scholarly journals Application of Trusted Computing Technology in Active Defense of Smart Substation

2021 ◽  
Vol 2108 (1) ◽  
pp. 012065
Author(s):  
Liandong Chen ◽  
Tao Yang ◽  
Gang Li ◽  
Xin Liu ◽  
Ning Lu ◽  
...  
Keyword(s):  
Trusted Computing ◽  
False Positive Rate ◽  
Development Stage ◽  
Computing Technology ◽  
Security Systems ◽  
Security Vulnerabilities ◽  
Active Defense ◽  
Whole Process ◽  
Positive Rate ◽  
Low Efficiency

Abstract Nowadays, most security systems mainly use firewall, intrusion detection, virus killing and other technologies to defend against external attacks. This passive defense mode has low efficiency and high false positive rate, and active defense technology can solve these problems to the greatest extent. At present, the intelligent substation is in the development stage with weak security. After a large number of terminals are connected, although the operation efficiency of the whole station is improved, it also brings more risks. This paper takes the access security of terminal equipment in intelligent substation as the research object. By mining the security vulnerabilities of substation, an active defense method based on trusted computing is proposed, the applicability and efficiency of trusted computing technology in the field of substation active defense are proved and the effectiveness of the method is verified to realize the trust guarantee of the whole process of terminal access to intelligent substation.

scholarly journals IoT Dataset Validation Using Machine Learning Techniques for Traffic Anomaly Detection

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2857
Author(s):  
Laura Vigoya ◽  
Diego Fernandez ◽  
Victor Carneiro ◽  
Francisco Nóvoa
Keyword(s):  
Machine Learning ◽  
Anomaly Detection ◽  
False Positive Rate ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
High Detection Rate ◽  
Security Vulnerabilities ◽  
Smart Systems ◽  
Learning Techniques ◽  
Positive Rate

With advancements in engineering and science, the application of smart systems is increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT restricted power and computing devices also raise concerns about security vulnerabilities. Machine learning-based techniques have recently gained credibility in a successful application for the detection of network anomalies, including IoT networks. However, machine learning techniques cannot work without representative data. Given the scarcity of IoT datasets, the DAD emerged as an instrument for knowing the behavior of dedicated IoT-MQTT networks. This paper aims to validate the DAD dataset by applying Logistic Regression, Naive Bayes, Random Forest, AdaBoost, and Support Vector Machine to detect traffic anomalies in IoT. To obtain the best results, techniques for handling unbalanced data, feature selection, and grid search for hyperparameter optimization have been used. The experimental results show that the proposed dataset can achieve a high detection rate in all the experiments, providing the best mean accuracy of 0.99 for the tree-based models, with a low false-positive rate, ensuring effective anomaly detection.

scholarly journals Advanced Principal Component Analysis for Analysis of Optimized Credit Card Fraud Detection

2019 ◽  
Vol 8 (11) ◽  
pp. 318-322
Keyword(s):  
Principal Component Analysis ◽  
Credit Card ◽  
Detection System ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Principal Component ◽  
Component Analysis ◽  
Security Systems ◽  
Positive Rate

The information has turned out to be increasingly more imperative to people, associations, and organizations, and thusly, shielding this delicate information in social databases has turned into a basic issue. In any case, in spite of customary security systems, assaults coordinated to databases still happen. In this way, an intrusion detection system (IDS) explicitly for the database that can give security from all conceivable malignant clients is important. In this paper, we present the Principal Component Analysis (PCA) technique with weighted voting in favor of the assignment of inconsistency location. PCA is a diagram based procedure reasonable for demonstrating bunching questions, and weighted casting a ballot improves its capacities by adjusting the casting a ballot effect of each tree. Trials demonstrate that RF with weighted casting a ballot shows a progressively predominant presentation consistency, just as better blunder rates with an expanding number of trees, contrasted with traditional grouping approaches. Besides, it outflanks all other best in class information mining calculations as far as false positive rate and false negative rate.

