• Title/Summary/Keyword: False Detection

Search Result 1,207, Processing Time 0.036 seconds

APPLICATIONS OF ASYMMETRIC HYSTERESIS LOOPS IN AMORPHOUS ALLOYS

  • Jr., C.D. Graham;Shin, K-H.;Zhou, Peter Y.
    • Journal of the Korean Magnetics Society
    • /
    • v.5 no.5
    • /
    • pp.579-582
    • /
    • 1995
  • The use of amorphous magnetic alloys as tags or targets in electronic article surveillance systems such as antishoplifting desvices is briefly reviewed. Improved tags became possible with the discovery in 1988 of asymmetric magnetization reversal (AMR) in certain amorphous alloys annealed in applied field approximately equal to the earth's field. These asymmetric hysteresis loops are highly unusual, if not unique, and so greatly diminish the probability of false alarms in a detection system. furthermore, the jump field Hj, which is the coercive field in negative applied fields, can be controlled over a useful range by controlling the field applied to the sample during annealing. By applying several tags to an object, each with a different jump field, it is possible to identify the object with a numeric code that can be remotely read by nonoptical means.

  • PDF

Hybridized Decision Tree methods for Detecting Generic Attack on Ciphertext

  • Alsariera, Yazan Ahmad
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.7
    • /
    • pp.56-62
    • /
    • 2021
  • The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

Securing SCADA Systems: A Comprehensive Machine Learning Approach for Detecting Reconnaissance Attacks

  • Ezaz Aldahasi;Talal Alkharobi
    • International Journal of Computer Science & Network Security
    • /
    • v.23 no.12
    • /
    • pp.1-12
    • /
    • 2023
  • Ensuring the security of Supervisory Control and Data Acquisition (SCADA) and Industrial Control Systems (ICS) is paramount to safeguarding the reliability and safety of critical infrastructure. This paper addresses the significant threat posed by reconnaissance attacks on SCADA/ICS networks and presents an innovative methodology for enhancing their protection. The proposed approach strategically employs imbalance dataset handling techniques, ensemble methods, and feature engineering to enhance the resilience of SCADA/ICS systems. Experimentation and analysis demonstrate the compelling efficacy of our strategy, as evidenced by excellent model performance characterized by good precision, recall, and a commendably low false negative (FN). The practical utility of our approach is underscored through the evaluation of real-world SCADA/ICS datasets, showcasing superior performance compared to existing methods in a comparative analysis. Moreover, the integration of feature augmentation is revealed to significantly enhance detection capabilities. This research contributes to advancing the security posture of SCADA/ICS environments, addressing a critical imperative in the face of evolving cyber threats.

Comparative Evaluation of Intron Prediction Methods and Detection of Plant Genome Annotation Using Intron Length Distributions

  • Yang, Long;Cho, Hwan-Gue
    • Genomics & Informatics
    • /
    • v.10 no.1
    • /
    • pp.58-64
    • /
    • 2012
  • Intron prediction is an important problem of the constantly updated genome annotation. Using two model plant (rice and $Arabidopsis$) genomes, we compared two well-known intron prediction tools: the Blast-Like Alignment Tool (BLAT) and Sim4cc. The results showed that each of the tools had its own advantages and disadvantages. BLAT predicted more than 99% introns of whole genomic introns with a small number of false-positive introns. Sim4cc was successful at finding the correct introns with a false-negative rate of 1.02% to 4.85%, and it needed a longer run time than BLAT. Further, we evaluated the intron information of 10 complete plant genomes. As non-coding sequences, intron lengths are not limited by a triplet codon frame; so, intron lengths have three phases: a multiple of three bases (3n), a multiple of three bases plus one (3n + 1), and a multiple of three bases plus two (3n + 2). It was widely accepted that the percentages of the 3n, 3n + 1, and 3n + 2 introns were quite similar in genomes. Our studies showed that 80% (8/10) of species were similar in terms of the number of three phases. The percentages of 3n introns in $Ostreococcus$ $lucimarinus$ was excessive (47.7%), while in $Ostreococcus$ $tauri$, it was deficient (29.1%). This discrepancy could have been the result of errors in intron prediction. It is suggested that a three-phase evaluation is a fast and effective method of detecting intron annotation problems.

