2015 IEEE Trustcom/BigDataSE/ISPA最新文献_第8页

Trust Evaluation in Mobile Devices: An Empirical Study 移动设备信任评价的实证研究

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.353

Richard S. Weiss, L. Reznik, Yanyan Zhuang, Andrew Hoffman, Darrel Pollard, Albert Rafetseder, Tao Li, Justin Cappos

{"title":"Trust Evaluation in Mobile Devices: An Empirical Study","authors":"Richard S. Weiss, L. Reznik, Yanyan Zhuang, Andrew Hoffman, Darrel Pollard, Albert Rafetseder, Tao Li, Justin Cappos","doi":"10.1109/Trustcom.2015.353","DOIUrl":"https://doi.org/10.1109/Trustcom.2015.353","url":null,"abstract":"Mobile devices today, such as smartphones and tablets, have become both more complex and diverse. This paper presents a framework to evaluate the trustworthiness of the individual components in a mobile system, as well as the entire system. The major components are applications, devices and networks of devices. Given this diversity and multiple levels of a mobile system, we develop a hierarchical trust evaluation methodology, which enables the combination of trust metrics and allows us to verify the trust metric for each component based on the trust metrics for others. The paper first demonstrates this idea for individual applications and Android-based smartphones. The methodology involves two stages: initial trust evaluation and trust verification. In the first stage, an expert rule system is used to produce trust metrics at the lowest level of the hierarchy. In the second stage, the trust metrics are verified by comparing data from components and a trust evaluation is produced for the combined system. This paper presents the results of two empirical studies, in which this methodology is applied and tested. The first study involves monitoring resource utilization and evaluating trust based on resource consumption patterns. We measured battery voltage, CPU utilization and network communication for individual apps and detected anomalous behavior that could be indicative of malicious code. The second study involves verification of the trust evaluation by comparing the data from two different devices: the GPS location from an Android smartphone in an automobile and the data from an on-board diagnostics (OBD) sensor of the same vehicle.","PeriodicalId":277092,"journal":{"name":"2015 IEEE Trustcom/BigDataSE/ISPA","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126118634","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

uCentive: An Efficient, Anonymous and Unlinkable Incentives Scheme uCentive:一个高效、匿名和不可链接的激励计划

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.423

Milica Milutinovic, Italo Dacosta, A. Put, B. Decker

{"title":"uCentive: An Efficient, Anonymous and Unlinkable Incentives Scheme","authors":"Milica Milutinovic, Italo Dacosta, A. Put, B. Decker","doi":"10.1109/Trustcom.2015.423","DOIUrl":"https://doi.org/10.1109/Trustcom.2015.423","url":null,"abstract":"Incentives systems are widely adopted to encourage user actions or contributions that benefit a service provider or a community. In exchange for their actions, users receive incentive points that can be used to obtain benefits or reputation. However, these systems require users to have a central account associated with all their activities. This approach allows providers to collect vast amounts of users' private information, even if pseudonyms are used. In this paper, we present uCentive, a flexible and efficient incentives scheme that allows users to earn and redeem incentives (uCents) that cannot be linked to their identities or actions. In addition, users can prove, if requested, ownership of their incentives without breaking unlinkability guarantees. uCentive also offers perfect forward unlinkability -- even if the user's secrets are compromised, redeemed uCents cannot be linked together or to the user's identity. Even though our scheme relies on heavy cryptography, experimental evaluation shows that it is adequate for mobile devices such as smartphones. We have also made our uCentive library and prototype apps publicly available for further assessment. In short, we provide a practical privacy-preserving incentives scheme that can eliminate users' growing privacy concerns when using such systems.","PeriodicalId":277092,"journal":{"name":"2015 IEEE Trustcom/BigDataSE/ISPA","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126120005","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

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.565

Muhidin A. Mohamed, M. Oussalah

引用次数: 9

An Energy Efficient Congestion Control Scheme for Multimedia Data in Wireless Sensor Networks 无线传感器网络中多媒体数据的高能效拥塞控制方案

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.518

Kyoungsoo Bok, Eunkyung Ryu, Junho Park, Jaesoo Yoo

引用次数: 1

Securing Network-Assisted Direct Communication: The Case of Unreliable Cellular Connectivity 保护网络辅助直接通信:不可靠蜂窝连接的情况

