Identifying cyber attacks traffic is very important for the Internet of things (IoT) security in smart city. Recently, the research community in the field of IoT Security endeavor hard to build ...anomaly, intrusion and cyber attacks traffic identification model using Machine Learning (ML) algorithms for IoT security analysis. However, the critical and significant problem still not studied in depth that is how to select an effective ML algorithm when there are numbers of ML algorithms for cyber attacks detection system for IoT security. In this paper, we proposed a new framework model and a hybrid algorithm to solve this problem. Firstly BoT-IoT identification dataset is applied and its 44 effective features are selected from a number of features for the machine learning algorithm. Then five effective machine learning algorithm is selected for the identification of malicious and anomaly traffic identification and also select the most widely ML algorithm performance evaluation metrics. To find out which ML algorithm is effective and should be used to select for IoT anomaly and intrusion traffic identification, a bijective soft set approach and its algorithm is applied. Then we applied the proposed algorithm based on bijective soft set approach. Our experimental results show that the proposed model with the algorithm is effective for the selection ML algorithm out of numbers of ML algorithms.
•This paper investigate Machine Learning (ML) algorithm and effective features.•This paper proposed a new framework model and a hybrid algorithm.•The basic technique used in this paper is bijective soft set and proposed new algorithm.•This paper selected effective ML algorithm and features for the identification attacks.•Finally, the paper validates the selected ML algorithm, Feature set for Attacks traffic.
Edge computing provides high-class intelligent services and computing capabilities at the edge of the networks. The aim is to ease the backhaul impacts and offer an improved user experience. However, ...the edge artificial intelligence exacerbates the security of the cloud computing environment due to the dissociation of data, access control, and service stages. In order to prevent users from carrying out lateral movement attacks in an edge-cloud computing environment, in this paper we propose a real-time lateral movement detection method, named CloudSEC, based on an evidence reasoning network for the edge-cloud environment. First, the concept of vulnerability correlation is introduced. Based on the vulnerability knowledge and environmental information of the network system, the evidence reasoning network is constructed, and the lateral movement reasoning ability provided by the evidence reasoning network is then used. The experiment results show that CloudSEC provides a strong guarantee for the rapid and effective evidence investigation, as well as real-time attack detection.
Abstract
Background
Non-small cell lung cancer (NSCLC) is one of the major types of lung cancer, which is a prevalent human disease all over the world. LncRNA LINC01503 is a super-enhancer-driven ...long non-coding RNA that is dysregulated in several types of human cancer. However, its role in NSCLC remains unknown.
Methods
Thirty NSCLC patients were recruited between April 2012 and April 2016. Luciferase reporter assay, qRT-PCR, Cell Counting Kit-8 (CCK-8), Transwell migration assay, RNA pull-down assay, western blotting, 5-ethynyl-29-deoxyuridine (EdU) assays, and flow cytometry were utilized to characterize the roles and relationships among LINC01503, miR-342-3p, and LASP1 in NSCLC. The transplanted mouse model was built to examine their biological functions in vivo.
Results
We demonstrated that the expression of lncRNA LINC01503 and LIM and SH3 domain protein 1 (LASP1) were upregulated and miR-342-3p was downregulated in NSCLC samples and cell lines. Functional experiments revealed that inhibiting the expression of LINC01503 or over-expression of miR-342-3p inhibited NSCLC growth and metastasis both in vitro and in vivo. In addition, LINC01503 could bind to miR-342-3p and affect the expression of LASP1.
Conclusion
These results provide a comprehensive analysis of the roles of LINC01503 as a competing endogenous RNA (ceRNA) in NSCLC progression.
In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to ...carefully select the sources to make sure that high quality data is accessed. A solution is to perform a quality evaluation in the cloud and select a set of high-quality, low-cost data sources (i.e., sensors or small sensor networks) that can answer queries. This paper studies the problem of min-cost quality-aware query which aims to find high quality results from multi-sources with the minimized cost. The measurement of the query results is provided, and two methods for answering min-cost quality-aware query are proposed. How to get a reasonable parameter setting is also discussed. Experiments on real-life data verify that the proposed techniques are efficient and effective.
