Pub Date : 2016-09-01DOI: 10.1109/NICS.2016.7725638
P. Nguyen, Tien Do, Anh-Thu Nguyen-Thi, T. Ngo, Duy-Dinh Le, T. Nguyen
Convolutional Neural Networks (CNNs) have been established as a powerful class of models for image recognition problems giving state-of-the-art results on recognition, detection, segmentation, classification and retrieval. Encouraged by these results, we develop our previous work [14] by implementing deep neural network architecture for extracting and representing visual features to improve the clustering quality of web video search results. Experiments were conducted on a dataset published in [14]. This dataset includes 1580 videos from 18 queries issued to the YouTube search engine. Our method exhibits significant performance improvements over the previously published result evaluated by Entropy measure (23.27% vs. 39.46%) and Purity measure (77.09% vs. 61.50%).
卷积神经网络(cnn)已经被建立为一类强大的图像识别问题模型，在识别、检测、分割、分类和检索方面提供了最先进的结果。受这些结果的鼓舞，我们通过实现用于提取和表示视觉特征的深度神经网络架构来改进web视频搜索结果的聚类质量，从而发展了我们之前的工作[14]。实验是在[14]发表的数据集上进行的。该数据集包括来自YouTube搜索引擎的18个查询的1580个视频。与先前发表的熵测度(23.27% vs. 39.46%)和纯度测度(77.09% vs. 61.50%)评价结果相比，我们的方法表现出显著的性能改进。
{"title":"Clustering web video search results with convolutional neural networks","authors":"P. Nguyen, Tien Do, Anh-Thu Nguyen-Thi, T. Ngo, Duy-Dinh Le, T. Nguyen","doi":"10.1109/NICS.2016.7725638","DOIUrl":"https://doi.org/10.1109/NICS.2016.7725638","url":null,"abstract":"Convolutional Neural Networks (CNNs) have been established as a powerful class of models for image recognition problems giving state-of-the-art results on recognition, detection, segmentation, classification and retrieval. Encouraged by these results, we develop our previous work [14] by implementing deep neural network architecture for extracting and representing visual features to improve the clustering quality of web video search results. Experiments were conducted on a dataset published in [14]. This dataset includes 1580 videos from 18 queries issued to the YouTube search engine. Our method exhibits significant performance improvements over the previously published result evaluated by Entropy measure (23.27% vs. 39.46%) and Purity measure (77.09% vs. 61.50%).","PeriodicalId":347057,"journal":{"name":"2016 3rd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121242177","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}
Pub Date : 2016-09-01DOI: 10.1109/NICS.2016.7725672
Duc Minh Vo, T. Le
Motivated by the newly recent trend in pattern recognition - convolutional neural network (CNN), we introduce a new fusion method based on CNN and support vector machines (SVM) for facial expression recognition problem. Our study puts the deep generic features from CNN and SVM together which is more efficient than CNN only. We investigate our proposed method on Cohn-Kanade dataset and achieve 96.04% in accuracy rate which is better than other state-of-the-art methods.
{"title":"Deep generic features and SVM for facial expression recognition","authors":"Duc Minh Vo, T. Le","doi":"10.1109/NICS.2016.7725672","DOIUrl":"https://doi.org/10.1109/NICS.2016.7725672","url":null,"abstract":"Motivated by the newly recent trend in pattern recognition - convolutional neural network (CNN), we introduce a new fusion method based on CNN and support vector machines (SVM) for facial expression recognition problem. Our study puts the deep generic features from CNN and SVM together which is more efficient than CNN only. We investigate our proposed method on Cohn-Kanade dataset and achieve 96.04% in accuracy rate which is better than other state-of-the-art methods.","PeriodicalId":347057,"journal":{"name":"2016 3rd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132032952","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}
Pub Date : 2016-09-01DOI: 10.1109/NICS.2016.7725645
Phai Vu Dinh, Thanh Nguyen Nguyen, Quang Uy Nguyen
In data mining, anomaly detection aims to identify the data samples that do not conform to an expected behavior. Anomaly detection has successfully been applied to many real world applications such as fraud detection for credit cards and intrusion detection in security. However, there are very little research on using anomaly detection techniques to detect cheating in online games. In this paper, we present an empirical study of anomaly detection in online games. Four unsupervised anomaly detection techniques were used to detect abnormal players. A method for evaluating the performance these detection techniques was introduced and analysed. The experiments were conducted on one artificial dataset and two real online games at VNG company. The results show the good capability of detection techniques used in this paper in detecting abnormal players in online games.
{"title":"An empirical study of anomaly detection in online games","authors":"Phai Vu Dinh, Thanh Nguyen Nguyen, Quang Uy Nguyen","doi":"10.1109/NICS.2016.7725645","DOIUrl":"https://doi.org/10.1109/NICS.2016.7725645","url":null,"abstract":"In data mining, anomaly detection aims to identify the data samples that do not conform to an expected behavior. Anomaly detection has successfully been applied to many real world applications such as fraud detection for credit cards and intrusion detection in security. However, there are very little research on using anomaly detection techniques to detect cheating in online games. In this paper, we present an empirical study of anomaly detection in online games. Four unsupervised anomaly detection techniques were used to detect abnormal players. A method for evaluating the performance these detection techniques was introduced and analysed. The experiments were conducted on one artificial dataset and two real online games at VNG company. The results show the good capability of detection techniques used in this paper in detecting abnormal players in online games.","PeriodicalId":347057,"journal":{"name":"2016 3rd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132795102","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}
Pub Date : 2016-09-01DOI: 10.1109/NICS.2016.7725632
Tien-Vu Truong, Nhan-Van Vo, Dac-Binh Ha, Duc-Dung Tran
Nowadays, physical layer secrecy has become the new approach to enhance information security of wireless networks and have attracted the attention of lot of researchers in the world. This paper investigates the physical layer secrecy performance of radio frequency energy harvesting (RF-EH) networks over Rayleigh fading channels. The considered RF-EH system consists of multiple power transfer stations, one source and multiple destinations in the presence of multiple passive eavesdroppers. The best power transfer station and the best received signal at destination is selected among multiple power transfer stations and among multiple destinations respectively. By using statistical characteristics of the signal-to-noise ratio (SNR), the exact closed-form expressions of existence probability of secrecy capacity and secrecy outage probability are derived. Finally, simulation results confirm an agreement between our analysis and equivalent Monte-Carlo simulations.
