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ShuYu Chen,GuiPing Wang,Jun Liu,MingWei Lin 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.1
In order to successfully monitor a large-scale distributed system, it is an important issue that the monitoring function fully covers all the entities in the system. To this end, a key challenge is to efficiently transmit state information of the entities in the system. This paper solves this challenge from two aspects. First, in virtue of the idea of self-organizing networks, this paper proposes a neighborhood organization algorithm, which self-organizes the nodes into several monitoring neighborhoods based on the t distance between nodes. The second aspect focuses on message transmission. There are three common message transmission methods in network, i.e., flooding, multicast and unicast. Flooding may cause high network overhead, while unicast may pose high system delay. Based on the idea of Gossip protocol, this paper proposes a directional message dissemination algorithm (D-Gossip), which is a kind of probabilistic multicast. D-Gossip reduces message dissemination uncertainty of traditional Gossip protocols. It effectively improves the efficiency and coverage of message dissemination, while reducing redundant information in the system due to Gossip protocol. The experimental results show that the neighborhood organization algorithm and the D-Gossip can effectively solve the above challenge.
Chen Shuyu,Yu Li,Deng Yao,Liu Yuanyuan,Wang Lingwei,Li Difei,Yang Kai,Liu Shengming,Tao Ailin,Chen Rongchang 대한천식알레르기학회 2022 Allergy, Asthma & Immunology Research Vol.14 No.5
Purpose: Interleukin (IL)-17A plays a critical role in the pathogenesis of allergic airway inflammation. Yet, the exact roles of IL-17A in asthma are still controversial. Thus, the aim of this study was to dissect the roles of IL-17A in toluene diisocyanate (TDI)-induced mixed granulocytic asthma and to assess the effects of neutralizing antibody in different effector phases on TDI-induced asthma. Methods: IL-17A functions in allergic airway inflammation were evaluated using mice deficient in IL-17A (Il17a−/−) or IL-17A monoclonal antibody (IL-17A mab, intraperitoneally, 50 μg per mouse, 100 μg per mouse). Moreover, the effects of exogenous recombinant IL (rIL)-17A in vivo (murine rIL-17A, intranasally, 1 μg per mouse) and in vitro (human rIL-17A, 100 ng/mL) were investigated. Results: TDI-induced mixed granulocytic airway inflammation was IL-17A-dependent because airway hyperreactivity, neutrophil and eosinophil infiltration, airway smooth muscle thickness, epithelium injury, dysfunctional T helper (Th) 2 and Th17 responses, granulocytic chemokine production and mucus overproduction were more markedly reduced in the Il17a−/− mice or by IL-17A neutralization during the sensitization phase of wild-type (WT) mice. By contrast, IL-17A neutralization during the antigen-challenge phase aggravated TDI-induced eosinophils recruitment, with markedly elevated Th2 response. In line with this, instillation of rIL-17 during antigen sensitization exacerbated airway inflammation by promoting neutrophils aggregation, while rIL-17A during the antigen-challenge phase protected the mice from TDI-induced airway eosinophilia. Moreover, rIL-17A exerted distinct effects on eosinophil- or neutrophil-related signatures in vitro. Conclusions: Our data demonstrated that IL-17A was required for the initiation of TDI-induced asthma, but functioned as a negative regulator of established allergic inflammation, suggesting that early abrogation of IL-17A signaling, but not late IL-17A neutralization, may prevent the progression of TDI-induced asthma and could be used as a therapeutic strategy for severe asthmatics in clinical settings.
An Improved Event Scenario Correlation Method for Multi-Source Security Log
Qianyun Wang,Shuyu Chen,Hancui Zhang,Tianshu Wu 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.2
Developing computer technologies and a network of persistently growing size put massive hosts and transmission devices in a vast network at increasingly higher risks. Log information of various devices can facilitate the detection of intrusion and attacks. Log information from a single data source is, however, with limitations. The analysis results cannot precisely reflect the current network situation if log information in a single data source is analyzed without correlation to analysis of log information from different data sources. To better demonstrate network situation, this paper proposes an improved event scenario correlation method for multi-source log analysis via researching on numerous existing data fusion methods and event correlation methods as well as integration of conventional event scenario correlation (ESC) method with fuzzy reasoning. Experimental results prove that the proposed method significantly reduces the False Positive rate (FP rate) and False Negative rate (FN rate) of security logs.
Anomaly-based Intrusion Detection using Multiclass-SVM with Parameters Optimized by PSO
GuiPing Wang,ShuYu Chen,Jun Liu 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.6
Intrusion detection systems (IDS) play an important role in defending network systems from insider misuse as well as external attackers. Compared with misuse-based techniques, anomaly-based intrusion detection techniques perform well in detecting new attacks. Firstly, this paper proposes a feature selection algorithm based on SVM (termed FS-SVM) to reduce the dimensionality of sample data. Moreover, this paper presents an anomaly-based intrusion detection algorithm, i.e., multiclass support vector machine (MSVM) with parameters optimized by particle swarm optimization (PSO) (termed MSVM-PSO), to detect anomalous connections. To verify the effectiveness of these two proposed algorithms (FS-SVM and MSVM-PSO) and the detection precision of MSVM-PSO, this paper conducts experiments on the famous KDD Cup dataset. This paper compares MSVM-PSO with three commonly adopted algorithms, namely, Bayesian, K-Means, and multiclass SVM with parameters optimized grid method (MSVM-grid). The experimental results show that MSVM-PSO outperforms these three algorithms in detection accuracy, FP rate, and FN rate.