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.453

A. Ometov, K. Zhidanov, S. Bezzateev, R. Florea, S. Andreev, Y. Koucheryavy

引用次数: 25

A Security Analysis of the Emerging P2P-Based Personal Cloud Platform MaidSafe 新兴p2p个人云平台MaidSafe的安全性分析

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.538

F. Jacob, Jens Mittag, H. Hartenstein

{"title":"A Security Analysis of the Emerging P2P-Based Personal Cloud Platform MaidSafe","authors":"F. Jacob, Jens Mittag, H. Hartenstein","doi":"10.1109/Trustcom.2015.538","DOIUrl":"https://doi.org/10.1109/Trustcom.2015.538","url":null,"abstract":"The emergence of decentralized crypto currencies such as Bitcoin and the success of the anonymizing network TOR lead to an increased interest in peer-to-peer based technologies lately - not only due to the prevalent deployment of mass network surveillance technologies by authorities around the globe. While today's application services typically employ centralized client/server architectures that require the user to trust the service provider, new decentralized platforms that eliminate this need of trust are on their rise. In this paper we critically analyze a fully decentralized alternative to today's digital ecosystem - MaidSafe - that drops most of the commonly applied principles. The MaidSafe network implements a fully decentralized personal data storage platform on which user applications can be built. The network is made up by individual users who contribute storage, computing power and bandwidth. All communication between network nodes is encrypted, yet users only have to remember a username and password. To guarantee these objectives, MaidSafe combines mechanisms such as Self-Authentication, Self-Encryption, and a P2P-based public key infrastructure. This paper provides a condensed description of MaidSafe's key protocol mechanisms, derives the underlying identity and access management architecture, and evaluates it with respect to security and privacy aspects.","PeriodicalId":277092,"journal":{"name":"2015 IEEE Trustcom/BigDataSE/ISPA","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132868190","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

Unblocking Stolen Mobile Devices Using SS7-MAP Vulnerabilities: Exploiting the Relationship between IMEI and IMSI for EIR Access 利用SS7-MAP漏洞解锁被盗移动设备:利用IMEI和IMSI之间的关系进行EIR访问

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.500

S. Rao, S. Holtmanns, Ian Oliver, T. Aura

引用次数: 29

Scalable Massively Parallel Learning of Multiple Linear Regression Algorithm with MapReduce 基于MapReduce的多元线性回归算法的可扩展大规模并行学习

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.560

Moufida Rehab Adjout, F. Boufarès

引用次数: 5

A MapReduce-Based k-Nearest Neighbor Approach for Big Data Classification 基于mapreduce的k近邻大数据分类方法

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.577

Jesús Maillo, I. Triguero, F. Herrera

{"title":"A MapReduce-Based k-Nearest Neighbor Approach for Big Data Classification","authors":"Jesús Maillo, I. Triguero, F. Herrera","doi":"10.1109/Trustcom.2015.577","DOIUrl":"https://doi.org/10.1109/Trustcom.2015.577","url":null,"abstract":"The k-Nearest Neighbor classifier is one of the most well known methods in data mining because of its effectiveness and simplicity. Due to its way of working, the application of this classifier may be restricted to problems with a certain number of examples, especially, when the runtime matters. However, the classification of large amounts of data is becoming a necessary task in a great number of real-world applications. This topic is known as big data classification, in which standard data mining techniques normally fail to tackle such volume of data. In this contribution we propose a MapReduce-based approach for k-Nearest neighbor classification. This model allows us to simultaneously classify large amounts of unseen cases (test examples) against a big (training) dataset. To do so, the map phase will determine the k-nearest neighbors in different splits of the data. Afterwards, the reduce stage will compute the definitive neighbors from the list obtained in the map phase. The designed model allows the k-Nearest neighbor classifier to scale to datasets of arbitrary size, just by simply adding more computing nodes if necessary. Moreover, this parallel implementation provides the exact classification rate as the original k-NN model. The conducted experiments, using a dataset with up to 1 million instances, show the promising scalability capabilities of the proposed approach.","PeriodicalId":277092,"journal":{"name":"2015 IEEE Trustcom/BigDataSE/ISPA","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133112800","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: 73

How to Misuse SMTP over TLS: A Study of the (In) Security of Email Server Communication 如何滥用SMTP over TLS:电子邮件服务器通信的安全性研究

2015 IEEE Trustcom/BigDataSE/ISPA Pub Date : 2015-08-20 DOI: 10.1109/Trustcom.2015.386

Lars Baumgärtner, Jonas Höchst, M. Leinweber, Bernd Freisleben

引用次数: 3