Improvement and Evaluation of Automatic Quality Check Algorithm for Particulate Matter (PM10) by Analysis of Instrument Status Code (부유분진(PM10) 측정기 상태 코드 분석을 통한 자동 품질검사 알고리즘 개선 및 평가)

  • Kim, Mi-Gyeong;Park, Young-San;Ryoo, Sang-Boom;Cho, Jeong Hoon
    • Atmosphere
    • /
    • v.29 no.4
    • /
    • pp.501-509
    • /
    • 2019
  • Asian Dust is a meteorological phenomenon that sand particles are raised from the arid and semi-arid regions-Taklamakan Desert, Gobi Desert and Inner Mongolia in China-and transported by westerlies and deposited on the surface. Asian dust results in a negative effect on human health as well as environmental, social and economic aspects. For monitoring of Asian Dust, Korea Meteorological Administration operates 29 stations using a continuous ambient particulate monitor. Kim et al. (2016) developed an automatic quality check (AQC) algorithm for objective and systematic quality check of observed PM10 concentration and evaluated AQC with results of a manual quality check (MQC). The results showed the AQC algorithm could detect abnormal observations efficiently but it also presented a large number of false alarms which result from valid error check. To complement the deficiency of AQC and to develop an AQC system which can be applied in real-time, AQC has been modulated. Based on the analysis of instrument status codes, valid error check process was revised and 6 status codes were further considered as normal. Also, time continuity check and spike check were modified so that posterior data was not referred at inspection time. Two-year observed PM10 concentration data and corresponding MQC results were used to evaluate the modulated AQC compared to the original AQC algorithm. The results showed a false alarm ratio decreased from 0.44 to 0.09 and the accuracy and the probability of detection were conserved well in spite of the exclusion of posterior data at inspection time.

The Realization of Panoramic Infrared Image Enhancement and Warning System for Small Target Detection (소형 표적 탐지를 위한 파노라믹 적외선 영상 향상 장치 및 경보시스템 구현)

  • Kim Ki Hong;Kim Ju Young;Jung Tae Yeon;Jeon Byung Gyoon;Lee Eui Hyuk;Kim Duk Gyoo
    • Journal of Korea Multimedia Society
    • /
    • v.8 no.1
    • /
    • pp.46-55
    • /
    • 2005
  • In this paper, we realize the panoramic infrared warning system to detect the small threaten object and propose the infrared image enhancement method to improve the warning ability of this system. This system composes of the sense head unit, the signal processing unit, and so on. In the proposed system, the sense head unit acquires the panoramic IR image with 360 degree field of view(FOV) by rotating the thermal sensor. The signal processing unit divides panoramic image into four sub-images with 90 degree FOV and computes the adaptive plateau value by using statistical characteristics of each subimage. Then the histogram equalization is performed for each subimage by using the adaptive plateau value. We realize the signal Processing unit by using the DSP and FPGA to perform the proposed method in real time. Experimental results show that the proposed method has better discrimination and lower false alarm rate than the conventional methods in this warning system.

  • PDF

The advantage of topographic prominence-adopted filter for the detection of short-latency spikes of retinal ganglion cells

  • Ahn, Jungryul;Choi, Myoung-Hwan;Kim, Kwangsoo;Senok, Solomon S.;Cho, Dong-il Dan;Koo, Kyo-in;Goo, Yongsook
    • The Korean Journal of Physiology and Pharmacology
    • /
    • v.21 no.5
    • /
    • pp.555-563
    • /
    • 2017
  • Electrical stimulation through retinal prosthesis elicits both short and long-latency retinal ganglion cell (RGC) spikes. Because the short-latency RGC spike is usually obscured by electrical stimulus artifact, it is very important to isolate spike from stimulus artifact. Previously, we showed that topographic prominence (TP) discriminator based algorithm is valid and useful for artifact subtraction. In this study, we compared the performance of forward backward (FB) filter only vs. TP-adopted FB filter for artifact subtraction. From the extracted retinae of rd1 mice, we recorded RGC spikes with $8{\times}8$ multielectrode array (MEA). The recorded signals were classified into four groups by distances between the stimulation and recording electrodes on MEA (200-400, 400-600, 600-800, $800-1000{\mu}m$). Fifty cathodic phase-$1^{st}$ biphasic current pulses (duration $500{\mu}s$, intensity 5, 10, 20, 30, 40, 50, $60{\mu}A$) were applied at every 1 sec. We compared false positive error and false negative error in FB filter and TP-adopted FB filter. By implementing TP-adopted FB filter, short-latency spike can be detected better regarding sensitivity and specificity for detecting spikes regardless of the strength of stimulus and the distance between stimulus and recording electrodes.

