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Protecting the privacy of humans in video sequences using a computer vision-based de-identification pipeline
حفاظت از حریم خصوصی افراد در توالی های ویدئویی با استفاده از شناسایی مبتنی بر دید کامپیوتری لوله ای-2017
Article history:Received 12 October 2016Revised 5 May 2017Accepted 27 May 2017Keywords:Privacy protection De-identiﬁcation Computer vision Video processingWe propose a computer vision-based de-identiﬁcation pipeline that enables automated protection of pri- vacy of humans in video sequences through obfuscating their appearance, while preserving the natu- ralness and utility of the de-identiﬁed data. Our pipeline speciﬁcally addresses de-identifying soft and non-biometric features, such as clothing, hair, skin color etc., which often remain recognizable when sim- pler techniques such as blurring are applied. Assuming a surveillance scenario, we combine background subtraction based on Gaussian mixtures with an improved version of the GrabCut algorithm to ﬁnd and segment pedestrians. De-identiﬁcation is performed by altering the appearance of the segmented pedes- trians through the neural art algorithm that uses the responses of a deep neural network to render the pedestrian images in a different style. Experimental evaluation is performed both by automated classiﬁ- cation and through a user study. Results suggest that the proposed pipeline successfully de-identiﬁes a range of hard and soft biometric and non-biometric identiﬁers, including face, clothing and hair.© 2017 Elsevier Ltd. All rights reserved.
Keywords: Privacy protection | De-identification | Computer vision | Video processing
نظارت جمعی و گزینه های سیاست فن آوری: بهبود امنیت ارتباطات خصوصی
سال انتشار: 2017 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 26
افشاگری های اسنودن در سال 2013 شعله بحث شدید در مشروعیت و وسعت عملیات جاسوسی که ناظر بر اینترنت و ارتباطات از راه دور در سراسر جهان بود را شعله ور کرد. حمله مداوم به حوزه خصوصی افراد در سراسر جهان توسط دولت ها و شرکت ها موضوعی است که بطور کافی با استفاده از اقدامات فنی و سازمانی فعلی صورت گرفته است. این مقاله استدلال می کند که به منظور حفظ اینترنت حیاتی و فعال، زیرساخت های اساسی آن باید بطور قابل توجهی تقویت شود. ما تعدادی گزینه های فنی و سیاسی، که به بهبود امنیت در اینترنت کمک می کند،پیشنهاد می کنیم. بر بحث پیرامون رمزگذاری و ناشناخته ، و همچنین در سیاست های مقابله با آسیب پذیری های نرم افزار و سخت افزار و ضعف معماری اینترنت تمرکز دارد.
کلید واژه ها: نظارت | سیاست | رمزگذاری | حریم خصوصی
|مقاله ترجمه شده|
Vision enhancement through single image fog removal
افزایش دید از طریق حذف مه آلود بودن تصویر-2017
Contrast and color of the captured pictures are degraded under foggy weather conditions and this degra- dation is often attributed to attenuation and airlight. To reduce the number of road accidents through vision enhancement in turbid weather, an efficient fog removal technique plays a vital role as fog greatly reduces the visibility and hence affects the computer vision algorithms such as surveillance, tracking and Fog Vision Enhancement System (FVES). In this paper, a novel and effective algorithm is proposed for sin- gle image fog removal that’s capable of handling images of gray and color channels. The proposed algo- rithm introduces Dark Channel Prior (DCP) followed by Weighted Least Square (WLS) and High Dynamic Range (HDR) based fog removal scheme. The qualitative and quantitative analysis is applied for the assessment of defogged images obtained from the proposed methodology and is additionally compared with the different fog removal algorithms to establish its superiority. The foremost dominant advantage of the proposed algorithm is its capability to preserve sharp details whereas maintaining the color quality.© 2016 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Air-light | Contrast gain | Colorfulness index | High Dynamic Range | Weighted Least Square | Transmission map | Dark Channel Prior
A lightweight biometrics based remote user authentication scheme for IoT services
یک راهبرد تایید هویت کاربر مبتنی بر بیومتریک سبک برای خدمات IoT-2017
Article history:Available online 12 January 2017Keywords: Biometrics IoT servicesKey agreementRemote user authentication SecurityUser authentication is becoming crucial in the accelerating Internet of Things (IoT) environment. With IoT several applications and services have been emerging in the areas such as, surveillance, healthcare, security, etc. The services offered can be accessed through smart device applications by the user from anywhere, anytime and anyplace. This makes security and privacy critical to IoT. Moreover, security is paramount in IoT, to enable secure access to the services; multi-factor based authentication can provide high security. In this paper, a lightweight biometric based remote user authentication and key agreement scheme for secure access to IoT services has been proposed. The protocol makes use of lightweight hash operations and XOR operation. The security analysis proves that it is robust against multiple security at- tacks. The formal veriﬁcation is performed using AVISPA tool, which conﬁrms its security in the presence of a possible intruder.© 2017 Elsevier Ltd. All rights reserved.
