Proceedings of the 2019 3rd International Conference on Information System and Data Mining最新文献

Using Robust Data Governance to Mitigate the Impact of Cybercrime 利用稳健的数据治理减轻网络犯罪的影响

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325923

Gerald Onwujekwe, Manoj A. Thomas, Kweku-Muata A. Osei-Bryson

引用次数: 7

Instant Adaptation Enrichment Technique to Improve Web Accessibility for Blind Users 提高盲人网页可访问性的即时适应增强技术

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325931

Suliman K. Almasoud, H. Mathkour

引用次数: 1

Network Traffic Anomaly Detection Based on Information Gain and Deep Learning 基于信息增益和深度学习的网络流量异常检测

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325946

Xianglin Lu, Pengju Liu, Jiayi Lin

{"title":"Network Traffic Anomaly Detection Based on Information Gain and Deep Learning","authors":"Xianglin Lu, Pengju Liu, Jiayi Lin","doi":"10.1145/3325917.3325946","DOIUrl":"https://doi.org/10.1145/3325917.3325946","url":null,"abstract":"With the rapid development of the Internet, the network traffic shows an explosive growth trend. Although the Internet facilitates people's lives, it also brings a lot of security threats. Thus, the analysis of abnormal behavior of network traffic becomes a crucial factor for ensuring the quality of Internet services and preventing network intrusion. This paper proposes a deep learning method that combines CNN and LSTM to detect abnormal network traffic, especially unknown intrusions. In the field of machine learning, the choice of features is the key ingredient to the effect and accuracy of the model. Therefore, this paper also proposes a feature selection method based on Information Gain (IG), extracting more valuable features, which are fed into the model. We use CNN to extract the higher dimensional features of the input data, and then use LSTM to learn the timing characteristics of the network traffic. We applied our model on the KDD99 dataset and assessed its accuracy. When the epoch greater than 4, the training accuracy reaches 0.99 and testing accuracy reaches 0.925, which showed a certain improvement compared with the traditional model. In the era when information volume is becoming more and more dense, the analysis of network traffic will become more and more necessary, which also proves broader application prospects.","PeriodicalId":249061,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Information System and Data Mining","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130019594","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: 9

A Practical Evaluation of a Secure and Energy-Efficient Smart Parking System Using the MQTT Protocol 基于MQTT协议的安全节能智能停车系统的实际评估

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325937

Ali Alqazzaz, Raed Alharthi, Ibrahim Alrashdi, E. Aloufi, M. Zohdy, Ming Hua

{"title":"A Practical Evaluation of a Secure and Energy-Efficient Smart Parking System Using the MQTT Protocol","authors":"Ali Alqazzaz, Raed Alharthi, Ibrahim Alrashdi, E. Aloufi, M. Zohdy, Ming Hua","doi":"10.1145/3325917.3325937","DOIUrl":"https://doi.org/10.1145/3325917.3325937","url":null,"abstract":"The smart parking system is a major component of the smart city concept, especially in the age of the Internet of Things (IoT). It attempts to take the stress out of finding a free parking space in crowded places, mostly during peak times. This paper focuses on implementing a secure smart parking solution based on the publish-subscribe communication model for exchanging a huge volume of data with a large number of clients while minimizing the power consumption. The Elliptic Curve Cryptography (ECC) was adopted in this paper as a promising substitution to traditional public key cryptography such as Rivest-Shamir-Adleman (RSA). The implemented system provides several functional services including parking vacancy detection, real-time information for drivers about parking availability, driver guidance, and parking reservation. Moreover, it provides security mechanisms for both network and application layers. Performance and power consumption experiments using a testbed show the efficiency and practicality of the implemented system, essentially with the IoT resource-constrained devices. Our findings demonstrate achieving energy consumption reductions of up to 54% and a CPU usage decrease of up to 55% compared to the existing solutions.","PeriodicalId":249061,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Information System and Data Mining","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125564795","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: 3

CUDA Optimized Neural Network Predicts Blood Glucose Control from Quantified Joint Mobility and Anthropometrics CUDA优化神经网络预测血糖控制量化关节活动和人体测量

