문지
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• 제15권12호
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• pp.2655-2663
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• 2011

지금까지 심방세동을 검출하는 방법은 P파의 형태, 시간 주파수 영역 분석법이 주를 이루었다. 하지만 P파는 잡음의 영향을 많이 받는 환경에서는 검출의 정확도가 떨어지며, 시간 주파수 영역 분석법은 RR 간격에 따라 변화하는 불규칙적 리듬에 관한 정보를 정확하게 얻지 못하는 단점이 있다. 본 연구에서는, P파의 형태는 고려하지 않고, 불규칙 RR 간격 리듬의 비선형적 특성 분석을 통한 심방세동 검출 알고리즘을 제안한다. 이를 위해 불규칙 RR 간격 리듬을 다양성, 무작위성, 복잡성으로 각각 정의하고 제곱평균제곱근(RMSSD), 전환점비(TPR), 표본 엔트로비(SpEn)의 3가지 비선형적 특성 분석을 통하여 심방세동을 분류하였다. 제안된 알고리즘의 검출 성능을 평가하기 위해 3가지 통계치의 최적값을 설정하고 MIT-BIH 심방세동 데이터베이스와 부정맥 데이터베이스를 이용하여 실험하였다. 성능 평가 결과, MIT-BIH 심방세동 데이터베이스에 대해서는 민감도(sensitivity:94.5%), 특이도(specificity:96.2%)를 각각 나타내었으며, 부정맥 데이터베이스에 대해서는 민감도(89.8%), 특이도(89.62%)를 각각 나타내었다.

• 전기전자학회논문지
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• 제28권1호
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• pp.116-122
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• 2024

AMBA AHB-Lite 버스는 저전력 및 경제성 측면에서 SoC에 널리 사용되는 온칩 버스 프로토콜이다. 하지만 이 프로토콜은 종단간 데이터 무결성을 위한 에러 검출 및 정정이 불가능하다. 이로 인해 자동차와 같이 열악한 환경에서 동작하는 경우에 데이터 변질과 시스템 불안정을 일으킬 수 있다. 이러한 문제를 해결하기 위해 본 논문에서는 AMBA AHB-Lite 버스에 SEC-DED(Single Error Correction-Double Error Detection)를 적용하는 방법을 제안한다. 이는 전송 중 발생하는 데이터 에러를 실시간으로 감지하고 정정하여 종단간 데이터 무결성을 강화한다. 시뮬레이션 결과, 에러가 일어나도 실시간으로 이를 감지하고 정정하여 차량용 온칩 버스에서 종단간 데이터 무결성을 강화하는 것을 확인하였다.

• 정보보호학회논문지
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• 제22권5호
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• pp.1069-1078
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• 2012

컴퓨터 시스템의 안전성을 위협하는 주요 취약점으로 메모리 관련 취약점이 알려져 있으며, 최근 들어 이러한 메모리 취약점을 이용한 시스템 상에서의 실제 공격 또한 증가하고 있다. 이에 따라 시스템을 보호하기 위해서 다양한 메모리 보호 메커니즘들이 연구되고 운영체제를 통해 구현되어 왔지만, 더불어 이를 우회할 수 있는 공격 기법들 또한 발전하고 있다. 특히 버퍼 오버플로우 공격은 Return to Library, Return-Oriented Programming 등의 공격 기법으로 발전되어왔으며, 최근에는 Return-Oriented Programming 공격 기법에 대한 보호 방법 등의 연구로 인해 이를 우회하는 Jump-Oriented Programming 공격 기법이 등장하였다. 따라서 본 논문에서는 메모리 관련 공격 기법 중 최근 등장한 Jump-Oriented Programming 공격 기법에 대해 살펴보고, 이에 대한 특징을 분석한다. 또한, 분석된 특징을 통한 바이너리 수준에서의 탐지 메커니즘을 제안하고, 실험을 통해 제안하는 방법이 Jump-Oriented Programming 공격에 대한 탐지가 가능함을 검증한다.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.75-84
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• 2022

The efficiency of the regional fiscal policy implementation is based on the achievement of target criteria in the formation and distribution of own financial resources of local budgets, reducing their deficit and reducing dependence on transfers. It is also relevant to compare the development of financial autonomy of regions in the course of decentralisation of fiscal relations. The study consists in the cluster analysis of the effectiveness of fiscal policy implementation in the context of 24 regions and the capital city of Kyiv (except for temporarily occupied territories) under conditions of fiscal decentralisation. Clustering of the regions of Ukraine by 18 indicators of fiscal policy implementation efficiency was carried out using Ward's minimum variance method and k-means clustering algorithm. As a result, the regions of Ukraine are grouped into 5 homogeneous clusters. For each cluster measures were developed to increase own revenues and minimize dependence on official transfers to increase the level of financial autonomy of the regions. It has been proved that clustering algorithms are an effective tool in assessing the effectiveness of fiscal policy implementation at the regional level and stimulating further expansion of financial decentralisation of regions.