scholarly journals An Improved Chinese String Comparator for Bloom Filter Based Privacy-Preserving Record Linkage

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1091
Author(s):  
Siqi Sun ◽  
Yining Qian ◽  
Ruoshi Zhang ◽  
Yanqi Wang ◽  
Xinran Li
Keyword(s):  
Record Linkage ◽  
False Positive ◽  
Personal Information ◽  
Chinese Language ◽  
False Positive Rate ◽  
Bloom Filter ◽  
Privacy Preserving ◽  
Computational Time ◽  
Positive Rate ◽  
Language Environment

With the development of information technology, it has become a popular topic to share data from multiple sources without privacy disclosure problems. Privacy-preserving record linkage (PPRL) can link the data that truly matches and does not disclose personal information. In the existing studies, the techniques of PPRL have mostly been studied based on the alphabetic language, which is much different from the Chinese language environment. In this paper, Chinese characters (identification fields in record pairs) are encoded into strings composed of letters and numbers by using the SoundShape code according to their shapes and pronunciations. Then, the SoundShape codes are encrypted by Bloom filter, and the similarity of encrypted fields is calculated by Dice similarity. In this method, the false positive rate of Bloom filter and different proportions of sound code and shape code are considered. Finally, we performed the above methods on the syntheticdatasets, and compared the precision, recall, F1-score and computational time with different values of false positive rate and proportion. The results showed that our method for PPRL in Chinese language environment improved the quality of the classification results and outperformed others with a relatively low additional cost of computation.

scholarly journals Bloom Filter-Based Secure Data Forwarding in Large-Scale Cyber-Physical Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Siyu Lin ◽  
Hao Wu
Keyword(s):  
False Positive ◽  
Large Scale ◽  
False Positive Rate ◽  
Bloom Filter ◽  
Cyber Physical Systems ◽  
Security Requirements ◽  
Data Forwarding ◽  
Physical Systems ◽  
Secure Data ◽  
Positive Rate

Cyber-physical systems (CPSs) connect with the physical world via communication networks, which significantly increases security risks of CPSs. To secure the sensitive data, secure forwarding is an essential component of CPSs. However, CPSs require high dimensional multiattribute and multilevel security requirements due to the significantly increased system scale and diversity, and hence impose high demand on the secure forwarding information query and storage. To tackle these challenges, we propose a practical secure data forwarding scheme for CPSs. Considering the limited storage capability and computational power of entities, we adopt bloom filter to store the secure forwarding information for each entity, which can achieve well balance between the storage consumption and query delay. Furthermore, a novel link-based bloom filter construction method is designed to reduce false positive rate during bloom filter construction. Finally, the effects of false positive rate on the performance of bloom filter-based secure forwarding with different routing policies are discussed.

A new analysis of the false positive rate of a Bloom filter

2010 ◽  
Vol 110 (21) ◽  
pp. 944-949 ◽  
Author(s):  
Ken Christensen ◽  
Allen Roginsky ◽  
Miguel Jimeno
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Bloom Filter ◽  
Positive Rate

scholarly journals An Automatic Traffic Sign Detection and Recognition System Based on Colour Segmentation, Shape Matching, and SVM

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Safat B. Wali ◽  
Mahammad A. Hannan ◽  
Aini Hussain ◽  
Salina A. Samad
Keyword(s):  
False Positive ◽  
Shape Matching ◽  
False Positive Rate ◽  
System Stability ◽  
Computational Time ◽  
Support Vector ◽  
Traffic Signs ◽  
Positive Rate ◽  
Colour Segmentation ◽  
Detection And Recognition

The main objective of this study is to develop an efficient TSDR system which contains an enriched dataset of Malaysian traffic signs. The developed technique is invariant in variable lighting, rotation, translation, and viewing angle and has a low computational time with low false positive rate. The development of the system has three working stages: image preprocessing, detection, and recognition. The system demonstration using a RGB colour segmentation and shape matching followed by support vector machine (SVM) classifier led to promising results with respect to the accuracy of 95.71%, false positive rate (0.9%), and processing time (0.43 s). The area under the receiver operating characteristic (ROC) curves was introduced to statistically evaluate the recognition performance. The accuracy of the developed system is relatively high and the computational time is relatively low which will be helpful for classifying traffic signs especially on high ways around Malaysia. The low false positive rate will increase the system stability and reliability on real-time application.

scholarly journals The Research of Technology of Bloom Filter Realization in Hardware

2012 ◽  
Vol 6-7 ◽  
pp. 790-795
Author(s):  
Teng Fei Guo ◽  
Jian Biao Mao ◽  
Zhi Gang Sun
Keyword(s):  
False Positive ◽  
Hardware Implementation ◽  
False Positive Rate ◽  
Hardware Design ◽  
Bloom Filter ◽  
False Positives ◽  
Implementation Framework ◽  
Positive Rate ◽  
Efficient Data

Bloom filter is a space-efficient data with a certain probability of false positive . We present a reusable hardware implementation framework, define a module interface to provide users with a customize module, and introduce the constraints of hardware resources in the analysis of false positive rate against the traditional Bloom filter hardware design and analysis of the Bloom filter false positives. Finally, we make verification and analysis of our design combined with the the NetMagic platform.

scholarly journals Locality Sensitive Hardware Signature Variants for Hardware Transactional Memory

2021 ◽  
Author(s):  
sangeetha r ◽  
Satyanarayana Vollala ◽  
Ramasubramanian N
Keyword(s):  
False Positive ◽  
Transactional Memory ◽  
False Positive Rate ◽  
False Negative ◽  
Bloom Filter ◽  
Conflict Detection ◽  
Bloom Filters ◽  
Positive Rate ◽  
Memory Conflicts ◽  
Probabilistic Data Structure

Abstract Lock based techniques have its own limitations like priority inversion, convoying, and deadlock. Lock free techniques overcome those mentioned limitations. Transactional memory (TM) is one leading lock free technique used in recent multi core processors like Intel Haswell and IBM BlueGene/Q. TM has to do data versioning and conflict detection. For conflict detection probabilistic data structure called Bloom Filters are used. Bloom filter based hardware signatures are used in TM. In TM shared memory conflicts like RAW, WAR, and WAW hazards are handled by Bloom Filter (BF). Hardware signatures store memory addresses in hashed form on Bloom filters. Bloom filters are easy to use, performance efficient data structures lead to false positive but never support false negative. Locality sensitive hardware signatures reduce filter occupancy by sharing bits for the contiguous memory addresses, in turn reduces the false positive rate. This paper implements existing H3 – HS and LS – HS proposed by Ricardo Quislant et al. [13]. Also this paper proposes RS – HS, CS – HS, and RO – HS. RO – HS equally spreads addresses among bloom filters thereby reduces filter occupancy. In turn reduced filter occupancy leads to better False Positive 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%.

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