بازیابی تصویر رمزگذاری شده در محیط ابر
ترجمه نشده

بازیابی تصویر رمزگذاری شده در محیط ابر

عنوان فارسی مقاله: به سمت بازیابی تصویر رمزگذاری شده کارآمد در محیط ابر
عنوان انگلیسی مقاله: Toward Efficient Encrypted Image Retrieval in Cloud Environment
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: مهندسی کامپیوتر
گرایش های تحصیلی مرتبط: مهندسی الگوریتم و محاسبات، امنیت اطلاعات، رایانش ابری
کلمات کلیدی فارسی: بازیابی تصویر مبتنی بر محتوا، بازیابی تصویر رمزگذاری شده، نمودار جهانی قابل مرور کوچک، شاخص امن
کلمات کلیدی انگلیسی: Content-based image retrieval, encrypted image retrieval, navigable small world graph, secure index
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2957497
دانشگاه: College of Computer Science and Technology, Jilin University, Changchun 130012, China
صفحات مقاله انگلیسی: 10
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.641 در سال 2018
شاخص H_index: 56 در سال 2019
شاخص SJR: 0.609 در سال 2018
شناسه ISSN: 2169-3536
شاخص Quartile (چارک): Q2 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E14077
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

I. Introduction

II. Related Work

III. Problem Formulation

IV. Secure Image Search Scheme

V. Security Analysis

Authors

Figures

References

بخشی از مقاله (انگلیسی)

Abstract

Outsourcing image search services to public clouds is an ever-increasing trend. However, directly outsourcing image datasets to untrusted clouds introduces privacy concerns. Several secure image retrieval schemes have been proposed recently. However, most of them require participation from image owners when building secure indexes, which wastes many computational resources of the image owners. Several schemes are proposed to solve this problem, but they suffer from low search accuracy on large datasets. In this paper, we propose the first secure image retrieval scheme that simultaneously solves these two problems. To obtain higher search accuracy, we extract image features via fine-tuned convolutional neural networks. Then, the image features are encrypted by using the secure k-Nearest Neighbor algorithm. To improve search speed and reduce the cost of image owners, we let cloud servers locally build a secure hierarchical index graph by using the encrypted image features. Besides, the secure index can be built and updated in parallel. We provide security analysis for the proposed scheme. Performance evaluations on the CIFAR-10 dataset show that the proposed scheme is practical. Moreover, compared with a recent scheme, our scheme can save more index construction time and cost of image owners when building secure indexes.

Introduction

With the rapid development of multimedia devices, a great many images are created every day. Image retrieval is a promising technology that helps us quickly find the images we are interested in. Content-based image retrieval (CBIR) plays a vital role in image retrieval. CBIR aims to use the visual content of a query image to search similar images from an image database, which is useful in many fields, such as remote diagnosis [1], face recognition [2], and online shopping [3]. Concerning the huge storage and the complicated maintenance cost, more and more image owners prefer to outsource huge image datasets and image search services to public clouds. Then, authorized users can retrieve similar images from the clouds. Unfortunately, although the public clouds reduce the cost of the image owners, they also introduce new security threats [4]. Since the outsourced image datasets may contain sensitive information, directly outsourcing the image datasets to untrusted cloud servers may cause the sensitive images to be stolen by commercial opponents, hackers, and cloud providers. Using traditional cryptosystems to protect the images can avoid the disclosure of the sensitive information, but the public clouds can no longer provide image search services.