2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)最新文献_第5页

Real time embedded system IPs protection using chaotic maps 使用混沌映射的实时嵌入式系统ip保护

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8248987

K. Salah

{"title":"Real time embedded system IPs protection using chaotic maps","authors":"K. Salah","doi":"10.1109/UEMCON.2017.8248987","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8248987","url":null,"abstract":"In this paper and for the first time, a novel chaotic maps algorithm is proposed to be used in hardware on-chip security for real-time embedded systems. The aim is to cipher the original program rom by changing the contents and the locations of the original data to ban extracting designs of secure IPs. As we know, many strong ciphers have been applied widely, such as DES, AES and RSA. But most of them cannot be directly used to encrypt real-time embedded systems because their encryption speed is not fast enough and they are computationally intensive. So, in this work we present a fast chaotic-based encryption algorithm which is suitable for real-time embedded systems in terms of performance, area and power efficiency. To illustrate the effectiveness of the proposed algorithm, numerical simulations are presented. Moreover, the proposed chaotic algorithm is implemented using RTL-design. The proposed encryption gives 64 bits of encrypted data per clock cycle. The hardware implementation results give a synthesis clock frequency of 400 MHz and a throughput of 3.2 Gbps while using low area. This makes the proposed algorithm suitable for embedded systems. The RTL implementation results match the Matlab simulation results. The strong structural complexity of our proposed algorithm makes it difficult to predict the key and make it able to resist exhaustive attack, statistical attack and differential attack. All these features show that our proposed algorithm is very suitable for hardware on-chip security for real-time embedded systems. An exhaustive cryptanalysis was completed, allowing us to conclude that the system is secure. Moreover, it is cost-effective solution.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":"1943 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129170371","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

Analyzing the existing noninvasive hemoglobin measurement techniques 分析现有的无创血红蛋白检测技术

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249080

M. Hasan, N. Sakib, Richard R. Love, Sheikh Iqbal Ahamed

{"title":"Analyzing the existing noninvasive hemoglobin measurement techniques","authors":"M. Hasan, N. Sakib, Richard R. Love, Sheikh Iqbal Ahamed","doi":"10.1109/UEMCON.2017.8249080","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249080","url":null,"abstract":"To meet the potential research challenges, such as cost, accuracy, and portability, a number of research has been conducted around the world in the domain of noninvasive measurement techniques. In this paper, we explored, analyzed, and critiqued concurrent research approaches that endeavored to meet the research challenges in noninvasive hemoglobin (Hb) measurement. Here, besides the conventional invasive Hb measurement methods, we covered the Hb measurement techniques based on various scientific contribution and advancement. We studied smartphone-image, IR-LED, and spectra-based solutions as well as noninvasive point-of-care (POC) devices. From that insight, in this paper, we delineated the novel smartphone-based approaches to measure hemoglobin level noninvasively that can leverage the computation, portability, and affordability of smartphone devices, and assure the desired accuracy and consistency. Apart from that, this paper describes how these novel proposals can overcome the limitations of the data collection and analysis in the state-of-the-art approaches in this domain.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130315823","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: 15

A new tree target tracking algorithm in WSNs 一种新的WSNs树目标跟踪算法

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249006

A. Odeh, Eman Abdelfattah

引用次数: 0

Home gateway for RF/PON based gigabit Transmission system for cable network 基于射频/PON的千兆有线网络传输系统的家庭网关

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249046

Joo-Young Lee, Juho Lee, Sungkwon Park, Jaewon Lee, Eunhee Hyun, Junyoung Jung

引用次数: 0

Low-power and high-performance 2.4 GHz RF transmitter for biomedical application 用于生物医学应用的低功耗高性能2.4 GHz射频发射机

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249090

Ahmed Alzahmi, Nahid Mirzaie, Chung-Ching Lin, Gyung-Su Byun

引用次数: 0

Enhancing sink node anonymity in tactical sensor networks using a reactive routing protocol 利用响应路由协议增强战术传感器网络中的汇聚节点匿名性

