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2017 International Carnahan Conference on Security Technology (ICCST)最新文献

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X-band ubiquitous radar system: First experimental results x波段泛在雷达系统:首次实验结果
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167851
Alvaro Duque de Quevedo, Fernando Ibanez Urzaiz, J. Gismero-Menoyo, A. Asensio-López
This paper presents the first experimental results of an ubiquitous frequency modulated continuous wave (FMCW) radar system demonstrator, working in the 8.75 GHz (X band). This system, which main application is in the area of surface surveillance radars, has been developed within the framework of the project numbered as TEC2014-53815-R (RAD-DAR), and is currently under its field-testing phase. This article presents the demonstrator and describes its main blocks. Subsequently, it focuses on signal acquisition and digitization, to later explain the offline coherent signal processing carried out with the captured data. After this, the document introduces the chosen scenario for the first field tests, and shows the first results of the offline processing, illustrated with Range-Doppler matrices and detection figures. Finally, the paper introduces future work lines, including the development of a radar data processor taking advantage of the achieved strong range-speed association.
本文介绍了工作在8.75 GHz (X波段)的泛在调频连续波(FMCW)雷达系统演示器的首次实验结果。该系统主要应用于地面监视雷达领域,已在编号为TEC2014-53815-R (RAD-DAR)的项目框架内开发,目前处于现场测试阶段。本文介绍了该演示器并描述了其主要模块。随后,重点介绍了信号采集和数字化,随后解释了使用捕获数据进行的离线相干信号处理。在此之后,该文档介绍了第一次现场测试所选择的场景,并显示了离线处理的第一次结果,并用距离-多普勒矩阵和检测图进行说明。最后,本文介绍了未来的工作方向,包括利用已实现的强距离-速度关联的雷达数据处理器的开发。
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引用次数: 6
How to implement EU data protection regulation for R&D on personal data 如何实施欧盟研发个人数据保护条例
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167797
R. Sánchez-Reillo, Ines Ortega-Fernandez, Wendy Ponce-Hernandez, Helga C. Quiros-Sandoval
Biometric R&D has to deal with personal data. From the Universal Declaration of Human Rights, privacy of a human being shall be protected, and this is addressed in different forms in each region of the world. In the case of the European Union, Data Protection Directives, Laws and Regulation have been established, and interpreted in different ways by each European Member State. Such a diversity has pushed the European Union to generate an improved regulation that will be mandatory in 2018. Biometric R&D shall not only comply with the current Directive, but also has to adapt its work to the new Regulation. This work is intended to describe the situation and provide a recommended procedure when having to acquire personal data.
生物识别技术研发必须处理个人数据。根据《世界人权宣言》,人的隐私应受到保护,这在世界各地以不同的形式得到解决。就欧盟而言,数据保护指令、法律和法规已经建立,并由每个欧洲成员国以不同的方式解释。这种多样性促使欧盟制定了一项改进的法规,将于2018年强制实施。生物识别技术研发不仅要遵守现行指令,还必须使其工作适应新法规。这项工作的目的是描述的情况,并提供一个建议的程序,当必须获得个人资料。
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引用次数: 1
Language dependent challenge-based keystroke dynamics 基于语言挑战的击键动力学
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167838
Patrick A. H. Bours, Sukanya Brahmanpally
Keystroke Dynamics can be used as an unobtrusive method to enhance password authentication, by checking the typing rhythm of the user. Fixed passwords will give an attacker the possibility to try to learn to mimic the typing behaviour of a victim. In this paper we will investigate the performance of a keystroke dynamic (KD) system when the users have to type given (English) words. Under the assumption that it is easy to type words in your native language and difficult in a foreign language will we also test the performance of such a challenge-based KD system when the challenges are not common English words, but words in the native language of the user. We collected data from participants with 6 different native language backgrounds and had them type random 8–12 character words in each of the 6 languages. The participants also typed random English words and random French words. English was assumed to be a language familiar to all participants, while French was not a native language to any participant and most likely most participants were not fluent in French. Analysis showed that using language dependent words gave a better performance of the challenge-based KD compared to an all English challenge-based system. When using words in a native language, then the performance of the participants with their mother-tongue equal to that native language had a similar performance compared to the all English challenge-based system, but the non-native speakers had an FMR that was significantly lower than the native language speakers. We found that native Telugu speakers had an FMR of less than 1% when writing Spanish or Slovak words. We also found that duration features were best to recognize genuine users, but latency features performed best to recognize non-native impostor users.
