DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...最新文献_第8页

Secure location tracking of femtocells in heterogeneous cellular networks 异构蜂窝网络中飞蜂窝的安全位置跟踪

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073815

Shin-Ming Cheng, Yu-Jyun Wang, Ying Chen

{"title":"Secure location tracking of femtocells in heterogeneous cellular networks","authors":"Shin-Ming Cheng, Yu-Jyun Wang, Ying Chen","doi":"10.1109/DESEC.2017.8073815","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073815","url":null,"abstract":"To improve indoor coverage and network capacity, deploying low-power and small-coverage femtocells in the coverage of a macrocell as a two-tier heterogeneous network is regarded as the most promising approach. Since femtocells share the same licensed spectrum with a macrocell, severe cross-tier and intra-tier interference from concurrent transmissions is introduced, which causes performance degradation. Under the dense and massive deployment of femtocells, mitigating interference in dynamic and realtime fashions is challenging, particularly when macro-femto backhaul coordination is infeasible. One possible solution is that before the deployment, operator determines the static channels a femtocell at a particular location can exploit, which is regarded as network planning on femtocells. However, the owner of the femtocell might install or move it anywhere without the operator's awareness and permission for high-quality indoor transmission. Such misuse behaviors destruct the extensive planning and explicitly suggest the existence of femtocell positioning mechanism. This paper explores the recent innovations in user positioning, Observed Time Difference of Arrival and verifiable multilateration, to design a secure femtocell location tracking scheme with the aid of macrocells. Performance evaluations show that considerable performance improvement can be achieved, and thus demonstrate the necessity of applying location tracking on planned femtocells for interference control.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"11 1","pages":"267-272"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82840261","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

Combining low-cost Inertial Measurement Unit (IMU) and deep learning algorithm for predicting vehicle attitude 结合低成本惯性测量单元(IMU)和深度学习算法预测车辆姿态

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073847

Jun-Ying Huang, Zhengyu Huang, KuanHung Chen

{"title":"Combining low-cost Inertial Measurement Unit (IMU) and deep learning algorithm for predicting vehicle attitude","authors":"Jun-Ying Huang, Zhengyu Huang, KuanHung Chen","doi":"10.1109/DESEC.2017.8073847","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073847","url":null,"abstract":"In the paper, we propose an acceleration-based and angular-velocity-based vehicle attitude recognition method by using a popular deep learning algorithm, i.e., Convolution Neural Network (CNN). We use an Inertial Measurement Unit (IMU) to collect six-axial signal of a vehicle. In particular, we construct a CNN model to learn the characteristics of six-axial IMU signal and the model can be used to predict vehicle attitudes. We constructed training data consists of 800 package from six attitudes. In addition, we preprocess the 800 package that each package will be broken down. Finally, our training data is 59200 sample-train. The experiment results show that the CNN works well, which can reach an average accuracy of 98% by the time of 1/5 of the overall action without any feature extraction methods. Because we use CNN model that it's the number of convolution kernel is less, we can reach real-time. Each estimated time is less than 0.5 sec based on the raspberry pi3.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"25 1","pages":"237-239"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89091936","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: 12

Computing with obfuscated data in arbitrary logic circuits via noise insertion and cancellation 在任意逻辑电路中，通过噪声的插入和消除对模糊数据进行计算

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073840

Yu-Wei Lee, N. Touba

{"title":"Computing with obfuscated data in arbitrary logic circuits via noise insertion and cancellation","authors":"Yu-Wei Lee, N. Touba","doi":"10.1109/DESEC.2017.8073840","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073840","url":null,"abstract":"In secure computing, sensitive data must be kept private by protecting it from being obtained by an attacker. Existing techniques for computing with encrypted data are either prohibitively expensive (e.g., fully homomorphic encryption) or only work for special cases. (e.g., only for linear circuits). This paper presents a lightweight methodology for computing with noise-obfuscated data by carefully selecting internal locations for noise cancellation in arbitrary logic circuits. Noise is inserted in the data before computation and then partially cancelled during the computation and fully cancelled at the outputs. While the proposed methodology does not provide the level of strong encryption that fully homomorphic encryption would provide, it has the advantage of being lightweight, easy to implement, and can be deployed with relatively minimal performance impact. A key idea in the proposed approach is to reduce the complexity of the noise cancellation logic by carefully selecting internal locations to do local noise canceling. This is done in a way that prevents more than one input per gate from propagating noise thereby avoiding the complexity that arises from reconvergent noise propagation paths. One important application of the proposed scheme is for protecting data inside a computing unit obtained from a third party IP provider where a hidden backdoor access mechanism or hardware Trojan could be maliciously inserted. Experimental results show that noise can be propagated to outputs with overheads ranging from (13%–56%).","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"18 1","pages":"146-152"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82060854","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

