2018 14th International Conference on Computational Intelligence and Security (CIS)最新文献_第9页

A Method of CNN Traffic Classification Based on Sppnet 一种基于Sppnet的CNN流量分类方法

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00093

Huiyi Zhou, Yong Wang, Miao Ye

引用次数: 9

The Comparing Analysis of Drosophila Optimization and Gravitational Search Algorithm 果蝇优化算法与引力搜索算法的比较分析

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00020

Xiaohua Li

引用次数: 0

Automotive ECU Functional Test System Based on PXI 基于PXI的汽车ECU功能测试系统

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00061

Changhong Zhu, Xiaoping Liang, Wei Deng

{"title":"Automotive ECU Functional Test System Based on PXI","authors":"Changhong Zhu, Xiaoping Liang, Wei Deng","doi":"10.1109/CIS2018.2018.00061","DOIUrl":"https://doi.org/10.1109/CIS2018.2018.00061","url":null,"abstract":"The traditional functional test system has such defects as high deviation and poor stability in the automotive ECU (Electronic Control Unit) test, so an automotive ECU functional test system based on PXI was proposed in the paper, wherein the system is composed of PXI bus, electronic monitoring test module, universal meter and computer. Specifically, the PXI bus is used for the data collection and the initialization test of the automotive ECU and for transmitting the data to the electronic monitoring test module; the electronic monitoring test module is composed of controller, power supply module, detection module, signal transceiver and on-off controller; the power module is used as the power supply of the electronic monitoring module; the detection module is used for transmitting the fault data detected thereby to the signal transceiver for signal transformation; the on-off controller is used for switching or cutting off the circuit through the fault signal analysis, and the controller is used for controlling the operation procedure of the whole electronic monitoring test module and for transmitting the screened data to the universal meter; the universal meter is used for amplifying the received data signals and transmitting the amplified data to the computer. The software design aimed to provide the test procedure and the troubleshooting algorithm of the automotive ECU functional test system based on PXI. The experiment result shows that the system designed thereby has high accuracy and high stability.","PeriodicalId":185099,"journal":{"name":"2018 14th International Conference on Computational Intelligence and Security (CIS)","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122963226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Class of Fuzzy Smooth Piecewise Twin Support Vector Machine 一类模糊光滑分段双支持向量机

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00091

Qing Wu, Haoyi Zhang, Rongrong Jing, Zhicang Wang

引用次数: 1

An Evolutionary Tabu Search Algorithm for Matching Biomedical Ontologies 生物医学本体匹配的进化禁忌搜索算法

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00049

Xingsi Xue, Aihong Ren, Dongxu Chen

{"title":"An Evolutionary Tabu Search Algorithm for Matching Biomedical Ontologies","authors":"Xingsi Xue, Aihong Ren, Dongxu Chen","doi":"10.1109/CIS2018.2018.00049","DOIUrl":"https://doi.org/10.1109/CIS2018.2018.00049","url":null,"abstract":"Since these biomedical ontologies are mostly developed independently and many of them cover overlapping domains, establishing meaningful links between them, so-called biomedical ontology matching, is critical to ensure inter-operability and has the potential to unlock biomedical knowledge by bridging related data. Due to the complexity of the biomedical ontology matching problem (large-scale optimal problem with lots of local optimal solutions), Evolutionary Algorithm (EA) can present a good methodology for determining biomedical ontology alignments. However, the slow convergence and premature convergence are two main shortcomings of EA-based ontology matching techniques, which make them incapable of effectively searching the optimal solution for biomedical ontology matching problems. To overcome this drawback, in this paper, an Evolutionary Tabu Search Algorithm (ETSA) is proposed, which introduces the Tabu Search algorithm (TS) as a local search strategy into EA's evolving process. Moreover, to efficiently solve the biomedical ontology matching problem, an biomedical concept similarity measure is presented to calculate the similarity value of two biomedical concepts and an optimal model for biomedical ontology matching is constructed. The experiment is conducted on the Large Biomed track provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with state-of-the-art ontology matchers show the effectiveness of ETSA.","PeriodicalId":185099,"journal":{"name":"2018 14th International Conference on Computational Intelligence and Security (CIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114673603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid Classification of WEB Trojan Exploiting Small Volume of Labeled Data Vectors 利用小容量标记数据向量的WEB木马混合分类

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00070

Shichang Xuan, Dapeng Man, Wei Wang, Kaiyue Qin, Wu Yang

{"title":"Hybrid Classification of WEB Trojan Exploiting Small Volume of Labeled Data Vectors","authors":"Shichang Xuan, Dapeng Man, Wei Wang, Kaiyue Qin, Wu Yang","doi":"10.1109/CIS2018.2018.00070","DOIUrl":"https://doi.org/10.1109/CIS2018.2018.00070","url":null,"abstract":"This research paper introduces a Denoising auto encoder (Unsupervised Deep Neural Network) combined with a typical Back Propagation (BP) Artificial Neural Network (ANN), capable of efficiently detecting WEB Trojan malware. Several researchers in the literature, employ Machine Learning (ML) to detect WEB Trojans. The data used in this paper, come from the WEB security Gateway, since there is less tagged data than unlabeled ones. Based on the literature, simple Supervised Learning (SULE) is not efficient enough for this task. The algorithm proposed herein is hybrid. It employs Unsupervised Learning (UNLE) based on a Stack Denoising Auto encoder (SdAE) to pre-train the data (one layer at a time). This results in more robust feature vectors. Then, in the fine-tuning process, minor adjustments are made through Supervised Learning (SUL) based on a BP ANN. The proposed approach, ensures that the developed model, can still perform accurately, even when the training data set has a small number of tagged data vectors. This research, verifies this hybrid Deep Learning approach used for WEB Trojan detection, outperforms other common classification methods.","PeriodicalId":185099,"journal":{"name":"2018 14th International Conference on Computational Intelligence and Security (CIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128228556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Research on the Practical Teaching Mode Based on Human Resources Professional Competition 基于人力资源专业竞争的实践教学模式研究

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/cis2018.2018.00118

Dongyi He, Wenxue Niu

引用次数: 0

Real-Time Network Traffic Classification Based on CDH Pattern Matching 基于CDH模式匹配的实时网络流量分类

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00036

Xunzhang Li, Yong Wang, Wenlong Ke, Hao Feng

引用次数: 4

Cloud Service Selection with Fuzzy C-Means Artificial Immune Network Memory Classifier 基于模糊c均值人工免疫网络记忆分类器的云服务选择

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00065

Weitao Ha

引用次数: 6

A New Hybrid Global Optimization Algorithm 一种新的混合全局优化算法

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI: 10.1109/CIS2018.2018.00087

Ding Wang

引用次数: 0