A distributed anomaly detection system for in-vehicle network using HTM

With the development of 5G and Internet of Vehicles technology, the possibility of remote wireless attack on an in-vehicle network has been proven by security researchers. Anomaly detection technology can effectively alleviate the security threat, as the first line of security defense. Based on this, this paper proposes a distributed anomaly detection system using hierarchical temporal memory (HTM) to enhance the security of a vehicular controller area network bus. The HTM model can predict the flow data in real time, which depends on the state of the previous learning. In addition, we improved the abnormal score mechanism to evaluate the prediction. We manually synthesized field modification and replay attack in data field. Compared with recurrent neural networks and hidden Markov model detection models, the results show that the distributed anomaly detection system based on HTM networks achieves better performance in the area under receiver operating characteristic curve score, precision, and recall

Accurate Sybil attack detection based on fine-grained physical channel information

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless network

Effects of waste milk feeding on rumen fermentation and bacterial community of pre-weaned and post-weaned dairy calves

The objective of this study was to investigate the effect of waste milk with antibiotic residue on rumen fermentation and rumen bacterial composition of dairy calves during pre-weaned and post-weaned periods. A total of 24 Holstein male calves (43.4 ± 0.93 kg body weight, mean ± standard error) were allocated into four blocks based on birth date. Dairy calves were supplied 100% milk replacer (MR, n = 8), 50% milk replacer mixed with 50% waste milk (MM, n = 8), or 100% waste milk (WM, n = 8). Ruminal samples were collected at 49 and 63 days of age and then subjected to determinations of pH value, volatile fatty acids (VFA), ammonia nitrogen (NH3–N) and 16S rRNA gene amplicon sequencing. The results showed that feeding WM had no effect on the pH value, the concentrations of VFA (acetic acid, propionic acid, butyric acid, isovaleric acid, valeric acid), and NH3–N in dairy calves compared to feeding MR. However, from 49 to 63 days of age, the pH value (p < 0.001) was significantly increased, while the levels of total VFA (p = 0.004), acetic acid (p = 0.01), propionic acid (p = 0.003) and valeric acid (p < 0.001) were significantly decreased. For rumen microorganisms, there was no differences in bacterial diversity among the treatments. But the relative abundance of Veillonellaceae was significantly lower (p = 0.05) in the calves fed WM than that from MR group at 49 days of age; however, no difference was detected at 63 days of age. Feeding WM to calves tended to reduce family Veillonellaceae and genus Olsenella in the rumen at 49 days of age (p = 0.049). Analysis of temporal changes in rumen bacteria based on alpha-diversity and beta-diversity as well as the microbial relative abundances did not exhibit any difference. In addition, relative abundances of Clostridia_UCG-014, Prevotella, Syntrophococcus, Eubacterium_nodatum_group, Pseudoramibacter and Solobacterium were correlated with rumen pH value and the concentrations of TVFA, propionic acid, isovaleric acid, valeric acid and NH3–N. In conclusion, compare to MR, calves supplied with WM had little changes on the rumen pH value, NH3–N or VFAs contents. Additionally, limited effects could be found on rumen microbiota in the calves fed WM. However, further studies needed to explore if there exist any long-term effects of early-life rumen microbiota modulation on dairy cows

A Novel Three-miRNA Signature Identified Using Bioinformatics Predicts Survival in Esophageal Carcinoma

Objective. We identified differentially expressed microRNAs (DEMs) between esophageal carcinoma (ESCA) tissues and normal esophageal tissues. We then constructed a novel three-miRNA signature to predict the prognosis of ESCA patients using bioinformatics analysis. Materials and Methods. We combined two microarray profiling datasets from the Gene Expression Omnibus (GEO) database and RNA-seq datasets from the Cancer Genome Atlas (TCGA) database to analyze DEMs in ESCA. The clinical data from 168 ESCA patients were selected from the TCGA database to assess the prognostic role of the DEMs. The TargetScan, miRDB, miRWalk, and DIANA websites were used to predict the miRNA target genes. Functional enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (David), and protein-protein interaction (PPI) networks were obtained using the Search Tool for the Retrieval of Interacting Genes database (STRING). Results. With cut-off criteria of P 1.0, 33 overlapping DEMs, including 27 upregulated and 6 downregulated miRNAs, were identified from GEO microarray datasets and TCGA RNA-seq count datasets. The Kaplan–Meier survival analysis indicated that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) was significantly associated with the overall survival of ESCA patients. The results of univariate and multivariate Cox regression analysis showed that the three-miRNA signature was a potential prognostic factor in ESCA. Furthermore, the gene functional enrichment analysis revealed that the target genes of the three miRNAs participate in various cancer-related pathways, including viral carcinogenesis, forkhead box O (FoxO), vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (ErbB2), and mammalian target of rapamycin (mTOR) signaling pathways. In the PPI network, three target genes (MAPK1, RB1, and CLTC) with a high degree of connectivity were selected as hub genes. Conclusions. Our results revealed that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) is a potential novel prognostic biomarker for ESCA

Establishment of a cell-based assay for examining the expression of tumor necrosis factor alpha (TNF-alpha) gene

Tumor necrosis factor alpha (TNF-alpha) is a proinflammatory cytokine produced by activated macrophages and lymphocytes and involved in many inflammatory diseases. Preventing the production or action of TNF-alpha is a potent therapeutic strategy for these inflammatory diseases. Since there is a lack of rapid and effective assay for examining the expression TNF-alpha in macrophages, we attempt to establish a reporter system to assess TNF-alpha gene expression through measuring luciferase activity. In this study, mouse macrophage cell line RAW 264.7 was stably transfected with a luciferase reporter pGL3-TNFPro-UTR, which contains TNF-alpha promoter and 3'-untranslated region (3'-UTR). The TNF-alpha-luciferase reporter cell line is used for assessing the expression of TNF-alpha gene induced by LPS in the presence or absence of chemicals that inhibit the biosynthesis of TNF-alpha such as dexamethasone and emodin, and also for measuring change of expression of TNF-alpha gene under downregulation of the expression of steroid receptor coactivator-3, a modulator for TNF-alpha. The luciferase activity correlated well with the ELISA results for TNF-alpha production, therefore, the TNF-alpha-luciferase reporter cell line is a sensitive, effective tool for studying the expression of TNF-alpha gene