141 research outputs found

    An E-Passport System with Multi-Stage Authentication : A Casestudy of the Security of Sri Lankaas E-Passport

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    E-passport or Electronic passport is one of the newly established research areas, especially since in the last few years there have been numerous reported attempts of illegal immigration across a number of country borders. Therefore, many countries are choosing to introduce electronic passports for their citizens and to automate the verification process at their border control security. The current e-passport systems are based on two technologies: RFID and Biometrics. New applications of RFID technology have been introduced in various aspects of people2019;s lives. Even though this technology has existed for more than a decade, it still holds considerable security and privacy risks. But together with RFID and biometric technologies an e-passport verification system can reduce fraud, identity theft and will help governments worldwide to improve security at their country borders. In 2017 Sri Lankan government proposed to introduce a new epassport scheme which will contain embedded RFID tags for person identification purpose. Therefore, this paper proposes a novel multi-stage e-passport verification scheme based on watermarking, biometrics and RFID

    Intellectual Property Protection for Deep Learning Models: Taxonomy, Methods, Attacks, and Evaluations

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    The training and creation of deep learning model is usually costly, thus it can be regarded as an intellectual property (IP) of the model creator. However, malicious users who obtain high-performance models may illegally copy, redistribute, or abuse the models without permission. To deal with such security threats, a few deep neural networks (DNN) IP protection methods have been proposed in recent years. This paper attempts to provide a review of the existing DNN IP protection works and also an outlook. First, we propose the first taxonomy for DNN IP protection methods in terms of six attributes: scenario, mechanism, capacity, type, function, and target models. Then, we present a survey on existing DNN IP protection works in terms of the above six attributes, especially focusing on the challenges these methods face, whether these methods can provide proactive protection, and their resistances to different levels of attacks. After that, we analyze the potential attacks on DNN IP protection methods from the aspects of model modifications, evasion attacks, and active attacks. Besides, a systematic evaluation method for DNN IP protection methods with respect to basic functional metrics, attack-resistance metrics, and customized metrics for different application scenarios is given. Lastly, future research opportunities and challenges on DNN IP protection are presented

    Deep Intellectual Property: A Survey

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    With the widespread application in industrial manufacturing and commercial services, well-trained deep neural networks (DNNs) are becoming increasingly valuable and crucial assets due to the tremendous training cost and excellent generalization performance. These trained models can be utilized by users without much expert knowledge benefiting from the emerging ''Machine Learning as a Service'' (MLaaS) paradigm. However, this paradigm also exposes the expensive models to various potential threats like model stealing and abuse. As an urgent requirement to defend against these threats, Deep Intellectual Property (DeepIP), to protect private training data, painstakingly-tuned hyperparameters, or costly learned model weights, has been the consensus of both industry and academia. To this end, numerous approaches have been proposed to achieve this goal in recent years, especially to prevent or discover model stealing and unauthorized redistribution. Given this period of rapid evolution, the goal of this paper is to provide a comprehensive survey of the recent achievements in this field. More than 190 research contributions are included in this survey, covering many aspects of Deep IP Protection: challenges/threats, invasive solutions (watermarking), non-invasive solutions (fingerprinting), evaluation metrics, and performance. We finish the survey by identifying promising directions for future research.Comment: 38 pages, 12 figure

    Enhancing Security to Protect e-passport against Photo Forgery

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    Electronic Passport (e-passport) is one of the results of the electronic revolution in the World; since the passport is the document of the person in terms of identity and nationality and is the property of the country. One of the most important challenges is to protect this document from forgery. The common forgery for the passport is replacing its holder photo. The proposed system concentrates on the security part of the e-passport. It consists of two parts; the first part is hiding of the security code by using steganography and storing the same code in the RFID tag by the issuing country of the epassport. The other part will be operated at the control point of the destination country to make sure of the e-passport validity by checking the hidden code using NFC and verify it with the one in the RFID tag. If the two values are equal, then the system will compute a key using Diffie-Hellman Key Exchange. This key will be used to read the secret information in the tag

    A dual watermarking scheme for identity protection

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    A novel dual watermarking scheme with potential applications in identity protection, media integrity maintenance and copyright protection in both electronic and printed media is presented. The proposed watermarking scheme uses the owner’s signature and fingerprint as watermarks through which the ownership and validity of the media can be proven and kept intact. To begin with, the proposed watermarking scheme is implemented on continuous-tone/greyscale images, and later extended to images achieved via multitoning, an advanced version of halftoning-based printing. The proposed watermark embedding is robust and imperceptible. Experimental simulations and evaluations of the proposed method show excellent results from both objective and subjective view-points

    Digital watermarking and novel security devices

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    EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Towards a more secure border control with 3D face recognition

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    Biometric data have been integrated in all ICAO compliant passports, since the ICAO members started to implement the ePassport standard. The additional use of three-dimensional models promises significant performance enhancements for border control points. By combining the geometry- and texture-channel information of the face, 3D face recognition systems show an improved robustness while processing variations in poses and problematic lighting conditions when taking the photo. This even holds in a hybrid scenario, when a 3D face scan is compared to a 2D reference image. To assess the potential of three-dimensional face recognition, the 3D Face project was initiated. This paper outlines the approach and research results of this project: The objective was not only to increase the recognition rate but also to develop a new, fake resistant capture device. In addition, methods for protection of the biometric template were researched and the second generation of the international standard ISO/IEC 19794-5:2011 was inspired by the project results

    Video and Imaging, 2013-2016

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