Differential Privacy for Edge Weights in Social Networks

Social networks can be analyzed to discover important social issues; however, it will cause privacy disclosure in the process. The edge weights play an important role in social graphs, which are associated with sensitive information (e.g., the price of commercial trade). In the paper, we propose the MB-CI (Merging Barrels and Consistency Inference) strategy to protect weighted social graphs. By viewing the edge-weight sequence as an unattributed histogram, differential privacy for edge weights can be implemented based on the histogram. Considering that some edges have the same weight in a social network, we merge the barrels with the same count into one group to reduce the noise required. Moreover, k-indistinguishability between groups is proposed to fulfill differential privacy not to be violated, because simple merging operation may disclose some information by the magnitude of noise itself. For keeping most of the shortest paths unchanged, we do consistency inference according to original order of the sequence as an important postprocessing step. Experimental results show that the proposed approach effectively improved the accuracy and utility of the released data

A Closer Look at the Security Risks in the Rust Ecosystem

Rust is an emerging programming language designed for the development of systems software. To facilitate the reuse of Rust code, crates.io, as a central package registry of the Rust ecosystem, hosts thousands of third-party Rust packages. The openness of crates.io enables the growth of the Rust ecosystem but comes with security risks by severe security advisories. Although Rust guarantees a software program to be safe via programming language features and strict compile-time checking, the unsafe keyword in Rust allows developers to bypass compiler safety checks for certain regions of code. Prior studies empirically investigate the memory safety and concurrency bugs in the Rust ecosystem, as well as the usage of unsafe keywords in practice. Nonetheless, the literature lacks a systematic investigation of the security risks in the Rust ecosystem. In this paper, we perform a comprehensive investigation into the security risks present in the Rust ecosystem, asking ``what are the characteristics of the vulnerabilities, what are the characteristics of the vulnerable packages, and how are the vulnerabilities fixed in practice?''. To facilitate the study, we first compile a dataset of 433 vulnerabilities, 300 vulnerable code repositories, and 218 vulnerability fix commits in the Rust ecosystem, spanning over 7 years. With the dataset, we characterize the types, life spans, and evolution of the disclosed vulnerabilities. We then characterize the popularity, categorization, and vulnerability density of the vulnerable Rust packages, as well as their versions and code regions affected by the disclosed vulnerabilities. Finally, we characterize the complexity of vulnerability fixes and localities of corresponding code changes, and inspect how practitioners fix vulnerabilities in Rust packages with various localities.Comment: preprint of accepted TOSEM pape

Statistical analysis of LiDAR-derived structure and intensity variables for tree species identification

Tree species identification is critical for sustainable forest management and native forest conservation. It has been recognised that airborne LiDAR (light detection and ranging) offers advantages over the interpretation of aerial photographs and processing of multi-spectral and/or hyper-spectral remote sensing data in forest classification. However, as shown by our previous studies of forest communities of the Strzelecki Ranges, Victoria, Australia, the only use of LiDAR-derived structure variables may not offer unequivocal distinction between all forest types, such as cool temperate rainforest dominated by the Myrtle Beech (Nothofagus cunninghamii) and adjacent Silver Wattle (Acacia dealbata) forest. This paper reports the results of deploying both structure and intensity variables derived from small-footprint, high-density discrete airborne LiDAR data for the classification of the Myrtle Beech and the Silver Wattle at individual tree level in the Strzeleckis. The tree species classification was achieved via linear discriminant analysis with cross-validation, the accuracy having been assessed by an error matrix. The results showed that the inclusion of LiDAR-derived intensity variables improved the accuracy of the classification of the Myrtle Beech and the Silver Wattle species in the study area. An overall classification accuracy of 86.4% was achieved using both structure and intensity variables

Trends of land surface phenology derived from passive microwave and optical remote sensing systems and associated drivers across the dry tropics 1992–2012

