基于边缘计算的支持多密钥的加密图像检索

doi:10.11959/j.issn.1000-436x.2020086

通信学报 ›› 2020, Vol. 41 ›› Issue (4): 14-26.doi: 10.11959/j.issn.1000-436x.2020086

所属专题：边缘计算

• 专题：边缘计算关键技术 • 上一篇下一篇

基于边缘计算的支持多密钥的加密图像检索

李颖莹^1,²,马建峰^1,²,苗银宾¹

¹ 西安电子科技大学网络与信息安全学院，陕西西安 710071
² 陕西省网络与系统安全重点实验室，陕西西安 710071

修回日期:2020-03-26 出版日期:2020-04-25 发布日期:2020-04-30
作者简介:李颖莹（1995- ），女，陕西汉中人，西安电子科技大学博士生，主要研究方向为数据隐私保护、云计算安全|马建峰（1963- ），男，陕西西安人，博士，西安电子科技大学教授、博士生导师，主要研究方向为计算机系统安全、移动与无线安全、系统可生存性和可信计算|苗银宾（1988- ），男，河南驻马店人，博士，西安电子科技大学讲师，主要研究方向为应用密码学、无线网络安全
基金资助:
促进海峡两岸科技合作联合基金资助项目(U1405255);陕西省科技统筹创新工程计划基金资助项目(2016KTZDGY05-06);中央高校基本科研业务费基金资助项目(JB191506);国家自然科学基金资助项目(61702404);国家自然科学基金资助项目(61702105);国家自然科学基金资助项目(U1804263);国家自然科学基金资助项目(61972094);陕西省自然科学基金资助项目(2019JQ-005);中国博士后科学基金资助项目(2017M613080)

Encrypted image retrieval in multi-key settings based on edge computing

Yingying LI^1,²,Jianfeng MA^1,²,Yinbin MIAO¹

¹ School of Cyber Engineering,Xidian University,Xi’an 710071,China
² Shaanxi Key Laboratory of Network and System Security,Xi’an 710071,China

Revised:2020-03-26 Online:2020-04-25 Published:2020-04-30
Supported by:
The Key Program of NSFC Grant(U1405255);Shannxi Science ＆ Technology Coordination ＆ Innovation Project(2016KTZDGY05-06);Fundamental Research Funds for the Central Universities(JB191506);The National Natural Science Foundation of China(61702404);The National Natural Science Foundation of China(61702105);The National Natural Science Foundation of China(U1804263);The National Natural Science Foundation of China(61972094);The Natural Science Foundation of Shannxi Province(2019JQ-005);China Postdoctoral Science Foundation Funded Project(2017M613080)

摘要/Abstract

摘要：

针对现有加密图像检索方案未考虑不同密钥加密图像集的情况，基于局部敏感哈希、安全近邻及代理重加密技术提出了基于边缘计算的支持多密钥的加密图像检索系统（包含基础方案和改进方案）。所提方案不但提高了图像查询效率、精度，而且降低了查询用户的额外计算开销。安全性分析表明，所提基础方案仅可抵抗已知密文攻击，而所提改进方案可抵抗已知背景攻击。基于实际数据集的实验性能测试表明，所提方案在实际应用场景中是可行的。

关键词: 多密钥, 局部敏感哈希, 代理重加密, 已知密文攻击, 已知背景攻击

Abstract:

Aiming at the fact that the existing encrypted image retrieval schemes do not consider different keys to encrypt images,a multi-key encrypted image retrieval system based on edge computing (including basic scheme and enhanced scheme) based on local sensitive hashing,secure nearest neighbor and proxy re-encryption technologies was proposed.The retrieval efficiency and accuracy were improved and the extra computational cost of query users was reduced.Security analysis shows that the basic scheme can only resist the known ciphertext attack,while the enhanced scheme can resist the known background attack.The experimental performance test based on the real-world dataset shows that the proposed schemes are feasible in practical application scenarios.

Key words: multi-key, locality sensitive hashing, proxy re-encryption, known ciphertext attack

中图分类号:

TP309

李颖莹,马建峰,苗银宾. 基于边缘计算的支持多密钥的加密图像检索[J]. 通信学报, 2020, 41(4): 14-26.

Yingying LI,Jianfeng MA,Yinbin MIAO. Encrypted image retrieval in multi-key settings based on edge computing[J]. Journal on Communications, 2020, 41(4): 14-26.