通过检查用户的打字节奏,击键动力学可以作为一种不显眼的方法来增强密码身份验证。固定的密码会让攻击者有可能模仿受害者的打字行为。在本文中,我们将研究当用户必须键入给定的(英语)单词时,击键动态(KD)系统的性能。假设在母语中键入单词很容易,而在外语中键入单词很困难,那么当挑战不是常见的英语单词,而是用户的母语单词时,我们还将测试这种基于挑战的KD系统的性能。我们收集了来自6种不同母语背景的参与者的数据,并让他们在6种语言中每种语言随机输入8-12个字符的单词。参与者还随机输入英语单词和法语单词。英语被认为是所有参与者都熟悉的语言,而法语不是任何参与者的母语,很可能大多数参与者的法语都不流利。分析表明,与全英语挑战系统相比,使用语言相关单词的基于挑战的KD表现更好。当使用母语单词时,母语等于母语的参与者的表现与全英语挑战系统的表现相似,但非母语人士的FMR明显低于母语人士。我们发现母语为泰卢固语的人在写西班牙语或斯洛伐克语单词时的FMR不到1%。我们还发现,持续时间特征最能识别真正的用户,而延迟特征最能识别非本地的冒名顶替用户。
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引用次数: 3
Signal processing on graphs for improving automatic credit card fraud detection 改进信用卡欺诈自动检测的图形信号处理
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167820
L. Vergara, A. Salazar, J. Belda, G. Safont, S. Moral, S. Iglesias
In this paper, several methods based on signal processing on graphs are proposed to improve the performance of credit card fraud detection. The proposed methods consist of a variant of the classic iterative amplitude adjusted Fourier transform (IAAFT) and two methods that we have called iterative surrogate signals on graph algorithms (ISSG). The objective is to generate surrogate samples from the original scarce fraud samples to improve the training of the detectors by lowering the variance of the estimate. A reliable augmentation of the target scarce population of frauds is important considering issues such as labeling cost; algorithm testing; data confidentiality; and constantly changing of patterns in the data streaming source. We have approached several scenarios with different legitimate and non-legitimate transaction ratios showing the feasibility of improving detection capabilities evaluated by means of receiver operating characteristic (ROC) curves and several key performance indicators (KPI) commonly used in financial business.
本文提出了几种基于图上信号处理的方法来提高信用卡欺诈检测的性能。所提出的方法包括经典迭代调幅傅立叶变换(IAAFT)的一种变体和我们称之为迭代替代信号图算法(ISSG)的两种方法。目标是从原始的稀缺欺诈样本中生成代理样本,通过降低估计的方差来改进检测器的训练。考虑到标签成本等问题,可靠地增加目标稀缺的欺诈人口是重要的;算法测试;数据的机密性;以及数据流源中模式的不断变化。我们已经接近了几种具有不同合法和非合法交易比率的场景,这些场景显示了通过接收者操作特征(ROC)曲线和金融业务中常用的几个关键绩效指标(KPI)来评估提高检测能力的可行性。
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引用次数: 18
Humans in the loop: Study of semi-automatic signature recognition based on attributes 人在循环:基于属性的半自动签名识别研究
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167815
D. Morocho, A. Morales, Julian Fierrez, J. Ortega-Garcia
The present work analyzes performance, abilities and contributions of the human being (layman) in semi-automatic signature recognition systems. During the last decade the performance of Automatic Signature Verification systems have been improved based on new machine learning techniques and better knowledge about intraclass and interclass variability of signers. However, there is still room for improvements and some real world applications demands lower error rates. This work analyzes collaborative tools such as crowdsourcing and human-assisted schemes developed to improve Automatic Signature Verification systems. The performance of humans in semi-automatic recognition tasks is directly related to the information provided during the comparisons. How humans can help automatic systems goes from direct forgery detection to semiautomatic attribute labeling. In this work, we present recent advances, analyzing their performance according to the same experimental protocol. The results suggest the potential of comparative attributes as a way to improve Automatic Signature Verification systems.
