• Korean Journal of Child Studies
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• v.36 no.5
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• pp.135-153
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• 2015

The purpose of this study was to investigate false belief understanding and justification reasoning according to information of reality amongst children aged 3, 4 and 5. Children aged 3 to 5 years (N = 176) participated in this study. Each child was interviewed individually and responded to questions designed to measure his/her false belief understanding. Every child responded to the false belief task under two different information conditions of reality(reality known vs reality unknown). For more specific analysis, children's reasoning responses were also recorded. The major findings of this study are as follows. Children could understand false belief more easily under reality unknown conditions. Specifically, the influences of information conditions were crucial to 3-year-olds but not to 4- and 5-year-olds. Although 3 year olds were able to avoid the systematical errors inherent in the false belief task, they still did not understand the false belief itself. This study provides specific aspects of false belief understanding and its relevance to general changes in cognitive development.

• Journal of Information Display
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• v.2 no.2
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• pp.32-38
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• 2001

PDP(plasma display panel) represents the gray levels by the pulse number modulation technique that results in undesirable dynamic false contours on moving images. This paper proposes a LUT(Look-up table) based error diffusion algorithm for reduction of the dynamic false contours. A quantitative measure of the dynamic false contours is defined first. The measure of the dynamic false contours is calculated through simulation of every gray level combination of two consecutive frames. Based on the calculated measures, a modified gray level for a pair of gray levels of two consecutive frames is chosen to reduce the dynamic false contours. The chosen gray levels serve as contents of a gray level conversion LUT. Given a pair of gray levels of two consecutive frames, the gray level of current frame is modified based on the gray level conversion LUT. The new gray level is displayed on PDP. An error diffusion algorithm is, then, applied to compensate for the differences in the gray levels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2115-2130
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• 2022

With the development of over-the-top (OTT) services, the demand for content is increasing, and you can easily and conveniently acquire various content in the online environment. As a result, copyrighted content can be easily copied and distributed, resulting in serious copyright infringement. Some special forms of online service providers (OSP) use filtering-based technologies to protect copyrights, but illegal uploaders use methods that bypass traditional filters. Uploading with a title that bypasses the filter cannot use a similar search method to detect illegal content. In this paper, we propose a technique for profiling the Heavy Uploader by normalizing the bypassed content title and efficiently detecting illegal content. First, the word is extracted from the normalized title and converted into a bit-array to detect illegal works. This Bloom Filter method has a characteristic that there are false positives but no false negatives. The false positive rate has a trade-off relationship with processing performance. As the false positive rate increases, the processing performance increases, and when the false positive rate decreases, the processing performance increases. We increased the detection rate by directly comparing the word to the result of increasing the false positive rate of the Bloom Filter. The processing time was also as fast as when the false positive rate was increased. Afterwards, we create a function that includes information about overall piracy and identify clustering-based heavy uploaders. Analyze the behavior of heavy uploaders to find the first uploader and detect the source site.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1997-2000
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• 2003

False Positive Alert 은 IDS 가 공격이 아닌 것을 공격으로 잘못 판단하는 것이다 이러한 false Positive 는 시스템에 직접적인 피해를 주지는 않으나, 시스템 관리자가 적절한 대처를 하기 어렵게 하므로 IDS의 새로운 문제점으로 대두되고 있다. 본 논문에서는 이러한 false Positive를 줄이기 위해 IDS 에서 나오는 Alert 중 False Positive를 필터링 하는 방법에 대해 제시한다. 공격에 대한 Alert과 False Positive Alert의 시간 패턴을 각각 분석, 학습함으로써 그 후의 Alert의 False Positive 여부를 판별한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.854-860
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• 2004

The result of fingerprint matching is different as the quality or the state of input fingerprint image. We can extract the false direction information when the quality of fingerprint is degraded by the noise or the scars of the ridges. The information of the direction is very important for the elimination of the false minutia, the measurement of the ridge distance, matching, finding of cores and deltas. We need the method which can compensate or correct the false information of directions because the false directions include serious errors in the fingerprint recognition. We propose a method which can compensate or correct the false direction of fingerprint with a \alpha$-trimmed mean filter followed by LPF to reconstruct the false direction information when fingerprints are corrupted by scars.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.307-309
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• 2004

침입탐지시스템에서 발생되는 오 경보는 false positive 와 false negative 로 구분된다. false positive는 실제적인 공격은 아니지만 공격이라고 오인하여 경보를 발생시켜 시스템의 효율성을 떨어뜨리기 때문에 false positive 패턴에 대한 분석이 필요하다. 오 경보 데이터는 시간이 지남에 따라 데이터의 양뿐만 아니라 데이터 패턴의 특성 또한 변하게 된다 따라서 새로운 데이터가 추가될 때마다 오 경보 데이터의 패턴을 분석할 수 있는 도구가 필요하다. 이 논문에서는 오 경보 데이터로부터 false positive 의 패턴을 분석할 수 있는 프레임워크에 대해서 기술한다. 우리의 프레임워크는 시간이 지남에 따라 변하는 데이터의 패턴 특성을 분석할 수 있도록 하기 위해 점진적 연관규칙 기법을 적용한다. 이 프레임워크를 통해서 false positive 패턴 특성의 변화를 효율적으로 관리 할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1874-1893
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• 2012

An approach to detect abnormal activities based on reputations created individually by each node is vulnerable to a false accusation since intrusion detection in ad-hoc networks is done in a distributed and cooperative manner. Detection of false accusation is considered important because the efficiency or survivability of the network can be degraded severely if normal nodes were excluded from the network by being considered as abnormal ones in the intrusion detection process. In this paper, we propose an improved reputation-based intrusion detection technique to efficiently detect and manage false accusations in ad-hoc networks. Additionally, we execute simulations of the proposed technique to analyze its performance and feasibility to be implemented in a real environment.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.65-75
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• 2009

The development of IT technology, Internet popularity is increasing geometrically. However, as its side effect, the intrusion behaviors such as information leakage for key system and infringement of computation network etc are also increasing fast. The attack traffic detection method which is suggested in this study utilizes the Snort, traditional NIDS, filters the packet with false positive among the detected attack traffics using Nmap information. Then, it performs the secondary filtering using nessus vulnerability information and finally performs correlation analysis considering appropriateness of management system, severity of signature and security hole so that it could reduce false positive alarm message as well as minimize the errors from false positive and as a result, it raised the overall attack detection results.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.14-32
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• 2022

This study aims to examine the perception of false information and deepfakes according to the experience of being exposed to false information and deepfake images for YouTube content users. The study used the data from 'YouTube Use and False Information Exposure Experience' conducted by the Korea Press Foundation in 2018. For the statistical analysis, correspondent analysis was employed. The main results followed as: First, it was found that men who have been exposed to false information are most seriously aware of the problems caused by false information on YouTube. Second, regarding the need for regulation on deepfake images, women who have experienced exposure to deepfake images tended to agree, and women had a stronger awareness of the need for regulation due to damage to deepfake images than men. While YouTube users generally agree that regulation is necessary, it is required to educate YouTube users about the types of disinformation and deepfakes. In particular, it is considered to be desirable to create an environment for the self-regulation of the producers and distributors.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.1-5
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• 2013

CR(Cognitive Radio) technology is maximized frequency reuse using unused frequency band. Conventional cooperative spectrum sensing has fixed false alarms. so all cooperative user has equal threshold. This problem is caused degradation of detection probability. so we propose and analysis the system model that false alarm differential setting through CSI(channel state information) for resonable threshold. Simulation results show improvement of detection probability.