• ETRI Journal
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• v.35 no.1
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• pp.80-88
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• 2013

A passive infrared or pyroelectric infrared (PIR) sensor is mainly used to sense the existence of moving objects in an indoor environment. However, in an outdoor environment, there are often outbreaks of false alarms from environmental changes and other sources. Therefore, it is difficult to provide reliable detection outdoors. In this paper, two algorithms are proposed to reduce false alarms and provide trustworthy quality to surveillance systems. We gather PIR signals outdoors, analyze the collected data, and extract the target features defined as window energy and alarm duration. Using these features, we model target and false alarms, from which we propose two target decision algorithms: window energy detection and alarm duration detection. Simulation results using real PIR signals show the performance of the proposed algorithms.

• Journal of the Korean Society of Safety
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• v.8 no.1
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• pp.6-12
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• 1993

Now it is reported that there are many companies and factories which confront to the problem of false alarm in Automatic Fire Detecting System (AFDS). Though an AFDS is a high-priced and very important device in detecting a fire. the problem degrades the reliability and utility, eventually faith. of the system. This is a research concerned about the problem of false alarm of fire detectors in an AFDS. Structure of detectors was modeled up as a general K out-of n system. and reliability characteristics including false alarm rate and missed alarm rate, are derived from it. For decision of an optimal structure of detectors. preliminary analysis on various criteria is accomplished. It is concluded that appropriate modification of a detector with plural sensors may increase the system reliability and decrease the false alarm rate.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.853-864
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• 2017

This paper proposes a false alarm rate reduction technique for detection of small targets in a terrestrial environment. CFAR algorithm is useful in homogeneous background, but it is not easy to detect targets in non-homogeneous background. In particular, when the clutter power is not significantly different from the target signal, it is difficult to detect the target due to high false alarm rate. To solve these difficulties, this study presents the false alarm rate reduction technique based on CFAR algorithm, matched filter and binary integration technique. The parameters are studied through the theoretical analysis and the validity of the proposed study is examined by the test results.

• Journal of KIISE
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• v.44 no.2
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• pp.171-178
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• 2017

In this study, we propose an automated unit test generation technique for detecting vulnerabilities of Android kernel modules. The technique automatically generates unit test drivers/stubs and unit test inputs for each function of Android kernel modules by utilizing dynamic symbolic execution. To reduce false alarms caused by function pointers and missing pre-conditions of automated unit test generation technique, we develop false alarm reduction techniques that match function pointers by utilizing static analysis and generate pre-conditions by utilizing def-use analysis. We showed that the proposed technique could detect all existing vulnerabilities in the three modules of Android kernel 3.4. Also, the false alarm reduction techniques removed 44.9% of false alarms on average.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.301-308
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• 2004

Misuse IDS is known to have an acceptable accuracy but suffers from high rates of false alarms. We show a behavior based alarm reduction with a memory-based machine learning technique. Our extended form of IBL, (XIBL) examines SNORT alarm signals if that signal is worthy sending signals to security manager. An experiment shows that there exists an apparent difference between true alarms and false alarms with respect to XIBL behavior This gives clear evidence that although an attack in the network consists of a sequence of packets, decisions over Individual packet can be used in conjunction with misuse IDS for better performance.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.669-670
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• 2008

In this paper, we present a real-time system to detect abnormal events on gas pipes, based on the signals which are observed through the audio sensors attached on them. First, features are extracted from these signals so that they are robust to noise and invariant to the distance between a sensor and a spot at which an abnormal event like an attack on the gas pipes occurs. Then, a classifier is constructed to detect abnormal events using neural networks. It is a combination of two neural network models, a Gaussian mixture model and a multi-layer perceptron, for the reduction of miss and false alarms. The former works for miss alarm prevention and the latter for false alarm prevention. The experimental result with real data from the actual gas system shows that the proposed system is effective in detecting the dangerous events in real-time with an accuracy of 92.9%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1616-1626
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• 2010

This paper will show how self-alarming EAS(Electronic Article Surveillance) system can improve its receiving performance of magnetic field signal and reduce false alarm using dual-band wireless communication. Our research improved the receiving performance and the areas of recognition of magnetic signal through the change of VLF receiving circuit and alarm transmitting method. In addition, we verified the reduction of false alarm by improvement of integrity and distance between tag and receiver through experiment. Thanks to our research, we can build the high performance and economical EAS with low false alarm on the multi gate store.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.1971-1977
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• 2001

Multipath Rayleigh fading channels for mobile radio transmission can be represented by the linear filter model, and depending on the delay path characteristics, only a selected number of taps may have significance in the receiver structure design. By using tap-selective equalization, reduction in both processing complexity and power consumption can be obtained. In this paper, we present an optimal tap selection method for a given channel model, and demonstrate the performance improvement over an existing method. We show the method performs the CFAR (Constant False Alarm Rate) detection when the noise power information is available, and derive exact expressions of the error probability for the case of noise power estimation. Using the derived formulas and simulation results, it is demonstrated that the error probability quickly approaches to the optimal performance as the number samples used for the noise power estimation increases.

• The Journal of the Acoustical Society of Korea
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• v.38 no.6
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• pp.661-669
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• 2019

High frequency active sonar is appropriate for detecting small targets such as a diver in coast environment. In case of using high frequency active sonar in shallow coastal environment, a false alarm rate is high due to clutters caused by marine biological noise, ship noise, wake, etc. In this paper, we propose an algorithm for target detection which is robust against clutter in active sonar system in shallow coastal environment. The proposed algorithm increases the rate of reduction clutter using calculation of statistical characteristics of signal and a clustering method. The algorithm is evaluated and analysed with sea trial data, as a result, that shows the rate of reducing rate of clutter of 96 % and over.

• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.107-114
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• 2012

Fire detection system is used for detection and alarm-generation of danger in case of fire. Most fire detection systems being used these days often malfunction from false positive and false negative errors. To improve detection reliability, an integrated fire detection algorithm using multi-senor information of heat, smoke and carbon monoxide detectors is suggested, then built and tested using the LabVIEW environment. Simulated using sensor measurement data offered by National Institute of Standards and Technology (NIST), possibility of reducing false positive and false negative errors is verified.