本文分析了人(外行人)在半自动签名识别系统中的表现、能力和贡献。在过去十年中,基于新的机器学习技术和对签名者类内和类间可变性的更好了解,自动签名验证系统的性能得到了改进。然而,仍然有改进的空间,一些现实世界的应用程序需要更低的错误率。这项工作分析了为改进自动签名验证系统而开发的众包和人工辅助方案等协作工具。人类在半自动识别任务中的表现与在比较过程中提供的信息直接相关。人类如何帮助自动系统从直接的伪造检测到半自动的属性标记。在这项工作中,我们介绍了最近的进展,并根据相同的实验方案分析了它们的性能。结果表明,比较属性作为一种改进自动签名验证系统的方法具有潜力。
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引用次数: 1
Curvelets for contact-less hand biometrics under varied environmental conditions 不同环境条件下的非接触式手部生物识别曲线
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167805
Belén Ríos-Sánchez, Miguel Viana-Matesanz, C. S. Ávila
In this work, the Curvelet transform is proposed as a fairly new feature extraction method for palmprint recognition. Particularly, a multiscale analysis has been performed at four levels, assessing and combining the features extracted at each level in order to find those which better represent the palmprint. Feature matching has been conducted by means of Euclidean distance and Support Vector Machines (SVMs), and comparative results are provided. In addition, a multimodal approach involving the extracted palmprint features and hand geometry features has also been evaluated, obtaining an improvement of the results in relation to monomodal biometrics. Evaluations have been carried out following an evaluation protocol based on the definitions suggested by the ISO/IDE 19795 norm that allows for a fair comparison between the different methods. To this end, images coming from two different contact-less databases, which cover different capturing conditions, have been employed.
本文提出了一种新的掌纹特征提取方法——Curvelet变换。特别是,在四个层次上进行了多尺度分析,评估和组合在每个层次上提取的特征,以找到更好地代表掌纹的特征。利用欧氏距离和支持向量机进行特征匹配,并给出对比结果。此外,还对一种涉及提取掌纹特征和手部几何特征的多模态方法进行了评估,获得了相对于单模态生物识别的改进结果。评估是根据ISO/IDE 19795规范建议的定义制定的评估协议进行的,该协议允许在不同方法之间进行公平比较。为此,采用了来自两个不同的非接触式数据库的图像,这些数据库涵盖了不同的捕获条件。
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引用次数: 3
CIC-AB: Online ad blocker for browsers CIC-AB:浏览器的在线广告拦截器
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167846
Arash Habibi Lashkari, A. Seo, G. Gil, A. Ghorbani
Online advertisements (ads) have taken over the web, nowedays most websites contain some sort of ads. While ads produce revenue for the server maintainer or to businesses, they have become intrusive and dangerous as ever. The ads use more bandwidth, show inappropriate content, and spread malware such as adware and ransomware. Although there are many products to block ads, also known as ad blockers, most depend on static filter lists that must be managed manually and frequently updated. When malicious advertisers can produce millions of new URLs within minutes, this is not the most effective method against ads. In this paper we propose our own ad blocker, CIC-AB, which uses machine learning techniques to detect new and unknown ads without needing to update a filter list. The proposed ad blocker has been developed as an extension for the common browsers (e.g. Firefox and Chrome). It classifies URLs, both HTTP and HTTPS, as: non-ad, normal-ad and malicious-ad. The analysis showed the average precision, recall and False Positive rate of CIC-AB for five classifiers namely; Naive Bayes (NB), Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Random Forest (RF) and Decision Tree (DT) is 97.16%, 94.96% and 3.38% respectively.