Long non-coding RNAs (lncRNAs) are key players in the development and progression of human cancers. The lncRNA XIST (X-inactive specific transcript) has been shown to be upregulated in human ...non-small cell lung cancer (NSCLC); however, its role and molecular mechanisms in NSCLC cell progression remain unclear.
qRT-PCR was conducted to assess the expression of XIST and miR-186. Cell proliferation was detected using MTT assay. Cell invasion and migration were evaluated using transwell assay. Cell cycle distribution and apoptosis rates were analyzed by flow cytometry. Luciferase reporter assay was used to identify the direct regulation of XIST and miR-186. A RNA immunoprecipitation was used to analyze whether XIST was associated with the RNA-induced silencing complex (RISC).
We confirmed that XIST was upregulated in NSCLC cell lines and tissues. Functionally, XIST knockdown inhibited cancer cell proliferation and invasion, and induced apoptosis in vitro, and suppressed subcutaneous tumor growth in vivo. Mechanistic investigations revealed a reciprocal repressive interaction between XIST and miR-186-5p. Furthermore, we showed that miR-186-5p has a binding site for XIST. Our data also indicated that XIST and miR-186-5p are likely in the same RNA induced silencing complex.
Together, our data revealed that XIST knockdown confers suppressive function in NSCLC and XIST may be a novel therapeutic marker in this disease.
Bacterial infections caused by pathogens have always been a thorny issue that threatens human health, and there is urgent need to develop a new generation of antimicrobial nano-agents and treatments. ...Herein, biodegradable nickel disulfide (ND) nanozymes as excellent antibacterial agents that integrate excellent photothermal performance, nano-catalysis property, and glutathione (GSH)-depleting function have been successfully constructed. The ND nanozymes can effectively catalyze the decomposition of H2O2 to produce ⋅OH, and the hyperthermia of ND nanozymes generated by photothermal therapy (PTT) can further increase its catalytic activity, which provides rapid and effective bacterial killing effect compared with nano-catalytic treatment or PTT alone. Surprisingly, the ND nanozymes have the ability of GSH consumption, thus enhancing its sterilization effect. Moreover, the ND nanozymes are biodegradable nanomaterials that do not cause any significant toxicity in vivo. Collectively, the ND nanozymes with excellent photothermal performance, catalytic activity, and GSH-depleting function are used for high-efficiency sterilization.
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•ND nanozymes have good photothermal and catalysis effect and GSH-depleting function•The multifunctional ND nanozymes have achieved satisfactory antibacterial effects•The biodegradable ND nanozymes have a wide application in precise sterilization
Medicine; Catalysis; Nanomaterials
Industrial control system (ICS) is gradually transitioning from being closed and isolated to open and interconnected. The network threats to ICS are becoming highly hidden, strong-confrontation, and ...cross-domain in nature. Once subjected to cyberattacks, industrial production will be directly affected. Consequently, network attacks on ICS and corresponding security protection technologies have attracted significant attention. This study focuses on the security protection issues of ICS. First, we analyzed the specific characteristics of ICS security protection, as well as the unclear and uncontrollable security challenges of ICS. The network attacks on ICS are summarized and analyzed, and then the security protection systems with a self-defense mode, such as border protection and defense in depth, are discussed. In view of the security challenges, the development ideas are given from the aspects of security and controllability of ICS and a novel security protection system of ICS, and key tasks and key technolo
Cryptosporidium is a highly pathogenic parasite responsible for diarrhea in children worldwide. Here, the epidemiological status and genetic characteristics of Cryptosporidium in children with or ...without diarrhea were investigated with tracking of potential sources in Wenzhou City, China.
