社交媒体平台的媒体取证:一项调查

IF 2.5 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS EURASIP Journal on Information Security Pub Date : 2021-05-01 DOI:10.1186/s13635-021-00117-2
Cecilia Pasquini, Irene Amerini, Giulia Boato
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引用次数: 31

摘要

网络上视觉信息的可靠性和社交媒体平台上病毒式传播的数字媒体的真实性引发了前所未有的关注。因此,在过去的几年中,多媒体取证研究社区追求将取证分析扩展到现实世界中基于web的开放系统的目标。本调查旨在描述迄今为止在共享数据分析方面所做的工作,涵盖三个主要方面:对社交网络上上传的媒体进行来源识别和完整性验证的取证技术,允许识别共享平台的平台来源分析,以及评估与其相关文本信息相关的媒体对象可信度的多媒体验证算法。已取得的成果与当前开放的问题和需要解决的研究挑战一起突出显示,以便在未来推进该领域。
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Media forensics on social media platforms: a survey
The dependability of visual information on the web and the authenticity of digital media appearing virally in social media platforms has been raising unprecedented concerns. As a result, in the last years the multimedia forensics research community pursued the ambition to scale the forensic analysis to real-world web-based open systems. This survey aims at describing the work done so far on the analysis of shared data, covering three main aspects: forensics techniques performing source identification and integrity verification on media uploaded on social networks, platform provenance analysis allowing to identify sharing platforms, and multimedia verification algorithms assessing the credibility of media objects in relation to its associated textual information. The achieved results are highlighted together with current open issues and research challenges to be addressed in order to advance the field in the next future.
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来源期刊
EURASIP Journal on Information Security
EURASIP Journal on Information Security COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
8.80
自引率
0.00%
发文量
6
审稿时长
13 weeks
期刊介绍: The overall goal of the EURASIP Journal on Information Security, sponsored by the European Association for Signal Processing (EURASIP), is to bring together researchers and practitioners dealing with the general field of information security, with a particular emphasis on the use of signal processing tools in adversarial environments. As such, it addresses all works whereby security is achieved through a combination of techniques from cryptography, computer security, machine learning and multimedia signal processing. Application domains lie, for example, in secure storage, retrieval and tracking of multimedia data, secure outsourcing of computations, forgery detection of multimedia data, or secure use of biometrics. The journal also welcomes survey papers that give the reader a gentle introduction to one of the topics covered as well as papers that report large-scale experimental evaluations of existing techniques. Pure cryptographic papers are outside the scope of the journal. Topics relevant to the journal include, but are not limited to: • Multimedia security primitives (such digital watermarking, perceptual hashing, multimedia authentictaion) • Steganography and Steganalysis • Fingerprinting and traitor tracing • Joint signal processing and encryption, signal processing in the encrypted domain, applied cryptography • Biometrics (fusion, multimodal biometrics, protocols, security issues) • Digital forensics • Multimedia signal processing approaches tailored towards adversarial environments • Machine learning in adversarial environments • Digital Rights Management • Network security (such as physical layer security, intrusion detection) • Hardware security, Physical Unclonable Functions • Privacy-Enhancing Technologies for multimedia data • Private data analysis, security in outsourced computations, cloud privacy
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