Addressing Mobile Agent Security through Agent Collaboration

  • Jean, Evens;Jiao, Yu;Hurson, Ali-R.
    • Journal of Information Processing Systems
    • /
    • v.3 no.2
    • /
    • pp.43-53
    • /
    • 2007
  • The use of agent paradigm in today's applications is hampered by the security concerns of agents and hosts alike. The agents require the presence of a secure and trusted execution environment; while hosts aim at preventing the execution of potentially malicious code. In general, hosts support the migration of agents through the provision of an agent server and managing the activities of arriving agents on the host. Numerous studies have been conducted to address the security concerns present in the mobile agent paradigm with a strong focus on the theoretical aspect of the problem. Various proposals in Intrusion Detection Systems aim at securing hosts in traditional client-server execution environments. The use of such proposals to address the security of agent hosts is not desirable since migrating agents typically execute on hosts as a separate thread of the agent server process. Agent servers are open to the execution of virtually any migrating agent; thus the intent or tasks of such agents cannot be known a priori. It is also conceivable that migrating agents may wish to hide their intentions from agent servers. In light of these observations, this work attempts to bridge the gap from theory to practice by analyzing the security mechanisms available in Aglet. We lay the foundation for implementation of application specific protocols dotted with access control, secured communication and ability to detect tampering of agent data. As agents exists in a distributed environment, our proposal also introduces a novel security framework to address the security concerns of hosts through collaboration and pattern matching even in the presence of differing views of the system. The introduced framework has been implemented on the Aglet platform and evaluated in terms of accuracy, false positive, and false negative rates along with its performance strain on the system.

Edge-Adaptive Color Interpolation for CCD Image Sensor

  • Heo, Bong-Su;Hong, Hun-Seop;Gang, Mun-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.39 no.1
    • /
    • pp.1-8
    • /
    • 2002
  • The color interpolation scheme can play an important role in overcoming the physical limitation of the CCD image sensor and in increasing the resolution of color signals, while most conventional approaches result in blurred edges and false color artifacts. In this paper, we have proposed an improved edge-adaptive color interpolation scheme for a progressive scan CCD image sensor with RGB color filter array The edge indicator function proposed utilizes not only the within-channel correlation but also the cross-channel correlation, and reflects the edge characteristics of an image adaptively. The color components unavailable for at each channel are interpolated along the edge direction, not across the edges, so that aliasing artifacts are supressed. Furthermore, we eliminated false color artifacts resulting from the color image formation model in the edge-adaptive color interpolation scheme by adopting the switching algorithm based on the color edge detection. Simulation results of the proposed algorithm indicate that the improved edge-adaptive color interpolation scheme produces quantitatively better and visually more pleasing results than conventional approaches.

An Improved Method for Detecting Caption in image using DCT-coefficient and Transition-map Analysis (DCT계수와 천이지도 분석을 이용한 개선된 영상 내 자막영역 검출방법)

  • An, Kwon-Jae;Joo, Sung-Il;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of the Korea Society of Computer and Information
    • /
    • v.16 no.4
    • /
    • pp.61-71
    • /
    • 2011
  • In this paper, we proposed the method for detecting text region on image using DCT-coefficient and transition-map analysis. The detecting rate of traditional method for detecting text region using DCT-coefficient analysis is high, but false positive detecting rate also is high and the method using transition-map often reject true text region in step of verification because of sticky threshold. To overcome these problems, we generated PTRmap(Promising Text Region map) through DCT-coefficient analysis and applied PTRmap to method for detecting text region using transition map. As the result, the false positive detecting rate decreased as compared with the method using DCT-coefficient analysis, and the detecting rate increased as compared with the method using transition map.