Improving diagnosis of acute appendicitis with atypical findings by Tc-99m HMPAO leukocyte scan

2002 ◽  
Vol 41 (01) ◽  
pp. 37-41 ◽  
Author(s):  
S. Shung-Shung ◽  
S. Yu-Chien ◽  
Y. Mei-Due ◽  
W. Hwei-Chung ◽  
A. Kao
Keyword(s):  
Acute Appendicitis ◽  
False Positive ◽  
False Positive Rate ◽  
Accurate Method ◽  
Clinical Findings ◽  
Pathological Findings ◽  
Lower Quadrant ◽  
Predictive Values ◽  
Positive Rate

Summary Aim: Even with careful observation, the overall false-positive rate of laparotomy remains 10-15% when acute appendicitis was suspected. Therefore, the clinical efficacy of Tc-99m HMPAO labeled leukocyte (TC-WBC) scan for the diagnosis of acute appendicitis in patients presenting with atypical clinical findings is assessed. Patients and Methods: Eighty patients presenting with acute abdominal pain and possible acute appendicitis but atypical findings were included in this study. After intravenous injection of TC-WBC, serial anterior abdominal/pelvic images at 30, 60, 120 and 240 min with 800k counts were obtained with a gamma camera. Any abnormal localization of radioactivity in the right lower quadrant of the abdomen, equal to or greater than bone marrow activity, was considered as a positive scan. Results: 36 out of 49 patients showing positive TC-WBC scans received appendectomy. They all proved to have positive pathological findings. Five positive TC-WBC were not related to acute appendicitis, because of other pathological lesions. Eight patients were not operated and clinical follow-up after one month revealed no acute abdominal condition. Three of 31 patients with negative TC-WBC scans received appendectomy. They also presented positive pathological findings. The remaining 28 patients did not receive operations and revealed no evidence of appendicitis after at least one month of follow-up. The overall sensitivity, specificity, accuracy, positive and negative predictive values for TC-WBC scan to diagnose acute appendicitis were 92, 78, 86, 82, and 90%, respectively. Conclusion: TC-WBC scan provides a rapid and highly accurate method for the diagnosis of acute appendicitis in patients with equivocal clinical examination. It proved useful in reducing the false-positive rate of laparotomy and shortens the time necessary for clinical observation.

Predicting Fetal Chromosome Anomalies in the First Trimester Using Pregnancy Associated Plasma Protein-A: A Comparison of Statistical Methods

1993 ◽  
Vol 32 (02) ◽  
pp. 175-179 ◽  
Author(s):  
B. Brambati ◽  
T. Chard ◽  
J. G. Grudzinskas ◽  
M. C. M. Macintosh
Keyword(s):  
Logistic Regression ◽  
General Population ◽  
Likelihood Ratio ◽  
False Positive ◽  
False Positive Rate ◽  
Ratio Method ◽  
Detection Rates ◽  
Gaussian Distributions ◽  
Positive Rate ◽  
Likelihood Ratio Method

Abstract:The analysis of the clinical efficiency of a biochemical parameter in the prediction of chromosome anomalies is described, using a database of 475 cases including 30 abnormalities. A comparison was made of two different approaches to the statistical analysis: the use of Gaussian frequency distributions and likelihood ratios, and logistic regression. Both methods computed that for a 5% false-positive rate approximately 60% of anomalies are detected on the basis of maternal age and serum PAPP-A. The logistic regression analysis is appropriate where the outcome variable (chromosome anomaly) is binary and the detection rates refer to the original data only. The likelihood ratio method is used to predict the outcome in the general population. The latter method depends on the data or some transformation of the data fitting a known frequency distribution (Gaussian in this case). The precision of the predicted detection rates is limited by the small sample of abnormals (30 cases). Varying the means and standard deviations (to the limits of their 95% confidence intervals) of the fitted log Gaussian distributions resulted in a detection rate varying between 42% and 79% for a 5% false-positive rate. Thus, although the likelihood ratio method is potentially the better method in determining the usefulness of a test in the general population, larger numbers of abnormal cases are required to stabilise the means and standard deviations of the fitted log Gaussian distributions.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

