发布求助
文献互助 智能选刊 最新文献

2019 UK/ China Emerging Technologies (UCET)最新文献

筛选
英文 中文
An Effective Android Ransomware Detection Through Multi-Factor Feature Filtration and Recurrent Neural Network 基于多因素特征滤波和递归神经网络的Android勒索软件检测
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881884
I. Bibi, Adnan Akhunzada, Jahanzaib Malik, Ghufran Ahmed, M. Raza
{"title":"An Effective Android Ransomware Detection Through Multi-Factor Feature Filtration and Recurrent Neural Network","authors":"I. Bibi, Adnan Akhunzada, Jahanzaib Malik, Ghufran Ahmed, M. Raza","doi":"10.1109/UCET.2019.8881884","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881884","url":null,"abstract":"with the increasing diversity of Android malware, the effectiveness of conventional defense mechanisms are at risk. This situation has endorsed a notable interest in the improvement of the exactitude and scalability of malware detection for smart devices. In this study, we have proposed an effective deep learning-based malware detection model for competent and improved ransomware detection in Android environment by looking at the algorithm of Long Short-Term Memory (LSTM). The feature selection has been done using 8 different feature selection algorithms. The 19 important features are selected through simple majority voting process by comparing results of all feature filtration techniques. The proposed algorithm is evaluated using android malware dataset (CI-CAndMal2017) and standard performance parameters. The proposed model outperforms with 97.08% detection accuracy. Based on outstanding performance, we endorse our proposed algorithm to be efficient in malware and forensic analysis.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127238453","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: 19
Active Constellation Extension for Peak Power Reduction Based on Positive and Negative Iterations in OFDM Systems 基于正负迭代的OFDM系统峰功率降低主动星座扩展
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881859
Yong Xiao, Lei Zhang, M. Imran
{"title":"Active Constellation Extension for Peak Power Reduction Based on Positive and Negative Iterations in OFDM Systems","authors":"Yong Xiao, Lei Zhang, M. Imran","doi":"10.1109/UCET.2019.8881859","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881859","url":null,"abstract":"Traditional active constellation extension (ACE) techniques iterate under a further and further away from decision boundary constraint to find distortions for peak-to-average power ratio (PAPR) reduction, which may stop the solution on suboptimal points because it's not permitted to go back when running into a suboptimum direction. In this paper, we present a novel ACE technique by iterating in both positive and negative directions, referring to distortions found in the last iteration. During iterations, optimization variations are changed from normally used extra distortions on the last estimates to the primitive OFDM signal, which can eliminate correlations between magnitudes and phases of complex distortions and finally give an analytic solution based on orthogonal projection. By making iterations run in positive and negative directions, this algorithm can find distortions to reduce PAPR more, compared with existing methods. Simulation results show that significant improvement can be achieved either for pure ACE or TR assisted ACE method, especially under higher-order modulation schemes.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116464972","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: 2
A Blockchain-based Secure Internet of Vehicles Management Framework 基于区块链的安全车联网管理框架
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881874
Mohamed Abdur Rahman, Md Mamunur Rashid, S. Barnes, Syed Maruf Abdullah
{"title":"A Blockchain-based Secure Internet of Vehicles Management Framework","authors":"Mohamed Abdur Rahman, Md Mamunur Rashid, S. Barnes, Syed Maruf Abdullah","doi":"10.1109/UCET.2019.8881874","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881874","url":null,"abstract":"In this paper, we propose a secure internet of vehicles (IoV) framework that can handle the transportation ecosystem of a very large and dynamic crowd. The framework will allow personalized and location-aware vehicle IoT data to store in blockchain and off-chain repositories for secure sharing with one's community of interest. As a test case of our proposed application, we have developed distributed smartphone applications that can be interfaced with the OBD-II interface to collect in-vehicle data from the CAN bus of a vehicle and an ambient intelligent environment consisting of IoT devices. The in-vehicle environment can collect vehicle sensory information, process the sensory data within the mobile edge network and store the transactions and the raw sensory data to blockchain and off-chain repositories through secure digital wallets. Finally, we will present our implemented framework and initial test results.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123946796","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: 10
Adversarial ML Attack on Self Organizing Cellular Networks 自组织蜂窝网络的对抗性ML攻击