Deterministic microcode machine generation 确定性微码机生成

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073858

A. M'zah, B. Monsuez, H. Aboutaleb

{"title":"Deterministic microcode machine generation","authors":"A. M'zah, B. Monsuez, H. Aboutaleb","doi":"10.1109/DESEC.2017.8073858","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073858","url":null,"abstract":"Microcode is a technique that is used to implement internal state machine sequencing in different type of controllers addressing a large range of different applications. It can be used to reduce the functional as well as the internal complexity of a design. A challenge in using microcode based IP-design in IPs that are designed to be used in critical applications is to ensure that the microprogram (i.e. a sequence of microcode instructions) will execute correctly in a possible harsh environment. A lot of work has been published on automatic generation of microcode as well as on proving that microcode generation is correct. However, very little work has been done on ensuring that microcode executes correctly in a harsh environment. In this paper, we propose a new deterministic solution that generates for a given set of valid internal state machine sequences the microcode as well as the embedded verification mechanism that verifies on the fly that the execution of the microcode sequence is correct and that the sequence is a valid sequence.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"1 1","pages":"370-376"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76526349","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

K-binID: Kernel binary code identification for Virtual Machine Introspection K-binID:内核二进制代码识别的虚拟机自省

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073801

Yacine Hebbal, S. Laniepce, Jean-Marc Menaud

{"title":"K-binID: Kernel binary code identification for Virtual Machine Introspection","authors":"Yacine Hebbal, S. Laniepce, Jean-Marc Menaud","doi":"10.1109/DESEC.2017.8073801","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073801","url":null,"abstract":"Virtual Machine Introspection (VMI) techniques generally employ kernel symbols to obtain addresses of kernel data and functions of interest to monitor guest OS states and activities. However, employing kernel symbols in an Infrastructure as a Service (IaaS) cloud presumes perfect knowledge of what kernel version and customization is running in an introspected VM. Moreover, existing kernel fingerprinting techniques are limited in precision and usability due to insufficient coverage of kernel code. So they are not suitable for IaaS cloud. In this paper, we present K-binID, a set of new automatic and OS-independent techniques based on static binary code analysis that enables the hypervisor to precisely identify version and customization of VM main kernel binary code (among a set of known kernels). K-binID achieves this in black-box regardless of challenges presented by compiler optimizations and kernel base address randomization. We designed and implemented our prototype of K-binID on KVM hypervisor. K-binID evaluation on a variety of Linux kernel binary code versions shows that, in 1 to 5 seconds, K-binID identifies precisely both the kernel version and customization of all tested kernels.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"321 1","pages":"107-114"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80232542","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

R2D2: Right place, right path data delivery R2D2:正确的位置，正确的路径数据传递

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073816

Ehab Ashary, C. E. Chow, Ashish Korpe, D. Thorpe

引用次数: 2

Source code transformation for software-based on-line error detection 基于软件的在线错误检测的源代码转换

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073852

Tsung-Yen Tsai, Jiun-Lang Huang

引用次数: 4

Novel designated ownership transfer with grouping proof 具有组证明的新型指定所有权转移

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073863

W. Liew, Kuo-Yu Tsai, Jia-Ning Luo, Ming-Hour Yang

引用次数: 8

Enabling practical experimentation in cyber-security training 开展网络安全培训实践

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073870

Jian Mao, Zheng Leong Chua, Zhenkai Liang

引用次数: 1

Droidrevealer: Automatically detecting Mysterious Codes in Android applications Droidrevealer:自动检测Android应用程序中的神秘代码

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073885

Xinyin Zhang, Yuanye Cao, Mutian Yang, Jingzheng Wu, Tianyue Luo, Yueqin Liu

引用次数: 0