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249005

Thomas Haakensen, P. Thulasiraman

{"title":"Enhancing sink node anonymity in tactical sensor networks using a reactive routing protocol","authors":"Thomas Haakensen, P. Thulasiraman","doi":"10.1109/UEMCON.2017.8249005","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249005","url":null,"abstract":"Tactical wireless sensor networks (WSNs) are deployed over a region of interest for mission centric operations. The sink node in a tactical WSN is the aggregation point of data processing. Due to its essential role in the network, the sink node is a high priority target for an attacker who wishes to disable a tactical WSN. This paper focuses on the mitigation of sink-node vulnerability in a tactical WSN. Specifically, we study the issue of protecting the sink node through a technique known as k-anonymity. To achieve k-anonymity, we use a specific routing protocol designed to work within the constraints of WSN communication protocols, specifically IEEE 802.15.4. We use and modify the Lightweight Ad hoc On-Demand Next Generation (LOADng) reactive-routing protocol to achieve anonymity. This modified LOADng protocol prevents an attacker from identifying the sink node without adding significant complexity to the regular sensor nodes. We simulate the modified LOADng protocol using a custom-designed simulator in MATLAB. We demonstrate the effectiveness of our protocol and also show some of the performance tradeoffs that come with this method.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122525544","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

Security solutions and design scenarios for software defined data centers 软件定义数据中心的安全解决方案和设计方案

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249071

Sai Manogna Duttaluri, Bijan Karimi

引用次数: 1

Automated facial expression recognition app development on smart phones using cloud computing 基于云计算的智能手机自动面部表情识别应用开发

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249000

Humaid Alshamsi, Veton Këpuska, H. Meng

{"title":"Automated facial expression recognition app development on smart phones using cloud computing","authors":"Humaid Alshamsi, Veton Këpuska, H. Meng","doi":"10.1109/UEMCON.2017.8249000","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249000","url":null,"abstract":"Automated human emotion detection is a topic of significant interest in the field of computer vision. Over the past decade, much emphasis has been on using facial expression recognition (FER) to extract emotion from facial expressions. In this paper, the proposed system presents a novel method of facial recognition based on the cloud model, in combination with the traditional facial expression system. The process of predicting emotions from facial expression images contains several stages. The first stage of this system is the pre-processing stage, which is applied by detecting the face in images and then resizing the images. The second stage involves extracting features from facial expression images using Facial Landmarks and Center of Gravity (COG) feature extraction algorithms, which generate the training and testing datasets that contain the expressions of Anger, Disgust, Fear, Happiness, Neutrality, Sadness, and Surprise. Support Vector Machine (SVM) classifiers are then used for the classification stage in order to predict the emotion. In addition, a Confusion Matrix (CM) technique is used to evaluate the performance of these classifiers. The proposed system is tested on CK+, JAFFE, and KDEF databases. However, the proposed system achieved a prediction rate of 96.3% when Facial Landmarks and the Center of Gravity (COG)+SVM method are used.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114278950","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

An efficient automated technique for epilepsy seizure detection using EEG signals 一种利用脑电图信号进行癫痫发作检测的高效自动化技术

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8248991

Zakareya Lasefr, Sai Shiva V. N. R. Ayyalasomayajula, K. Elleithy

{"title":"An efficient automated technique for epilepsy seizure detection using EEG signals","authors":"Zakareya Lasefr, Sai Shiva V. N. R. Ayyalasomayajula, K. Elleithy","doi":"10.1109/UEMCON.2017.8248991","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8248991","url":null,"abstract":"Epilepsy is a neurological disorder characterized by epileptic seizures. Epileptic seizure can be analyzed through the normal and abnormal activity of the brain. This abnormal activity can be observed only through the use of an efficient algorithm. The process of an efficient algorithm always uses signal processing in which an epileptic signal can be considered as an input signal. This paper introduces a technique to detect epileptic signal and to compare the characteristics of the brain signals at different stages. Our algorithm is based on signal processing techniques to detect epilepsy in the EEG signal. The signal processing starts with sampling the signal at 178.6 Hz so that the signal operating frequency follows oversampling criteria. The sampled signal is given to the designed filter so that the unwanted noise can be removed and the signal is ready to be decomposed. Then, the signal is decomposed at five different signal levels so that its frequency spectrum is reduced to less than 200 Hz using different wavelet filters at each level. In the feature extraction, we have used signal features rather than statistical features so that we can still rely on time domain and frequency domain features for an EEG signal. These features are classified using Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANN) to detect the epilepsy in the EEG signal. The results were demonstrated for different sets of brain signal that show the normal behavior of the brain signals and epileptic behavior of the signal with seizure. A comparison of our work with the present traditional methodologies proves that our algorithm is more efficient in detecting epilepsy.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121805693","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

Eldercare robotics revolution-explaining robotics for eldercare 老年护理机器人革命——解释老年护理机器人

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249030

N. DiMaria, Kristen Tan, Bruno Salgado, Wenkang Su, Gregg Vesonder

引用次数: 2