{"title":"Secrecy performance analysis of energy harvesting wireless networks with multiple power transfer stations and destinations in the presence of multiple eavesdroppers","authors":"Tien-Vu Truong, Nhan-Van Vo, Dac-Binh Ha, Duc-Dung Tran","doi":"10.1109/NICS.2016.7725632","DOIUrl":"https://doi.org/10.1109/NICS.2016.7725632","url":null,"abstract":"Nowadays, physical layer secrecy has become the new approach to enhance information security of wireless networks and have attracted the attention of lot of researchers in the world. This paper investigates the physical layer secrecy performance of radio frequency energy harvesting (RF-EH) networks over Rayleigh fading channels. The considered RF-EH system consists of multiple power transfer stations, one source and multiple destinations in the presence of multiple passive eavesdroppers. The best power transfer station and the best received signal at destination is selected among multiple power transfer stations and among multiple destinations respectively. By using statistical characteristics of the signal-to-noise ratio (SNR), the exact closed-form expressions of existence probability of secrecy capacity and secrecy outage probability are derived. Finally, simulation results confirm an agreement between our analysis and equivalent Monte-Carlo simulations.","PeriodicalId":347057,"journal":{"name":"2016 3rd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131100698","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}
Pub Date : 2016-09-01DOI: 10.1109/NICS.2016.7725671
X. Nguyen, Dai Tho Nguyen, Long H. Vu
In this paper, we propose a novel Payload-based One-class Classifier for Anomaly Detection called POCAD, which combines a generalized 2v-gram feature extractor and a one-class SVM classifier to effectively detect network intrusion attacks. We extensively evaluate POCAD with real-world datasets of HTTP-based attacks. Our experiment results show that POCAD can quickly detect malicious payload and achieves a high detection rate as well as a low false positive rate. The experiment results also show that POCAD outperforms state of the art payload-based detection schemes such as McPAD [4] and PAYL [8].
{"title":"POCAD: A novel pay load-based one-class classifier for anomaly detection","authors":"X. Nguyen, Dai Tho Nguyen, Long H. Vu","doi":"10.1109/NICS.2016.7725671","DOIUrl":"https://doi.org/10.1109/NICS.2016.7725671","url":null,"abstract":"In this paper, we propose a novel Payload-based One-class Classifier for Anomaly Detection called POCAD, which combines a generalized 2v-gram feature extractor and a one-class SVM classifier to effectively detect network intrusion attacks. We extensively evaluate POCAD with real-world datasets of HTTP-based attacks. Our experiment results show that POCAD can quickly detect malicious payload and achieves a high detection rate as well as a low false positive rate. The experiment results also show that POCAD outperforms state of the art payload-based detection schemes such as McPAD [4] and PAYL [8].","PeriodicalId":347057,"journal":{"name":"2016 3rd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS)","volume":"20 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132721136","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}
Pub Date : 2016-09-01DOI: 10.1109/NICS.2016.7725665
Dinh Thanh Le, Thi Nhu Thuong Huynh, T. Nguyen
In this paper, we design two wideband compact MIMO antennas, and utilize them for experiments on indoor channel characteristic measurements. One of the antennas is a three-port orthogonally polarized, and the other is a six-port formed into a cube. The antennas operate at center frequency of 2.6 GHz and support a bandwidth of over 400 MHz. Isolation between the ports of the antennas are kept under -18 dB. Using these antennas, we measure the channel characteristics of the indoor environment, and analyze the performance of the antennas. As a result, high data rate capacity can be achieved with the proposed compact antennas, making them applicable in MIMO wireless communications.
{"title":"Measurements on indoor channel characteristics using wideband MIMO antennas","authors":"Dinh Thanh Le, Thi Nhu Thuong Huynh, T. Nguyen","doi":"10.1109/NICS.2016.7725665","DOIUrl":"https://doi.org/10.1109/NICS.2016.7725665","url":null,"abstract":"In this paper, we design two wideband compact MIMO antennas, and utilize them for experiments on indoor channel characteristic measurements. One of the antennas is a three-port orthogonally polarized, and the other is a six-port formed into a cube. The antennas operate at center frequency of 2.6 GHz and support a bandwidth of over 400 MHz. Isolation between the ports of the antennas are kept under -18 dB. Using these antennas, we measure the channel characteristics of the indoor environment, and analyze the performance of the antennas. As a result, high data rate capacity can be achieved with the proposed compact antennas, making them applicable in MIMO wireless communications.","PeriodicalId":347057,"journal":{"name":"2016 3rd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117183304","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}
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