Game Theory Based False Negative Probability of Embedded Watermark Under Unintentional and Steganalysis Attacks

Steganalysis attack is to statistically estimate the embedded watermark in the watermarked multimedia,and the estimated watermark may be destroyed by the attacker.The existing methods of false negative probability,however,do not consider the influence of steganalysis attack.This paper proposed the game theory based false negative probability to estimate the impacts of steganalysis attack,as well as unintentional attack.Specifically,game theory was used to model the collision between the embedment and steganalysis attack,and derive the optimal building embedding/attacking strategy.Such optimal playing strategies devote to calculating the attacker destructed watermark,used for calculation of the game theory based false negative probability.The experimental results show that watermark detection reliability measured using our proposed method,in comparison,can better reflect the real scenario in which the embedded watermark undergoes unintentional attack and the attacker using steganalysis attack.This paper provides a foundation for investigating countermeasures of digital watermarking community against steganalysis attack.

False Negative Sample Detection for Graph Contrastive Learning

Recently,self-supervised learning has shown great potential in Graph Neural Networks (GNNs) through contrastive learning,which aims to learn discriminative features for each node without label information. The key to graph contrastive learning is data augmentation. The anchor node regards its augmented samples as positive samples,and the rest of the samples are regarded as negative samples,some of which may be positive samples. We call these mislabeled samples as “false negative” samples,which will seriously affect the final learning effect. Since such semantically similar samples are ubiquitous in the graph,the problem of false negative samples is very significant. To address this issue,the paper proposes a novel model,False negative sample Detection for Graph Contrastive Learning (FD4GCL),which uses attribute and structure-aware to detect false negative samples. Experimental results on seven datasets show that FD4GCL outperforms the state-of-the-art baselines and even exceeds several supervised methods.

Discrimination of False Negative Results in RT-PCR Detection of SARS-CoV-2 RNAs in Clinical Specimens by Using an Internal Reference

Reverse transcription-polymerase chain reaction(RT-PCR)is an essential method for specific diagnosis of SARS-CoV-2 infection.Unfortunately,false negative test results are often reported.In this study,we attempted to determine the principal causes leading to false negative results of RT-PCR detection of SARS-CoV-2 RNAs in respiratory tract specimens.Multiple sputum and throat swab specimens from 161 confirmed COVID-19 patients were tested with a commercialfluorescent RT-PCR kit targeting the ORF1 ab and N regions of SARS-CoV-2 genome.The RNA level of a cellular housekeeping gene ribonuclease P/MRP subunit p30(RPP30)in these specimens was also assessed by RT-PCR.Data for a total of 1052 samples were retrospectively re-analyzed and a strong association between positive results in SARS-CoV-2 RNA tests and high level of RPP30 RNA in respiratory tract specimens was revealed.By using the ROC-AUC analysis,we identified Ct cutoff values for RPP30 RT-PCR which predicted false negative results for SARS-CoV-2 RT-PCR with high sensitivity(95.03%–95.26%)and specificity(83.72%–98.55%)for respective combination of specimen type and ampli-fication reaction.Using these Ct cutoff values,false negative results could be reliably identified.Therefore,the presence of cellular materials,likely infected host cells,are essential for correct SARS-CoV-2 RNA detection by RT-PCR in patient specimens.RPP30 could serve as an indicator for cellular content,or a surrogate indicator for specimen quality.In addition,our results demonstrated that false negativity accounted for a vast majority of contradicting results in SARS-CoV-2 RNA test by RT-PCR.

Benchmarking Approach to Compare Web Applications Static Analysis Tools Detecting OWASP Top Ten Security Vulnerabilities

To detect security vulnerabilities in a web application,the security analyst must choose the best performance Security Analysis Static Tool(SAST)in terms of discovering the greatest number of security vulnerabilities as possible.To compare static analysis tools for web applications,an adapted benchmark to the vulnerability categories included in the known standard Open Web Application Security Project(OWASP)Top Ten project is required.The information of the security effectiveness of a commercial static analysis tool is not usually a publicly accessible research and the state of the art on static security tool analyzers shows that the different design and implementation of those tools has different effectiveness rates in terms of security performance.Given the significant cost of commercial tools,this paper studies the performance of seven static tools using a new methodology proposal and a new benchmark designed for vulnerability categories included in the known standard OWASP Top Ten project.Thus,the practitioners will have more precise information to select the best tool using a benchmark adapted to the last versions of OWASP Top Ten project.The results of this work have been obtaining using widely acceptable metrics to classify them according to three different degree of web application criticality.

