An encrypted speech authentication and tampering recovery method based on perceptual hashing

计算机科学 感知 散列函数 计算机安全 认证(法律) 数字水印 语音识别 加密 人工智能 生物 神经科学
作者
Qiu-yu Zhang,Denghai Zhang,Fu-jiu Xu
出处
期刊:Multimedia Tools and Applications [Springer Science+Business Media]
被引量:5
标识
DOI:10.1007/s11042-021-10905-0
摘要

With the progress of speech retrieval technology in the cloud, it brings a lot of conveniences for speech user. Yet, the inquiry encrypted speech results from the speech retrieval system are faced with some secure issues to settle, such as integrity authentication and tampering recovery. In this paper, an encrypted speech authentication and tampering recovery method based on perceptual hashing is proposed. Firstly, the original speech is scrambled by Duffing mapping to construct an encrypted speech library in the cloud, through extracting product of uniform sub-band spectrum variance and spectral entropy of encrypted speech and constructing a perceptual hashing sequence to generate the hashing template of the cloud. From this, a one-to-one correspondence between the encrypted speech and perceptual hashing sequence is established. Secondly, the authentication digest of encrypted speech is extracted according to the inquiry result during the retrieval. Then, the authentication digest and the perceptual hashing sequence of the hashing template in the cloud are matched by the Hamming distance algorithm. Finally, for encrypted speech that fails authentication, tampering detection and location are performed, and the tampered samples are recovered by the least square curve fitting method. The simulation results show that the proposed method can extract the authentication digest directly in the encrypted speech, and the authentication digest not only has good discrimination and robustness, but it accurately locates the tampered area for malicious substitution and mute attacks. In addition, the proposed method can recover tampered speech signals in high quality without any extra information.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
年年岁岁花相似完成签到 ,获得积分10
2秒前
自然的沛山完成签到 ,获得积分10
4秒前
清茶发布了新的文献求助10
4秒前
xixi发布了新的文献求助10
5秒前
zzzkyt发布了新的文献求助10
6秒前
snowwang完成签到,获得积分10
7秒前
星许完成签到 ,获得积分10
7秒前
科目三应助我在青年湖旁采纳,获得10
8秒前
10秒前
10秒前
不安溪灵完成签到,获得积分10
11秒前
情怀应助baijx采纳,获得10
11秒前
11秒前
13秒前
想发JHM完成签到,获得积分10
13秒前
14秒前
Yarrow发布了新的文献求助10
14秒前
董梦薇发布了新的文献求助10
15秒前
慕青应助五十采纳,获得10
15秒前
16秒前
17秒前
无花果应助纳纳椰采纳,获得10
17秒前
Norman发布了新的文献求助10
17秒前
solar完成签到,获得积分10
17秒前
dd完成签到,获得积分20
18秒前
19秒前
19秒前
钱塘郎中完成签到,获得积分0
19秒前
完美世界应助称心的晓霜采纳,获得10
20秒前
zzzkyt发布了新的文献求助10
20秒前
在水一方应助Nini采纳,获得10
20秒前
宋世伟发布了新的文献求助10
20秒前
21秒前
21秒前
cdercder应助你泽采纳,获得10
22秒前
lzy发布了新的文献求助10
23秒前
23秒前
张宇锋发布了新的文献求助10
23秒前
27秒前
高分求助中
Cronologia da história de Macau 5000
Erwählung und Berufung bei Paulus: Bedeutung, Entwicklung und Funktion einer Vorstellung in ihrem frühjüdischen und griechisch-römischen Kontext 850
Matrix Methods in Data Mining and Pattern Recognition 510
Interactions of Vowel Quality and Prosody in East Slavic 500
Vander's Renal Physiology第10版 500
Animalia: Animal and Human Interaction in the Early Medieval English World (Exeter Studies in Medieval Europe) 400
Synfacts Issue 07 · Volume 22 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7131168
求助须知:如何正确求助?哪些是违规求助? 8781271
关于积分的说明 18563542
捐赠科研通 6714155
什么是DOI,文献DOI怎么找? 3152168
关于科研通互助平台的介绍 2276150
邀请新用户注册赠送积分活动 2126559