Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security最新文献_第2页

Simulation of Border Control in an Ongoing Web-based Experiment for Estimating Morphing Detection Performance of Humans 在一个正在进行的基于网络的实验中模拟边界控制以估计人类的变形检测性能

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395073

A. Makrushin, Dennis Siegel, J. Dittmann

引用次数: 8

Steganography by Minimizing Statistical Detectability: The cases of JPEG and Color Images 最小化统计可检测性的隐写术:JPEG和彩色图像的案例

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395075

R. Cogranne, Quentin Giboulot, P. Bas

引用次数: 43

Simulating Suboptimal Steganographic Embedding 模拟次优隐写嵌入

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395071

Christy Kin-Cleaves, Andrew D. Ker

引用次数: 2

Feature Aggregation Networks for Image Steganalysis 用于图像隐写分析的特征聚合网络

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395072

Haneol Jang, Tae-Woo Oh, Kibom Kim

{"title":"Feature Aggregation Networks for Image Steganalysis","authors":"Haneol Jang, Tae-Woo Oh, Kibom Kim","doi":"10.1145/3369412.3395072","DOIUrl":"https://doi.org/10.1145/3369412.3395072","url":null,"abstract":"Since convolutional neural networks have shown remarkable performance on various computer vision tasks, many network architectures for image steganalysis have been introduced. Many of them use fixed preprocessing filters for stable learning, which have a disadvantage of limited use of the information of the input image. The recently introduced end-to-end learning method uses a structure that limits the number of channels of feature maps close to the input and stacks residual blocks. This method has limitations in generating feature maps of various levels and resolutions that can be effective for steganalysis. We therefore propose the feature aggregation-based steganalysis networks: expand the number of channels of convolutional blocks close to the input data, aggregate feature maps of various levels and resolutions, and utilize rich information to improve steganalysis performance. In addition, the capped activation function is applied to obtain better generalization performance. The proposed method outperforms the state-of-the-art steganalysis on detection of the advanced steganography algorithms J-UNIWARD and UED, for JPEG quality factor 75 and 95.","PeriodicalId":298966,"journal":{"name":"Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129211755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Robust Video Steganographic Method against Social Networking Transcoding Based on Steganographic Side Channel 基于隐写侧信道的抗社交网络转码视频隐写鲁棒方法

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395066

Pingan Fan, Hong Zhang, Yifan Cai, Pei Xie, Xianfeng Zhao

{"title":"A Robust Video Steganographic Method against Social Networking Transcoding Based on Steganographic Side Channel","authors":"Pingan Fan, Hong Zhang, Yifan Cai, Pei Xie, Xianfeng Zhao","doi":"10.1145/3369412.3395066","DOIUrl":"https://doi.org/10.1145/3369412.3395066","url":null,"abstract":"The social networks transcode uploaded videos in a lossy way, which makes most video steganographic methods become unusable. In this paper, a robust video steganographic method is proposed to resist video transcoding on social networking sites. The luminance component of the raw video is selected as the cover and Quantization Index Modulation (QIM) algorithm based on block statistical features is applied to embed secret messages. To make a good tradeoff between the robustness and visual quality, an iteration in the local transcoder is designed to determine the minimum quantization step for each video. Then, a strategy of selecting robust video frames is proposed to further improve the robustness and security. To avoid sharing information beforehand between the sender and the receiver, a steganographic side channel is built for correct message extraction. Experimental results have shown that our proposed method can provide strong robustness against social networks transcoding, the average bit error rate is less than 1%. Meanwhile, our proposed method achieves a satisfactory level of security performance. It's a robust and secure method for covert communication on social networking sites such as YouTube and Vimeo.","PeriodicalId":298966,"journal":{"name":"Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security","volume":"39 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120852026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Deep Audio Steganalysis in Time Domain 时域深度音频隐写分析

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395064

Daewon Lee, Tae-Woo Oh, Kibom Kim

引用次数: 4

Exploiting Micro-Signals for Physiological Forensics 利用微信号进行生理取证

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3396882

Min Wu

引用次数: 2

Protecting Smartphone Screen Notification Privacy by Verifying the Gripping Hand 通过验证握持手保护智能手机屏幕通知隐私

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395077

Chen Wang, Jingjing Mu, Long Huang

{"title":"Protecting Smartphone Screen Notification Privacy by Verifying the Gripping Hand","authors":"Chen Wang, Jingjing Mu, Long Huang","doi":"10.1145/3369412.3395077","DOIUrl":"https://doi.org/10.1145/3369412.3395077","url":null,"abstract":"As the most common personal devices, smartphones contain the user's private information. While people use mobile devices anytime and anywhere, the sensitive contents might be leaked from the screens. The smartphone notifications cause such privacy leakages even on a lock screen. With the aim to alert the user of an event (e.g., text messages, phone calls and calendar reminders), these onscreen notifications usually contain the sender's name and even a clip of the contents for preview. Such information, if not displayed appropriately, may cause the leakages of the user's social relations, personal hobbies and private message contents. This work focuses on wisely displaying the notifications to avoid leaking the user's privacy. We develop an unobtrusive user authentication system to confirm the user identity via their gripping-hands before displaying notifications. In particular, we carefully design an inaudible acoustic signal and emit it from the smartphone speaker to sense the gripping hand, when there is a need to push notifications. The signal propagating to the smartphone's microphones carries the user's biometric information related to the gripping hand (e.g., palm size and gripping strength). We further derive the Mel Frequency Cepstral Coefficient time series and develop a machine learning-based algorithm to identify the user. The experimental results show that our system can identify 8 users with 92% accuracy.","PeriodicalId":298966,"journal":{"name":"Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131311016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

LiveDI: An Anti-theft Model Based on Driving Behavior LiveDI:基于驾驶行为的防盗模型

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-06-22 DOI: 10.1145/3369412.3395069

Hashim Abu-gellban, L. Nguyen, M. Moghadasi, Zhenhe Pan, Fang Jin

引用次数: 12

Nested Tailbiting Convolutional Codes for Secrecy, Privacy, and Storage 用于保密、隐私和存储的嵌套尾部卷积码

Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security Pub Date : 2020-04-27 DOI: 10.1145/3369412.3395063

Thomas Jerkovits, O. Günlü, V. Sidorenko, G. Kramer

{"title":"Nested Tailbiting Convolutional Codes for Secrecy, Privacy, and Storage","authors":"Thomas Jerkovits, O. Günlü, V. Sidorenko, G. Kramer","doi":"10.1145/3369412.3395063","DOIUrl":"https://doi.org/10.1145/3369412.3395063","url":null,"abstract":"The key agreement problem with biometric or physical identifiers and two terminals for key enrollment and reconstruction is considered. A nested convolutional code construction that performs lossy compression with side information is proposed. Nested convolutional codes are an alternative to nested polar codes and nested random linear codes that achieve all points of the key-leakage-storage regions of the generated-secret and chosen-secret models for long block lengths. Our design uses a convolutional code for vector quantization during enrollment and a subcode of it for error correction during reconstruction. Physical identifiers with small bit error probability are considered to illustrate the gains of the proposed construction. One variant of nested convolutional codes improves on all previous constructions in terms of the key vs. storage rate ratio but it has high complexity. Another variant of nested convolutional codes with lower complexity performs similarly to previously designed nested polar codes. The results suggest that the choice of convolutional or polar codes for key agreement with identifiers depends on the complexity constraints.","PeriodicalId":298966,"journal":{"name":"Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122520478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3