2017 12th International Conference on Computer Engineering and Systems (ICCES)最新文献_第4页

Radar false alarm processing using proposed algorithm for Xampling and compressive sensing 采用所提出的算法对雷达虚警进行采样和压缩感知处理

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275267

M. Hossiny, Sameh G. Salem, F. Ahmed, K. Moustafa

引用次数: 1

Digital signature and authentication mechanisms using new customized hash function for cognitive radio networks 基于自定义哈希函数的认知无线网络数字签名和认证机制

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275299

John N. Soliman, T. A. Mageed, H. El-Hennawy

{"title":"Digital signature and authentication mechanisms using new customized hash function for cognitive radio networks","authors":"John N. Soliman, T. A. Mageed, H. El-Hennawy","doi":"10.1109/ICCES.2017.8275299","DOIUrl":"https://doi.org/10.1109/ICCES.2017.8275299","url":null,"abstract":"Wireless technologies, applications and services have been witnessed a rapid growth in the past few years, due to this development, spectrum scarcity and shortage has become a major concern, several spectrum portions of the static allocated licensed bands are under-utilized. Cognitive radio networks (CRNs) are considered to be the most promising solution in improving the spectrum utilization and solving the spectrum scarcity by providing licensed spectrum portions to unlicensed users, however due to nature of these networks, CRNs are exposed to different types of threats and attacks from different malicious users, which can affect the network availability and performance, in this paper a proposed authentication mechanisms and digital signature scheme applied using new customized hash function for CRNs, the proposed model simulated and tested to provide both primary and secondary users data authentication, data integrity and non-repudiation in CRNs, achieving a defend strategy from the well-known attacks that could be launched by malicious, selfish users, threats and vulnerabilities in CRNs.","PeriodicalId":170532,"journal":{"name":"2017 12th International Conference on Computer Engineering and Systems (ICCES)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129184430","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

Efficient energy management technique for WSNs 无线传感器网络的高效能量管理技术

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275289

Samah Kamel, Tamer F. Ghanem, K. M. Amin, H. Abdelkader

引用次数: 0

Efficient image segmentation of RGB-D images RGB-D图像的高效分割

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275331

Islam I. Fouad, S. Rady, M. Mostafa

引用次数: 1

Enhancing accuracy and security of ADS-B via MLAT assisted-flight information system 利用MLAT辅助飞行信息系统提高ADS-B的准确性和安全性

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275300

Ahmed Abdel Wahab El Marady

引用次数: 10

FPGA based energy detection spectrum sensing for cognitive radios under noise uncertainty 基于FPGA的认知无线电噪声不确定性能量检测频谱感知

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275374

M. Fouda, A. S. Eldien, H. Mansour

{"title":"FPGA based energy detection spectrum sensing for cognitive radios under noise uncertainty","authors":"M. Fouda, A. S. Eldien, H. Mansour","doi":"10.1109/ICCES.2017.8275374","DOIUrl":"https://doi.org/10.1109/ICCES.2017.8275374","url":null,"abstract":"To improve the efficiency of bandwidth usage, the cognitive radios concept has emerged. Spectrum sensing is a pivotal function in cognitive radio systems so that the secondary users can be able to access the free spectrum holes without interfering with primary users. Energy detection is the most common and easiest spectrum sensing technique for cognitive radios. In this paper, the conventional energy detection receiver operating characteristic curve and performance metrics are simulated under additive white Gaussian noise (AWGN) environment by using Monte Carlo simulation. Also, the performance of energy detection is analyzed under different types of M-ary modulation. The analysis of performance will carry the assumption of noise uncertainty. This performance gain is compared with conventional energy detection without any noise effect. In addition, the relation between a number of samples and signal to noise ratio wall (SNR wall) is provided and simulated. The simulation tool used in the analysis is MATLAB software. Finally, the implementation of energy detection technique in the time domain and frequency domain is designed on Xilinx Spartan-3E (XC3S500E-FG320) Field Programmable Gate Array (FPGA) kit by using Verilog language and Xilinx ISE Simulator version 14.1.","PeriodicalId":170532,"journal":{"name":"2017 12th International Conference on Computer Engineering and Systems (ICCES)","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114449071","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: 8

A low computation message delivery and authentication VANET protocol 一种低计算量的消息传递和认证VANET协议

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275303

Islam Z. Ahmed, Taha M. Mohamed, R. Sadek

引用次数: 6

Evaluation of cisplatin efficiency as a chemotherapeutic drug based on neural networks optimized by genetic algorithm 基于遗传算法优化神经网络的顺铂化疗疗效评价

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275391

A. Sahlol, Yasmine S. Moemen, A. Ewees, A. Hassanien

引用次数: 11

Attacks detection in SCADA systems using an improved non-nested generalized exemplars algorithm 基于改进的非嵌套广义示例算法的SCADA系统攻击检测

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275377

H. Kholidy, Ali Tekeoglu, Stefano Iannucci, S. Sengupta, Qian Chen, S. Abdelwahed, John Hamilton

{"title":"Attacks detection in SCADA systems using an improved non-nested generalized exemplars algorithm","authors":"H. Kholidy, Ali Tekeoglu, Stefano Iannucci, S. Sengupta, Qian Chen, S. Abdelwahed, John Hamilton","doi":"10.1109/ICCES.2017.8275377","DOIUrl":"https://doi.org/10.1109/ICCES.2017.8275377","url":null,"abstract":"Supervisory Control and Data Acquisition (SCADA) systems became vital targets for intruders because of the large volume of its sensitive data. The Cyber Physical Power Systems (CPPS) is an example of these systems in which the deregulation and multipoint communication between consumers and utilities involve large volume of high speed heterogeneous data. The Non-Nested Generalized Exemplars (NNGE) algorithm is one of the most accurate classification techniques that can work with such data of CPPS. However, NNGE algorithm tends to produce rules that test a large number of input features. This poses some problems for the large volume data and hinders the scalability of any detection system. In this paper, we introduce our new Feature Selection and Data Reduction Method (FSDRM) to improve the classification accuracy and speed of the NNGE algorithm and to reduce the computational resource consumption. FSDRM provides the following functionalities: (1) it reduces the dataset features by selecting the most significant ones, (2) it reduces the NNGE's hyperrectangles classifiers. The experiments show that the FSDRM reduces the NNGE hyperrectangles by 29.06%, 37.34%, and 26.76% and improves the classification accuracy of the NNGE by 8.57%, 4.19%, and 3.78% using the Multi, Binary, and Triple class datasets respectively.","PeriodicalId":170532,"journal":{"name":"2017 12th International Conference on Computer Engineering and Systems (ICCES)","volume":"641 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121988716","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

Impact of process variability on FinFET 6T SRAM cells for physical unclonable functions (PUFs) 工艺可变性对物理不可克隆功能(puf)的FinFET 6T SRAM单元的影响

2017 12th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2017-12-01 DOI: 10.1109/ICCES.2017.8275272

M. Faragalla, M. Ewais, H. Ragai, M. S. Badran, H. Issa

引用次数: 2