Forms, Importance, and Ineffability of Factor Interactions to Define Personality Disorders: Comment on Lilienfeld et al. (2019)

2019 ◽  
Author(s):  
Stephen D Benning ◽  
Edward Smith
Keyword(s):  
Personality Disorders ◽  
False Positive Rate ◽  
Empirical Work ◽  
Design Studies ◽  
Linear Threshold ◽  
Positive Rate ◽  
Saturation Effects ◽  
Factor Interactions ◽  
Main Effects ◽  
Criterion Variables

The emergent interpersonal syndrome (EIS) approach conceptualizes personality disorders as the interaction among their constituent traits to predict important criterion variables. We detail the difficulties we have experienced finding such interactive predictors in our empirical work on psychopathy, even when using uncorrelated traits that maximize power. Rather than explaining a large absolute proportion of variance in interpersonal outcomes, EIS interactions might explain small amounts of variance relative to the main effects of each trait. Indeed, these interactions may necessitate samples of almost 1,000 observations for 80% power and a false positive rate of .05. EIS models must describe which specific traits’ interactions constitute a particular EIS, as effect sizes appear to diminish as higher-order trait interactions are analyzed. Considering whether EIS interactions are ordinal with non-crossing slopes, disordinal with crossing slopes, or entail non-linear threshold or saturation effects may help researchers design studies, sampling strategies, and analyses to model their expected effects efficiently.

scholarly journals PRATD: A Phased Remote Access Trojan Detection Method with Double-Sided Features

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1894
Author(s):  
Chun Guo ◽  
Zihua Song ◽  
Yuan Ping ◽  
Guowei Shen ◽  
Yuhei Cui ◽  
...  
Keyword(s):  
False Positive ◽  
Detection Method ◽  
False Positive Rate ◽  
True Positive Rate ◽  
Remote Access ◽  
Detection Methods ◽  
Security Threats ◽  
True Positive ◽  
Trojan Detection ◽  
Positive Rate

Remote Access Trojan (RAT) is one of the most terrible security threats that organizations face today. At present, two major RAT detection methods are host-based and network-based detection methods. To complement one another’s strengths, this article proposes a phased RATs detection method by combining double-side features (PRATD). In PRATD, both host-side and network-side features are combined to build detection models, which is conducive to distinguishing the RATs from benign programs because that the RATs not only generate traffic on the network but also leave traces on the host at run time. Besides, PRATD trains two different detection models for the two runtime states of RATs for improving the True Positive Rate (TPR). The experiments on the network and host records collected from five kinds of benign programs and 20 famous RATs show that PRATD can effectively detect RATs, it can achieve a TPR as high as 93.609% with a False Positive Rate (FPR) as low as 0.407% for the known RATs, a TPR 81.928% and FPR 0.185% for the unknown RATs, which suggests it is a competitive candidate for RAT detection.

Ascertaining an efficient eligibility cut-off for extended Medicare items for eating disorders

2021 ◽  
pp. 103985622110286
Author(s):  
Tracey Wade ◽  
Jamie-Lee Pennesi ◽  
Yuan Zhou
Keyword(s):  
Eating Disorders ◽  
Eating Disorder ◽  
False Positive Rate ◽  
Area Under The Curve ◽  
Rate Sensitivity ◽  
True Positive Rate ◽  
Eating Disorder Examination Questionnaire ◽  
Eating Disorder Examination ◽  
Positive Rate ◽  
The Relationship