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881842
Salah-ud-din Farooq, M. Usama, Junaid Qadir, M. Imran
{"title":"Adversarial ML Attack on Self Organizing Cellular Networks","authors":"Salah-ud-din Farooq, M. Usama, Junaid Qadir, M. Imran","doi":"10.1109/UCET.2019.8881842","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881842","url":null,"abstract":"Deep Neural Networks (DNN) have been widely adopted in self-organizing networks (SON) for automating different networking tasks. Recently, it has been shown that DNN lack robustness against adversarial examples where an adversary can fool the DNN model into incorrect classification by introducing a small imperceptible perturbation to the original example. SON is expected to use DNN for multiple fundamental cellular tasks and many DNN-based solutions for performing SON tasks have been proposed in the literature have not been tested against adversarial examples. In this paper, we have tested and explained the robustness of SON against adversarial example and investigated the performance of an important SON use case in the face of adversarial attacks. We have also generated explanations of incorrect classifications by utilizing an explainable artificial intelligence (AI) technique.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125828896","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
Texture Classification using a Hybrid Deep and Handcrafted Features 使用混合深度和手工特征的纹理分类
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881836
Fawad, Muhammad Adeel Asghar, A. Saeed, Muhammad Jamil Khan, Muhammad Zahid, M. Rehman
{"title":"Texture Classification using a Hybrid Deep and Handcrafted Features","authors":"Fawad, Muhammad Adeel Asghar, A. Saeed, Muhammad Jamil Khan, Muhammad Zahid, M. Rehman","doi":"10.1109/UCET.2019.8881836","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881836","url":null,"abstract":"In this paper, we have proposed a hybrid descriptor for the texture classification task. The feature variables are extracted from the approximation coefficients of the image, through a combination of deep neural network and handcrafted feature. The AlexNet along with completed joint scale local binary pattern (CJLBP) is used for illumination, scaling, and orientation invariance description. The wavelet decomposition layer provides robustness against additive white Gaussian noise. The feature dimensionality is reduced by using Principal Component Analysis. We have evaluated our proposed descriptor on the images of Outex texture databases. The experimental results presented in the paper in term of classification accuracy show that our proposed descriptor outperforms state-of-the-art feature extraction scheme.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124962978","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
A New Discriminative Feature Learning for Person Re-Identification Using Additive Angular Margin Softmax Loss 基于加性角边缘软最大损失的人再识别新判别特征学习
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881838
Jie Su, Xiaohai He, L. Qing, Yanmei Yu, Shengyu Xu, Yonghong Peng
{"title":"A New Discriminative Feature Learning for Person Re-Identification Using Additive Angular Margin Softmax Loss","authors":"Jie Su, Xiaohai He, L. Qing, Yanmei Yu, Shengyu Xu, Yonghong Peng","doi":"10.1109/UCET.2019.8881838","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881838","url":null,"abstract":"In this paper, a new end-to-end framework is proposed for person re-identification (re-ID) by combining metric learning and classification. In this new framework, the Additive Angular Margin Softmax is used which imposes an additive angular margin constraint to the target logit on hypersphere manifold. This is aimed to improve the similarity of the intra-class features and the dissimilarity of the inter-class features simultaneously. Compard with the three popular used softmax-based-loss methods, the experiments show that the proposed approach has achieved improved performance on Market1501 and DukeMTMC-reID datasets for person re-ID.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128503008","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: 4
A Study on Beamforming for Coverage of Emergency Areas from UAVs 无人机覆盖应急区域的波束形成研究
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881862
Stefano Bolis, Davide Scazzoli, L. Reggiani, M. Magarini, M. Alam
{"title":"A Study on Beamforming for Coverage of Emergency Areas from UAVs","authors":"Stefano Bolis, Davide Scazzoli, L. Reggiani, M. Magarini, M. Alam","doi":"10.1109/UCET.2019.8881862","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881862","url":null,"abstract":"In this paper we present a study on the use of beamforming (BF) for devices discovery from flying platforms, typically Unmanned Aerial Vehicles (UAVs). This type of application is meant to be exploited in emergency scenarios characterized by the absence of a network infrastructure; the purpose is to search and identify the devices (and consequently the persons) spread in a limited area without the possibility of connecting to a mobile network. The use of an antenna array from the UAV is supposed to increase the sensitivity towards devices with weak signals and/or difficult propagation conditions. Our preliminary results indicate the effectiveness of a scanning method based on BF techniques for discovering and detecting terminals on the ground. The numerical results provide an insight on the capability level of BF solutions in these conditions w.r.t. to the size of the area to be covered.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130032825","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 Survey on Deep Learning for the Routing Layer of Computer Network 计算机网络路由层深度学习研究综述