A total of 1032 children were recruited, 684 of whom had diarrhea and 348 without, from Yuying Children's Hospital in Wenzhou, China. Samples of stool were collected from each participant, followed by extraction of DNA, genotyping, and molecular identification of Cryptosporidium species and subtypes.
Twenty-two of the 1032 (2.1%) children were infected with Cryptosporidium spp. with 2.5% (17/684) and 1.4% (5/348) in diarrhoeic and asymptomatic children, respectively. Four Cryptosporidium species were identified, including C. parvum (68.2%; 15/22), C. felis (13.6%; 3/22), C. viatorum (9.1%; 2/22), and C. baileyi (9.1%; 2/22). Two C. parvum subtypes named IIdA19G1 (n = 14) and IInA10 (n = 1), and one each of C. felis (XIXa) and C. viatorum (XVaA3g) subtype was found as well.
This is the first research that identified Cryptosporidium in children of Wenzhou, China, using PCR. Identification of zoonotic C. parvum, C. felis, C. viatorum, and their subtypes indicate potential cross-species transmission of Cryptosporidium between children and animals. Additionally, the presence of C. baileyi in children suggests that this species has a wider host range than previously believed and that it possesses the capacity to infect humans.
Blastocystis sp., a significant zoonotic parasite with a global distribution, was the focus of this study, which aimed to investigate its prevalence and genetic diversity among diarrheic and ...asymptomatic children in Wenzhou, China. We collected 1,032 fecal samples from Yuying Children's Hospital, Wenzhou, China, comprising 684 from children with diarrhea and 348 from asymptomatic children. Genomic DNA extracted from these samples was used to detect Blastocystis spp. by PCR, targeting the small subunit ribosomal RNA gene. Subsequently, a phylogenetic tree was constructed, applying the maximum likelihood method. Blastocystis spp. were detected in 67 (6.5%) of the fecal samples. The prevalence rate of Blastocystis spp. in diarrheic children (8.8%; 60/684) was significantly higher than that in asymptomatic children (2.0%; 7/348) (χ
= 17.3, p < 0.001). Sequence analysis of the SSU rRNA gene identified five known Blastocystis spp. subtypes, ST1 (n = 12), ST2 (n = 5), ST3 (n = 35), ST4 (n = 12), and ST7 (n = 3). ST1 and ST3 were present in both diarrheic and asymptomatic children, while ST2, ST4, and ST7 were exclusive to diarrheic children. Intra-subtype genetic polymorphisms were identified, comprising four variations in ST1 (ST1-1 to ST1-4), five in ST3 (ST3-1 to ST3-5), two in ST4 (ST4-1 and ST4-2), and two in ST7 (ST7-1 and ST7-2). Notably, ST1-2 to ST1-4, ST3-3 to ST3-5, and ST7-1 and ST7-2 represent newly identified variations. The composition and genetic characteristics of subtypes among children in this region suggest various sources of infection, including human-to-human and animal-to-human transmission.
Selecting the right features for further data analysis is important in the process of equipment anomaly detection, especially when the origin data source involves high dimensional data with a low ...value density. However, existing researches failed to capture the fact that the sensor data are usually correlated (e.g., duplicated deployed sensors), and the correlations would be broken when anomalies occur with happen to the monitored equipment. In this paper, we propose to capture such sensor data correlation changes to improve the performance of IoT (Internet of Things) equipment anomaly detection. In our feature selection method, we first cluster correlated sensors together to recognize the duplicated deployed sensors according to sensor data correlations, and we monitor the data correlation changes in real time to select the sensors with correlation changes as the representative features for anomaly detection. To that end, (1) we conducted curve alignment for the sensor clustering; (2) we discuss the appropriate window size for data correlation calculation; (3) and adopted MCFS (Multi-Cluster Feature Selection) into our method to adapt to the online feature selection scenario. According to the experiment evaluation derived from real IoT equipment, we prove that our method manages to reduce the false negative of IoT equipment anomaly detection of 30% with almost the same level of false positive.
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