Keywords: Biometrics | IoT services | Key agreement | Remote user authentication | Security
Big Data and security policies: Towards a framework for regulating the phases of analytics and use of Big Data
سیاست های داده های بزرگ و امنیت: به چارچوبی برای تنظیم مراحل تجزیه و تحلیل و استفاده از داده های بزرگ-2017
computer law & s e c u r i t y review 33 ( 2 0 1 7 ) 309–323 http://dx.doi.org/10.1016/j.clsr.2017.03.002 Available online at www.sciencedirect.com www.compseconline.com/publications/prodclaw.htm A B S T R A C T Big Data analytics in national security, law enforcement and the fight against fraud have the potential to reap great benefits for states, citizens and society but require extra safeguards to protect citizens’ fundamental rights. This involves a crucial shift in emphasis from regulating Big Data collection to regulating the phases of analysis and use. In order to benefit from the use of Big Data analytics in the field of security, a framework has to be developed that adds new layers of protection for fundamental rights and safeguards against erroneous and malicious use. Additional regulation is needed at the levels of analysis and use, and the oversight regime is in need of strengthening. At the level of analysis – the algorithmic heart of Big Data processes – a duty of care should be introduced that is part of an internal audit and external review procedure. Big Data projects should also be subject to a sunset clause. At the level of use, profiles and (semi-) automated decision-making should be regulated more tightly. Moreover, the responsibility of the data processing party for accuracy of analysis – and decisions taken on its basis – should be anchored in legislation. The general and security-specific oversight functions should be strengthened in terms of technological expertise, access and resources. The possibilities for judicial review should be expanded to stimulate the development of case law. © 2017 Dennis Broeders, Erik Schrijvers, Bart van der Sloot, Rosamunde van Brakel, Josta de Hoog & Ernst Hirsch Ballin. Published by Elsevier Ltd. All rights reserved.
Keywords:Big Data | Security | Data protection | Privacy | Regulation | Fraud | Policing | Surveillance | Algorithmic accountability | the Netherlands
Optimal sensor deployment to increase the security of the maximal breach path in border surveillance
استقرار سنسور بهینه برای افزایش امنیت حداکثر مسیر شکست در نظارت بر مرز-2017
Article history:Received 4 May 2014Accepted 7 September 2016Available online 14 September 2016Keywords:OR in defense Border surveillanceWireless sensor networks Bilevel programming Maximal breach pathWireless Sensor Networks (WSN) are based on the collaborative effort of a large number of sensors which are low-cost, low-power, multi-functional small electronic devices. They provide a distributed sensing and monitoring environment for the area of interest and hence are used for applications such as environmen- tal monitoring, border surveillance, and target tracking. In this work we study optimal deployment of WSNs for border surveillance using a static Stackelberg game frame and propose a bilevel optimization model for the optimal deployment of a heterogenous WSN so that the security of the area under con- sideration is increased as much as possible. There are two players in this game: defender and intruder. The defender is the leader and tries to determine the best sensor locations so as to maximize the secu- rity measured in terms of coverage intensity at discretized points in the area. The well-informed intruder assuming the role of the follower is capable of destroying some of the sensors so as to identify the max- imal breach path, which represents the safest path from his perspective and thus increases the chance of being undetected by the sensors. This new approach results in a mixed-integer linear bilevel program- ming formulation that is diﬃcult to solve exactly. Therefore, we propose three Tabu search heuristics and realize computational experiments on a large set of test instances in order to assess their performances.© 2016 Elsevier B.V. All rights reserved.
Keywords: OR in defense | Border surveillance | Wireless sensor networks | Bilevel programming | Maximal breach path
Track me, track me not_ Support and consent to state and private sector surveillance
پیگیری من، من را پیگیری نکن _ پشتیبانی و رضایت نظارت دولتی و خصوصی-2017
The current study examines consent to surveillance and identiﬁes links between support for state surveillance and consent to surveillance by private entities. Contrary to a tendency in academic literature and public debates to consider private and state surveillance as a single phenomenon in terms of methods, magnitude, and practice, ﬁndings show that individuals distinguish between these two types of surveillance when it comes to compliance and consent. Support for state surveillance is much more widespread and does not correlate with consent to private sector surveillance. Furthermore, support and consent to surveillance are rather nuanced, with diﬀerent factors predicting diﬀerent types of surveillance, according to the justiﬁcations and contexts of surveillance methods: Private sector surveillance is predicted by the compensation oﬀered to subjects, factors related to behavior in online social networks and age. With regard to state surveillance- support varies between surveillance as part of the war against terrorism, which is most common and predicted by political trust and support for other types of state surveillance, surveillance for security reasons which is predicted by age, political interest, political orientation and support for anti-terror surveillance, and surveillance in general- which is least common and predicted by religiosity, level of privacy settings in SNS, political trust and anti-terror surveil- lance.