在线广告(广告)已经接管了网络,现在大多数网站都包含某种形式的广告。虽然广告为服务器维护人员或企业带来收入,但它们已经变得侵入性和危险性一如既往。这些广告占用更多的带宽,展示不适当的内容,并传播恶意软件,如广告软件和勒索软件。虽然有许多产品可以阻止广告,也被称为广告拦截器,但大多数依赖于必须手动管理和经常更新的静态过滤列表。当恶意广告商可以在几分钟内产生数百万个新url时,这并不是对抗广告的最有效方法。在本文中,我们提出了我们自己的广告拦截器CIC-AB,它使用机器学习技术来检测新的和未知的广告,而无需更新过滤列表。拟议的广告拦截器已开发为一个扩展,为常见的浏览器(如Firefox和Chrome)。它将HTTP和HTTPS url分类为:非广告、正常广告和恶意广告。分析表明,5种分类器的平均准确率、查全率和假阳性率分别为:朴素贝叶斯(NB)、支持向量机(SVM)、k近邻(KNN)、随机森林(RF)和决策树(DT)分别为97.16%、94.96%和3.38%。
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引用次数: 22
Accurate multi-target surveillance system over wide areas 广域精确多目标监视系统
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167853
Francisco-Javier Romero-Paisano, F. Pérez-Martínez, Susan Martínez-Cordero, J. Calvo-Gallego
The article presents an accurate system for surveillance purposes of multiple targets in wide areas. The surveillance system is based on a GB-ROSAR (Ground-Based-Rotating Synthetic Aperture Radar). It is a fixed radar with the ability of obtaining images by synthesizing the radiating aperture by a circular movement of the antenna. The prototype makes use of FM-CW (Frequency-Modulated Continuous-Wave) signals, operating in millimeter wave bands. The system has been developed with low cost devices. The objective of this work is to show, through simulations and experimental results, the real possibilities of this type of systems in the setting of precise surveillance of several targets simultaneously over wide areas. This study contains the design and construction of the proposed surveillance system, the implemented signal processing, the obtained results and its interpretation, and the conclusions about this work.
本文提出了一种适用于大范围内多目标监视的精确系统。监视系统基于GB-ROSAR(地基旋转合成孔径雷达)。它是一种固定雷达,能够通过天线的圆周运动合成辐射孔径来获取图像。原型机使用FM-CW(调频连续波)信号,工作在毫米波波段。该系统采用低成本设备开发。这项工作的目的是通过模拟和实验结果来展示这种类型的系统在广泛区域内同时对几个目标进行精确监视的真正可能性。本研究包含了所提出的监控系统的设计和构建,实现的信号处理,获得的结果及其解释,以及关于本工作的结论。
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引用次数: 1
SoTRAACE — Socio-technical risk-adaptable access control model SoTRAACE -社会技术风险适应性访问控制模型
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167835
Pedro Moura, Paulo A. P. Fazendeiro, Pedro Marques, A. Ferreira
Within the necessary security requirements, access control measures are essential to provide adequate means to protect data from unauthorized accesses. However, current and traditional solutions are commonly based on predefined access policies and roles and are therefore inflexible by assuming uniform access control decisions through people's different type of devices, environments and situational conditions, and across enterprises, location and time. We live in an age of the mobile paradigm of anytime/anywhere access as the smartphone is the most ubiquitous device that people now hold. In this new age, access control models need to determine adaptable access decisions based on multiple factors aggregated at the moment of request and not just perform a predefined comparison of attributes. This paper presents a new access control model: SoTRAACE — Socio-Technical Risk-Adaptable Access Control Model. This model aggregates attributes from various domains to help performing a risk assessment that is balanced against the operational needs at the moment of each request, so to provide the most accurate and secure access decision. As a proof of concept, SoTRAACE is used to model and compare two different use case scenarios in the healthcare sector.