Objective: Currently eligibility for expanded Medicare items for eating disorders (excluding anorexia nervosa) require a score ⩾ 3 on the 22-item Eating Disorder Examination-Questionnaire (EDE-Q). We compared these EDE-Q “cases” with continuous scores on a validated 7-item version of the EDE-Q (EDE-Q7) to identify an EDE-Q7 cut-off commensurate to 3 on the EDE-Q. Methods: We utilised EDE-Q scores of female university students ( N = 337) at risk of developing an eating disorder. We used a receiver operating characteristic (ROC) curve to assess the relationship between the true-positive rate (sensitivity) and the false-positive rate (1-specificity) of cases ⩾ 3. Results: The area under the curve showed outstanding discrimination of 0.94 (95% CI: .92–.97). We examined two specific cut-off points on the EDE-Q7, which included 100% and 87% of true cases, respectively. Conclusion: Given the EDE-Q cut-off for Medicare is used in conjunction with other criteria, we suggest using the more permissive EDE-Q7 cut-off (⩾2.5) to replace use of the EDE-Q cut-off (⩾3) in eligibility assessments.

Evidence for Age-Adjusted D-Dimer to Rule out Pulmonary Embolism: An Institutional Study

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S5-S5
Author(s):  
Ridin Balakrishnan ◽  
Daniel Casa ◽  
Morayma Reyes Gil
Keyword(s):  
Pulmonary Embolism ◽  
False Positive ◽  
False Positive Rate ◽  
Moderate Risk ◽  
Older Population ◽  
Statistical Measures ◽  
Positive Rate ◽  
Risk Patients ◽  
D Dimer ◽  
Rule Out

Abstract The diagnostic approach for ruling out suspected acute pulmonary embolism (PE) in the ED setting includes several tests: ultrasound, plasma d-dimer assays, ventilation-perfusion scans and computed tomography pulmonary angiography (CTPA). Importantly, a pretest probability scoring algorithm is highly recommended to triage high risk cases while also preventing unnecessary testing and harm to low/moderate risk patients. The d-dimer assay (both ELISA and immunoturbidometric) has been shown to be extremely sensitive to rule out PE in conjunction with clinical probability. In particularly, d-dimer testing is recommended for low/moderate risk patients, in whom a negative d-dimer essentially rules out PE sparing these patients from CTPA radiation exposure, longer hospital stay and anticoagulation. However, an unspecific increase in fibrin-degradation related products has been seen with increase in age, resulting in higher false positive rate in the older population. This study analyzed patient visits to the ED of a large academic institution for five years and looked at the relationship between d-dimer values, age and CTPA results to better understand the value of age-adjusted d-dimer cut-offs in ruling out PE in the older population. A total of 7660 ED visits had a CTPA done to rule out PE; out of which 1875 cases had a d-dimer done in conjunction with the CT and 5875 had only CTPA done. Out of the 1875 cases, 1591 had positive d-dimer results (>0.50 µg/ml (FEU)), of which 910 (57%) were from patients older than or equal to fifty years of age. In these older patients, 779 (86%) had a negative CT result. The following were the statistical measures of the d-dimer test before adjusting for age: sensitivity (98%), specificity (12%); negative predictive value (98%) and false positive rate (88%). After adjusting for age in people older than 50 years (d-dimer cut off = age/100), 138 patients eventually turned out to be d-dimer negative and every case but four had a CT result that was also negative for a PE. The four cases included two non-diagnostic results and two with subacute/chronic/subsegmental PE on imaging. None of these four patients were prescribed anticoagulation. The statistical measures of the d-dimer test after adjusting for age showed: sensitivity (96%), specificity (20%); negative predictive value (98%) and a decrease in the false positive rate (80%). Therefore, imaging could have been potentially avoided in 138/779 (18%) of the patients who were part of this older population and had eventual negative or not clinically significant findings on CTPA if age-adjusted d-dimers were used. This data very strongly advocates for the clinical usefulness of an age-adjusted cut-off of d-dimer to rule out PE.

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