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881852
Fengling Jiang, K. Dashtipour, A. Hussain
{"title":"A Survey on Deep Learning for the Routing Layer of Computer Network","authors":"Fengling Jiang, K. Dashtipour, A. Hussain","doi":"10.1109/UCET.2019.8881852","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881852","url":null,"abstract":"With recent achievements in deep learning over the past year, many computer and network applications actively used deep learning architectures including convolution neural network and long short-term memory to improve the performance of their approach through them. The computer network used a complex and dynamic system. For example, routing is the main networking tasks in the fields of the communication network and it is widely used to optimize the optimal routing from the original host to the destination host. However, most of the traditional routing protocol is based on the experience of experts. In this paper, we present an overview of deep learning methods for the routing layer in the computer network. Furthermore, this paper discusses reinforcement learning methods about network routing. Finally, we outline a summary of the current state-of-the-art approaches along with some future research directions.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130920049","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: 16
UAV Aided Data Dissemination for Multi-hop Backhauling in RAN 无人机辅助下RAN多跳回程数据传播
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881868
Xiaoyan Shi, J. Thompson, M. Safari, Shenjie Huang, Rongke Liu
{"title":"UAV Aided Data Dissemination for Multi-hop Backhauling in RAN","authors":"Xiaoyan Shi, J. Thompson, M. Safari, Shenjie Huang, Rongke Liu","doi":"10.1109/UCET.2019.8881868","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881868","url":null,"abstract":"Emerging applications in the radio access network (RAN), such as proactive caching and the massive machine type communications, will generate traffic with a Large Volume of data but can tolerate long Transmission Delay (LVTD). Together with a rapid growth of overall traffic demand, traffic with LVTD features brings lots of challenges to the backhaul in RANs. In this paper, we study how to schedule traffic in multi-hop backhaul networks with the help of unmanned aerial vehicles (UAVs), In the proposed system, the UAVs are employed to establish broadband connections with the ground terminals through free-space optical links and serve as data collectors between terrestrial access points so as to alleviate the communication burden on the terrestrial network. Through numerical simulations, it is demonstrated that the novel network scheduling scheme combined with dynamic UAV path planning can provide significant performance gain.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121498872","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
An free of iteration array-error estimation method for multi-channel SAR systems* 多通道SAR系统的无迭代阵列误差估计方法*
2019 UK/ China Emerging Technologies (UCET) Pub Date : 2019-08-01 DOI: 10.1109/UCET.2019.8881869
Lun Ma
{"title":"An free of iteration array-error estimation method for multi-channel SAR systems*","authors":"Lun Ma","doi":"10.1109/UCET.2019.8881869","DOIUrl":"https://doi.org/10.1109/UCET.2019.8881869","url":null,"abstract":"This paper considers the problem of estimating gain-phase and position errors for multi-channel synthetic aperture radar (SAR) systems. In multi-channel SAR systems, the clutter spectrum components within a Doppler bin can be used as calibration sources with known directions. Conventional eigen-structure methods, which iterates alternatively between the self-calibration method for gain-phase error estimation and the least squares method for estimating position errors, may converge to a local optimal solution. In this paper, it is observed that the steering vectors corresponding to a pair of Doppler bins within the same range bin have a rotational relationship. We obtain a new array-error estimation method based on this observation. The method, which obtain the position errors in terms of extracting the rotational matrix in a least square's framework, is proposed via combining the projection matrices corresponding to the paired Doppler bins. The validity of the proposed method is verified by the experimental results of measured four-channel SAR data.","PeriodicalId":169373,"journal":{"name":"2019 UK/ China Emerging Technologies (UCET)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125620267","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信