在必要的安全需求范围内,访问控制措施对于提供足够的手段来保护数据免受未经授权的访问是必不可少的。然而,当前和传统的解决方案通常基于预定义的访问策略和角色,因此不灵活,因为它们假定通过人们不同类型的设备、环境和情景条件,以及跨企业、跨地点和跨时间的统一访问控制决策。我们生活在一个随时随地访问的移动范式时代,因为智能手机是人们现在拥有的最普遍的设备。在这个新时代,访问控制模型需要根据请求时刻聚合的多个因素确定适应性访问决策,而不仅仅是执行预定义的属性比较。本文提出了一种新的访问控制模型:SoTRAACE -社会技术风险适应性访问控制模型。该模型聚合了来自不同领域的属性,以帮助执行风险评估,该评估与每个请求时刻的操作需求相平衡,从而提供最准确和最安全的访问决策。作为概念验证,SoTRAACE用于对医疗保健部门的两种不同用例场景进行建模和比较。
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引用次数: 12
Generation and evaluation of synthetic models for training people detectors 人员检测器训练综合模型的生成与评价
Pub Date : 2017-10-01 DOI: 10.1109/CCST.2017.8167818
Rafael Martin Nieto, Jesus Molina Merchan, Álvaro García-Martín, J. Sanchez
There is a large demand in the area of video-surveillance, especially in people detection, which has caused a large increase in the number of researches and resources in this field. As training images and annotations are not always available, it is important to consider the cost involved in creating the detector models. For example, for elderly people detection, the detector must have into account different positions such as standing, sitting, in a wheelchair, etc. Therefore, this work has the main objective of reducing the amount of resources needed to generate the detection model, saving the cost of having to record new sequences and generate the associated annotations for a detector training. To achieve this, three synthetic image datasets have been created in order to train three different models, evaluating which model is optimal and finally analyzing its feasibility by comparing it with a people detector for wheelchair users trained with real images. Other people detection scenarios in which this technique could be applied are, for example, people riding horses or motorbikes, or people carrying supermarket carts. The synthetic datasets have been generated by combining images of standing people with wheelchair images, combining image patches, and segmenting sections of people (trunk, legs, etc.) to add them to the wheelchair image. As expected, the obtained results have a reduction of efficiency (between 21 and 25%) in exchange for the enormous saving in human annotation and resources to record real images.
在视频监控领域,特别是在人员检测方面有着巨大的需求,这导致了该领域的研究和资源的大量增加。由于训练图像和注释并不总是可用的,因此考虑创建检测器模型所涉及的成本是很重要的。例如,对于老年人的检测,探测器必须考虑到不同的位置,如站着、坐着、坐在轮椅上等。因此,这项工作的主要目标是减少生成检测模型所需的资源量,节省必须记录新序列并为检测器训练生成相关注释的成本。为了实现这一目标,我们创建了三个合成图像数据集来训练三个不同的模型,评估哪一个模型是最优的,最后通过将其与使用真实图像训练的轮椅使用者的人检测器进行比较,分析其可行性。其他可以应用该技术的人员检测场景,例如,骑马或骑摩托车的人,或推着超市购物车的人。合成数据集是通过将站立的人图像与轮椅图像结合,结合图像patch,对人的部分(躯干、腿部等)进行分割添加到轮椅图像中生成的。正如预期的那样,获得的结果降低了效率(在21%到25%之间),以换取大量节省人工注释和记录真实图像的资源。
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引用次数: 0
期刊
2017 International Carnahan Conference on Security Technology (ICCST)
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