Analysis of Pesticide Residues in Vegetables by Enzyme Inhibition Colorimetric Kit

[Objectives]The paper was to understand the detection effect of commercial enzyme inhibition colorimetric kit.[Methods]Six brands of kits were used to detect pesticide residues in vegetables.The detection results were compared with those of 50 kinds of organophosphorus pesticides and 10 kinds of carbamate pesticides detected by chromatography and mass spectrometry.According to different thresholds,the test results of different kits were evaluated,and the false positive rate,false negative rate and coincidence rate of each kit were obtained.The test results of commercial enzyme inhibition colorimetric kits were compared and analyzed.[Results]The detection effect of kit D was the best among the 6 brands of kits,and the coincidence rate was the highest under the 7 thresholds.There was a certain relationship between the detection effect of commercial enzyme inhibition colorimetric kit and the determination threshold of positive samples.The false positive rate decreased with the increase of determination threshold,and the false negative rate increased with the increase of determination threshold,but the coincidence rate with chromatography and mass spectrometry can not reach 100%.When the threshold was set to 20%,the effect was the best.The coincidence rate of 3 brands of kits with the results of chromatography and mass spectrometry was the highest,and none of the 6 kits involved in the comparison had the lowest coincidence rate under this threshold.[Conclusions]It is suggested to modify the threshold values in national standard and trade standard.

Positive reverse transcription-polymerase chain reaction assay results in patients recovered from COVID-19: Report of two cases

BACKGROUND Coronavirus disease 2019(COVID-19)has spread around the globe.On February 28,2020,the World Health Organization adjusted the risk of spread and impact of COVID-19 to“very high”at the global level.Studies have mainly focused on the etiology,epidemiology,and treatment of COVID-19 to limit further spread and the negative impact of the disease,while less attention has been devoted to the follow-up and reexamination of patients who recovered from COVID-19 or were released from quarantine.CASE SUMMARY This study reports two cases where patients who had negative reverse transcription-polymerase chain reaction(RT-PCR)test results and met the criteria for discharge subsequently had positive RT-PCR test results.The clinical manifestations and computed tomography(CT)findings of these patients were examined.The conversion of RT-PCR test results in these two patients may be related to false-negative and false-positive outcomes of the test.CT images helped track improvement of pulmonary lesions.CONCLUSION The timing of discharge of COVID-19 patients should be determined by comprehensive analysis of CT images and RT-PCR test results.

An early recognition algorithm for BitTorrent traffic based on improved K-means

In response to the deficiencies of BitTorrent, the concept of density radius was proposed, and the distance from the maximum point of radius density to cluster center as a cluster radius was taken to solve the too large cluster radius resulted from the discrete points and to reduce the false positive rate of early recognition algorithms. Simulation results show that in the actual network environment, the improved algorithm, compared with K-means, will reduce the false positive rate of early identification algorithm from 6.3% to 0.9% and has a higher operational efficiency.

Prevalence of Plasmodium falciparum isolates lacking the histidine rich protein 2 gene among symptomatic malaria patients in Kwilu Provinee of the Democratic Republic of Congo

Background:Malaria rapid diagnostic tests have become a primary and critical tool for malaria diagnosis in malariaendemic countries where Plasmodium falciparum Histidine Rich Protein 2-based rapid diagnostic tests(PflHRP2-based RDTs)are widely used.However,in the last decade,the accuracy of PflHRP2-based RDTs has been challenged by the emerge nee of P.falciparum strains harbouring deletions of the P.falciparum histidine rich protein 2(pflnrp2)gene,resulting in false-negative results.In the Democratic Republic of Congo(D.R.Congo),little is known about the prevalence of the pfhrp2 gene deletion among P.falciparum isolates infecting symptomatic patients,especially in low to moderate transmission areas where pfhrp2 deletion parasites are assumed to emerge and spread.Here we determine the local prevalence and factors associated with pfhrp2 gene deletions among symptomatic malaria patients in the Kwilu Province of the D.R.Congo.

Application of internal standard method in recombinant luminescent bacteria test

Mercury and its organic compounds have been of severe concern worldwide due to their damage to the ecosystem and human health. The development of effective and affordable technology to monitor and signal the presence of bioavailable mercury is an urgent need.The Mer gene is a mercury-responsive resistant gene, and a mercury-sensing recombinant luminescent bacterium using the Mer gene was constructed in this study. The mer operon from marine Pseudomonas putida strain SP1 was amplified and fused with prompterless lux CDABE in the p UCD615 plasmid within Escherichia coli cells, resulting in p THE30–E. coli.The recombinant strain showed high sensitivity and specificity. The detection limit of Hg^2＋was 5 nmol/L, and distinct luminescence could be detected in 30 min. Cd^2＋, Cu^2＋, Zn^2＋, Ca^2＋,Pb^2＋, Mg^2＋, Mn^2＋, and Al^3＋did not interfere with the detection over a range of 10-5–1 m M.Application of recombinant luminescent bacteria testing in environmental samples has been a controversial issue： especially for metal-sensing recombinant strains, false negatives caused by high cytotoxicity are one of the most important issues when applying recombinant luminescent bacteria in biomonitoring of heavy metals. In this study, by establishing an internal standard approach, the false negative problem was overcome;furthermore, the method can also help to estimate the suspected mercury concentration,which ensures high detection sensitivity of bioavailable Hg2＋.