图/表 14

图1

表1

图2

表2

符号定义"

符号	定义
$M ={m_{t}}_{t = 1}^{n} = {M_{i}}_{i = 1}^{w}$	明文图像集
$C = {c_{t}}_{t = 1}^{n} = {C_{i}}_{i = 1}^{w}$	加密图像集
$K = {k_{i}}_{i = 1}^{w}$	图像加密密钥集
$I = {I_{i}}_{i = 1}^{w}$	安全索引集
$Λ = {Λ_{i}}_{i = 1}^{w}$	重加密密钥集
TD	陷门

表2

图3

表3

第j个哈希表"

桶值	图像信息
${BKT}_{i, j}^{1}$	$(ID (m_{i, 1}), f_{i, 1}), (ID (m_{i, 12}), f_{i, 12}), (ID (m_{i, 35}), f_{i, 35}), \dots$
${BKT}_{i, j}^{2}$	$(ID (m_{i, 7}), f_{i, 7}), (ID (m_{i, 24}), f_{i, 24}), (ID (m_{i, 67}), f_{i, 67}), \dots$
#	#
${BKT}_{i, j}^{N_{i, j}}$	$(ID (m_{i, 16}), f_{i, 16}), (ID (m_{i, 28}), f_{i, 28}), (ID (m_{i, 49}), f_{i, 49}), \dots$

表3

表4

加密后的第j个哈希表"

加密桶值	图像信息
$φ ({BKT}_{i, j}^{1})$	$(ID (m_{i, 1}), {f^{'}}_{i, 1}), (ID (m_{i, 12}), {f^{'}}_{i, 12}), (ID (m_{i, 35}), {f^{'}}_{i, 35}), \dots$
$φ ({BKT}_{i, j}^{2})$	$(ID (m_{i, 7}), {f^{'}}_{i, 7}), (ID (m_{i, 24}), {f^{'}}_{i, 24}), (ID (m_{i, 67}), {f^{'}}_{i, 67}), \dots$
#	#
$φ ({BKT}_{i, j}^{N_{i, j}})$	$(ID (m_{i, 16}), {f^{'}}_{i, 16}), (ID (m_{i, 28}), {f^{'}}_{i, 28}), (ID (m_{i, 49}), {f^{'}}_{i, 49}), \dots$

表4

表5

3种方案的理论计算开销对比"

方案	KeyGen	KeyTrans	IndexGen	TrapdoorGen	Serach
基础方案	$2 G + r Z_{p} + 2 {d^{'}}^{2}$	(w+2)G+wG_T	(λLH+2M′)n	λLH +2M′	2d′ ²n+r′E
改进方案	$2 G + r Z_{p} + 2 {d^{″}}^{2}$	(w 2)+ G+wG_T	(λLH+2M′′)n	λLH +2M′′	2d′′ ²n+r′E
MIPP	(2+3d)wG_q	—	ndpG _q	dpG _q	n(2G_q+G_q)

表5

表6

3种方案的理论存储开销对比"

方案	KeyGen	KeyTrans	IndexGen	TrapdoorGen
基础方案	$2 \| G \| + (w + 2) \| Z_{p} \| + 2 d^{'} (d^{'} + 1) + (L + 1) d$	$(w + 1) \| G \| + w \| G_{T} \|$	$2 d^{'} n \| Z_{p} \|$	$2 d^{'} \| Z_{p} \|$
改进方案	$2 \| G \| + (w + 2) \| Z_{p} \| + 2 d^{″} (d^{″} + 1) + (L + 1) d$	$(w + 1) \| G \| + w \| G_{T} \|$	$2 d^{″} n \| Z_{p} \|$	$2 d^{″} \| Z_{p} \|$
MIPP	$w (d \| Z_{q} \| + \| Z_{p} \|) + \| G_{p} \|$	—	$2 n \| G_{q} \|$	$2 \| G_{q} \|$

表6

图4

图5

图6

图7

图8

参考文献 32

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方案	多密钥加密图像	访问控制	已知背景攻击安全	高效率
文献[3]方案	√	√	√	×
文献[9]方案	×	×	√	×
文献[10]方案	×	×	×	√
文献[11]方案	×	√	√	√
文献[12]方案	×	√	√	√
文献[13]方案	√	×	√	×
文献[18]方案	√	×	√	√
本文方案	√	√	√	√

方案	KeyGen	KeyTrans	IndexGen	TrapdoorGen
基础方案	$2 \| G \| + (w + 2) \| Z_{p} \| + 2 d^{'} (d^{'} + 1) + (L + 1) d$	$(w + 1) \| G \| + w \| G_{T} \|$	$2 d^{'} n \| Z_{p} \|$	$2 d^{'} \| Z_{p} \|$
改进方案	$2 \| G \| + (w + 2) \| Z_{p} \| + 2 d^{″} (d^{″} + 1) + (L + 1) d$	$(w + 1) \| G \| + w \| G_{T} \|$	$2 d^{″} n \| Z_{p} \|$	$2 d^{″} \| Z_{p} \|$
MIPP	$w (d \| Z_{q} \| + \| Z_{p} \|) + \| G_{p} \|$	—	$2 n \| G_{q} \|$	$2 \| G_{q} \|$

基于边缘计算的支持多密钥的加密图像检索

Encrypted image retrieval in multi-key settings based on edge computing

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