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325940

Sterling Ramroach, A. Dhanoo, B. Cockburn, A. Joshi

{"title":"CUDA Optimized Neural Network Predicts Blood Glucose Control from Quantified Joint Mobility and Anthropometrics","authors":"Sterling Ramroach, A. Dhanoo, B. Cockburn, A. Joshi","doi":"10.1145/3325917.3325940","DOIUrl":"https://doi.org/10.1145/3325917.3325940","url":null,"abstract":"Neural network training entails heavy computation with obvious bottlenecks. The Compute Unified Device Architecture (CUDA) programming model allows us to accelerate computation by passing the processing workload from the CPU to the graphics processing unit (GPU). In this paper, we leveraged the power of Nvidia GPUs to parallelize all of the computation involved in training, to accelerate a backpropagation feed-forward neural network with one hidden layer using CUDA and C++. This optimized neural network was tasked with predicting the level of glycated hemoglobin (HbA1c) from non-invasive markers. The rate of increase in the prevalence of Diabetes Mellitus has resulted in an urgent need for early detection and accurate diagnosis. However, due to the invasiveness and limitations of conventional tests, alternate means are being considered. Limited Joint Mobility (LJM) has been reported as an indicator for poor glycemic control. LJM of the fingers is quantified and its link to HbA1c is investigated along with other potential non-invasive markers of HbA1c. We collected readings of 33 potential markers from 120 participants at a clinic in south Trinidad. Our neural network achieved 95.65% accuracy on the training and 86.67% accuracy on the testing set for male participants and 97.73% and 66.67% accuracy on the training and testing sets for female participants. Using 960 CUDA cores from a Nvidia GeForce GTX 660, our parallelized neural network was trained 50 times faster on both subsets, than its corresponding CPU implementation on an Intel® Core™ i7-3630QM 2.40 GHz CPU.","PeriodicalId":249061,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Information System and Data Mining","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126790916","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

Study on Polymorphic Equilibrium of Internet Economy 互联网经济的多态均衡研究

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325950

Chenggang Li, Lu Ge

引用次数: 0

Using Intelligent Algorithms to Construct a Wafer Foundry System in Manufacturing Industry 利用智能算法构建制造业晶圆代工系统

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325918

Ruey-Shun Chen, Yeh-Cheng Chen, Jyh-haw Yeh, Yu-Xi Hu, N. Xiong, C-P Lee

{"title":"Using Intelligent Algorithms to Construct a Wafer Foundry System in Manufacturing Industry","authors":"Ruey-Shun Chen, Yeh-Cheng Chen, Jyh-haw Yeh, Yu-Xi Hu, N. Xiong, C-P Lee","doi":"10.1145/3325917.3325918","DOIUrl":"https://doi.org/10.1145/3325917.3325918","url":null,"abstract":"The research combines two heuristic algorithms, COMSOAL and Priority rule-based algorithm, to design a production scheduling algorithm. Meanwhile it refers to dispatching rule and wafer start rule. Also base on the requirements and characters of wafer foundry companies, it designs proper capacity constraint model and wafer start rule to construct production planning system. Using simple, fast and flexible methods to generate reasonable and feasible production plans. The results of the research can give the wafer foundry companies several contributions. First, it shortens the execution time of generating a production plan. It improves the flexibility and efficiency of production planning. Second, the resolution of production plan is raised from the summary of manufacturing process and product type to full product name of order and demand allocation. It improves the resolution and accuracy of information analysis. Third, the planning period of wafer start plan is improved as well. Last, the frequency of production planning operation is improved from once a fortnight to once a week.","PeriodicalId":249061,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Information System and Data Mining","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133930760","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

An Application of Image Classification to Saltwater Fish Identification in Louisiana Fisheries 图像分类在路易斯安那州咸水鱼类识别中的应用

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325934

Nibha Manandhar, John W. Burris

引用次数: 3

Research Trends in Knowledge Management: Past, Present and Future 知识管理的研究趋势:过去、现在和未来

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325949

Shabahat Husain, Rumman Gul

引用次数: 1

Citrus Greening Infection Detection (CiGID) by Computer Vision and Deep Learning 通过计算机视觉和深度学习检测柑橘绿化病害（CiGID）

Proceedings of the 2019 3rd International Conference on Information System and Data Mining Pub Date : 2019-04-06 DOI: 10.1145/3325917.3325936

Charles T. Soini, Sofiane Fellah, Muhammad R. Abid

引用次数: 10