Changes in vegetation phenology are among the most sensitive biological responses to global change. While land surface phenological changes in the Northern Hemisphere have been extensively studied from the widely used long-term AVHRR (Advanced Very High Resolution Radiometer) data, current knowledge on land surface phenological trends and the associated drivers remains uncertain for the tropics. This uncertainty is partly due to the well-known challenges of applying satellite-derived vegetation indices from the optical domain in areas prone to frequent cloud cover. The long-term vegetation optical depth (VOD) product from satellite passive microwaves features less sensitivity to atmospheric perturbations and measures different vegetation traits and functioning as compared to optical sensors. VOD thereby provides an independent and complementary data source for studying land surface phenology and here we performed a combined analysis of the VOD and AVHRR NDVI (Normalized Difference Vegetation Index) datasets for the dry tropics (25°N to 25°S) during 1992–2012. We find a general delay in the VOD derived start of season (SOS) and end of season (EOS) as compared to NDVI derived metrics, however with clear differences among land cover and continents. Pixels characterized by significant phenological trends (P < 0.05) account for up to 20% of the study area for each phenological metric of NDVI and VOD, with large spatial difference between the two sensor systems. About 50% of the pixels studied show significant phenological changes in either VOD or NDVI metrics. Drivers of phenological changes were assessed for pixels of high agreement between VOD and NDVI phenological metrics (serving as a means of reducing noise-related uncertainty). We find rainfall variability and woody vegetation change to be the main forcing variables of phenological trends for most of the dry tropical biomes, while fire events and land cover change are recognized as second-order drivers. Taken together, our study provides new insights on land surface phenological changes and the associated drivers in the dry tropics, as based on the complementary long-term data sources of VOD and NDVI, sensitive to changes in vegetation water content and greenness, respectively

Exploring Impaired SERCA Pump-Caused Alternation Occurrence in Ischemia

Impaired sarcoplasmic reticulum (SR) calcium transport ATPase (SERCA) gives rise to Ca(2+) alternans and changes of the Ca2+release amount. These changes in Ca(2+) release amount can reveal the mechanism underlying how the interaction between Ca(2+) release and Ca(2+) uptake induces Ca(2+) alternans. This study of alternans by calculating the values of Ca(2+) release properties with impaired SERCA has not been explored before. Here, we induced Ca(2+) alternans by using an impaired SERCA pump under ischemic conditions. The results showed that the recruitment and refractoriness of the Ca(2+) release increased as Ca(2+) alternans occurred. This indicates triggering Ca waves. As the propagation of Ca waves is linked to the occurrence of Ca(2+) alternans, the "threshold" for Ca waves reflects the key factor in Ca(2+) alternans development, and it is still controversial nowadays. We proposed the ratio between the diastolic network SR (NSR) Ca content (Cansr) and the cytoplasmic Ca content (Ca i ) (Cansr/Ca i ) as the "threshold" of Ca waves and Ca(2+) alternans. Diastolic Cansr, Ca i , and their ratio were recorded at the onset of Ca(2+) alternans. Compared with certain Cansr and Ca i , the "threshold" of the ratio can better explain the comprehensive effects of the Ca(2+) release and the Ca(2+) uptake on Ca(2+) alternans onset. In addition, these ratios are related with the function of SERCA pumps, which vary with different ischemic conditions. Thus, values of these ratios could be used to differentiate Ca(2+) alternans from different ischemic cases. This agrees with some experimental results. Therefore, the certain value of diastolic Cansr/Ca i can be the better "threshold" for Ca waves and Ca(2+) alternans

Role of p53 in pseudorabies virus replication, pathogenicity, and host immune responses

International audienceAbstractAs a key cellular transcription factor that plays a central role in cellular responses to a broad range of stress factors, p53 has generally been considered as a host cell restriction factor for various viral infections. However, the defined roles of p53 in pseudorabies virus (PRV) replication, pathogenesis, and host responses remain unclear. In the present study, we initially constructed a p53 overexpressing a porcine kidney epithelial cell line (PK-15) to detect the effect of p53 on PRV replication in vitro. The results show that viral glycoprotein B (gB) gene copies and the titers of virus were significantly higher in p53 overexpressing PK-15 cells than in PK-15 and p53 inhibitor treated p53 overexpressing PK-15 cells. A similar result was also found in the p53 inhibitor PFT-α-treated PK-15 cells. We then examined the effects of p53 on PRV infection in vivo by using p53-knockout (p53−/−) mice. The results show that p53 knockout not only led to significantly reduced rates of mortality but also to reduced viral replication and development of viral encephalitis in the brains of mice following intracranial inoculation. Furthermore, we examined the effect of p53 knockout on the expression of the reported host cell regulators of PRV replication in the brains of mice by using RNA sequencing. The results show that p53 knockout downregulated the interferon (IFN) regulator genes, chemokine genes, and antiviral genes after PRV infection. This finding suggests that p53 positively regulates viral replication and pathogenesis both in vitro and in vivo. These findings offer novel targets of intrinsic host cell immunity for PRV infection