Keywords:Privacy | Surveillance | Consent | Experiment | Security
Mass surveillance and technological policy options_ Improving security of private communications
گزینه های نظارت انبوه و سیاست تکنولوژی _ اصلاح ارتباطات مخفی در امنیت-2017
The 2013 Snowden revelations ignited a vehement debate on the legitimacy and breadth of intelligence operations that monitor the Internet and telecommunications worldwide. The ongoing invasion of the private sphere of individuals around the world by governments and companies is an issue that is handled inadequately using current technological and organizational measures.This article1 argues that in order to retain a vital and vibrant Internet, its basic infrastructure needs to bestrengthened considerably. We propose a number of technical and political options, which would contribute to improving the security of the Internet. It focuses on the debates around end-to-end encryption and anonymization, as well as on policies addressing software and hardware vulnerabilities and weaknesses of the Internet architecture.
Keywords:Surveillance | Policy | Encryption | Privacy
Midgar: Detection of people through computer vision in the Internet of Things scenarios to improve the security in Smart Cities, Smart Towns, and Smart Homes
Midgar: تشخیص مردم از طریق چشم انداز کامپیوتری در اینترنت از شرایط برای بهبود امنیت در شهرهای هوشمند، شهر های کوچک هوشمند و خانه های هوشمند-2017
Article history:Received 28 October 2015 Received in revised form 23 December 2016Accepted 29 December 2016Available online 5 January 2017Keywords: Smart Cities Smart Towns Smart HomesInternet of Things Smart Objects Computer Vision Surveillance SecurityCould we use Computer Vision in the Internet of Things for using pictures as sensors? This is the principal hypothesis that we want to resolve. Currently, in order to create safety areas, cities, or homes, people use IP cameras. Nevertheless, this system needs people who watch the camera images, watch the recording after something occurred, or watch when the camera notifies them of any movement. These are the disadvantages. Furthermore, there are many Smart Cities and Smart Homes around the world. This is why we thought of using the idea of the Internet of Things to add a way of automating the use of IP cameras. In our case, we propose the analysis of pictures through Computer Vision to detect people in the analysed pictures. With this analysis, we are able to obtain if these pictures contain people and handle the pictures as if they were sensors with two possible states. Notwithstanding, Computer Vision is a very complicated field. This is why we needed a second hypothesis: Could we work with Computer Vision in the Internet of Things with a good accuracy to automate or semi-automate this kind of events? The demonstration of these hypotheses required a testing over our Computer Vision module to check the possibilities that we have to use this module in a possible real environment with a good accuracy. Our proposal, as a possible solution, is the analysis of entire sequence instead of isolated pictures for using pictures as sensors in the Internet of Things.© 2016 Elsevier B.V. All rights reserved.
Keywords:Smart Cities | Smart Towns | Smart Homes | Internet of Things | Smart Objects | Computer Vision | Surveillance | Security
Business Finance and Enterprise Management in the Era of Big Data: An introduction
کسب و کار مالی و مدیریت سازمانی در دوران داده های بزرگ: معرفی-2017
On March 10–11, 2016, National Taiwan Normal University, Beijing Tsinghua University, and National Chi Nan University jointly hosted 2016 Global Economics and Management Conference at Taipei and Nantou, Taiwan. The theme of the confer ence is ‘‘Business Finance and Enterprise Management in the Era of Big Data’’. Over recent years, big data has become a key basis for competition. Business enterprises have been gathering data alongside the rise of social media and the Internet, inviting collaboration among formerly walled-off functional units, and even seeking information from external suppliers or customers to create real-time customization. Within the financial services sector, big data strategies have begun to make some impacts in the areas of capital markets using sentiment analysis for trading, risk analytics, and market surveillance etc. Both industry and academia call for the attention on the rising challenges and opportunities presented by big data initiatives. This special issue comprises of ten papers investigating with various facets on the following aspects: utilization of market aggregated information, agency/governance issues and trade facilitation across countries.