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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology Engineering Research Center of Digital forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical Engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image forensics.Despite the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression standards.In particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing methods.To tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is proposed.The QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion representation.The relationships between the color channels of the image are preserved,and the utilization of color information is optimized.Additionally,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double compression.Experimental results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Image coding Image color analysis Quaternions forensics Transform coding Color Feature extraction

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Application of Microbiome in forensics

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Genomics, Proteomics & Bioinformatics 2023年第1期21卷 97-107页

作者： Jun Zhang Wenli Liu Halimureti Simayijiang Ping Hu Jiangwei Yan School of Forensic Medicine Shanxi Medical UniversityTaiyuan 030001China Beijing Center for Physical and Chemical Analysis Beijing 100089China Key Laboratory of Environment and Health(HUST) Ministry of Education&Ministry of Environmental Protectionand State Key Laboratory of Environmental Health(Incubation)School of Public HealthTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430074China

Recent advances in next-generation sequencing technologies and improvements in bioinformatics have expanded the scope of microbiome analysis as a forensic tool.Microbiome research is concerned with the study of the compositional profile and diversity of microbial flora as well as the interactions between microbes,hosts,and the environment.It has opened up many new possibilities for forensic analysis.In this review,we discuss various applications of microbiome in forensics,including identification of individuals,geolocation inference,and post-mortem interval(PMI)estimation.

关键词： Microbiome forensics Next-generation sequencing Bioinformatics Application

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Research on Metaverse Security and forensics

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Computers, Materials & Continua 2023年第10期77卷 799-825页

作者： Guangjun Liang Jianfang Xin Qun Wang Xueli Ni Xiangmin Guo Pu Chen Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjingChina Engineering Research Center of Electronic Data forensics Analysis NanjingChina Key Laboratory of Digital forensics Department of Public Security of Jiangsu ProvinceNanjingChina School of Intelligent Engineering Nanjing Institute of Railway TechnologyNanjingChina

As a subversive concept,the metaverse has recently attracted widespread attention around the world and has set off a wave of enthusiasm in academic,industrial,and investment circles.However,while the metaverse brings unprecedented opportunities for transformation to human society,it also contains related risks.Metaverse is a digital living space with information infrastructure,interoperability system,content production system,and value settlement system as the underlying structure in which the inner core is to connect real residents through applications and identities.Through social incentives and governance rules,the metaverse reflects the digital migration of human society.This article will conduct an in-depth analysis of the metaverse from the perspective of electronic data forensics.First,from the perspective of Internet development,the background and development process of the metaverse is discussed.By systematically elaborating on the concept and connotation of the metaverse,this paper summarizes the different views of current practitioners,experts,and scholars on the metaverse.Secondly,from the perspective of metaverse security,the social risk and crime risks of the metaverse are discussed.Then the importance of metaverse forensics is raised.Third,from the perspective of blockchain,smart wearable devices,and virtual reality devices,the objects and characteristics of metaverse forensics have been studied in depth.Taking smart wearable devices as an example,this paper gives the relevant experimental process of smart bracelet forensics.Finally,many challenges faced by metaverse forensics are summarized by us which provide readers with some exploratory guidance.

关键词： Metaverse forensics blockchain smart wear virtual reality

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WIDE:A witness-based data priority mechanism for vehicular forensics

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Blockchain(Research and Applications) 2022年第2期3卷 15-24页

作者： Chuka Ohama Regio A.Michelin Raja Jurdak Salil S.Kanhere Sanjay Jha University of New South Wales(UNSW) SydneyNSW 2052Australia Queensland University of Technology(QUT) BrisbaneQLD 4000Australia

In this paper,we present a WItness based Data priority mEchanism(WIDE)for vehicles in the vicinity of an accident to facilitate liability decisions.WIDE evaluates the integrity of data generated by these vehicles,called witnesses,in the event of an accident to assure the reliability of data to be used for making liability decisions and ensure that such data are received from credible witnesses.To achieve this,WIDE introduces a two-level integrity assessment to achieve end-to-end integrity by initially ascertaining the integrity of data-producing sensors,and validating that data generated have not been altered on transit by compromised road-side units(RSUs)by executing a practical byzantine fault tolerance(pBFT)protocol to reach consensus on data reliability.Furthermore,WIDE utilises a blockchain based reputation management system(BRMS)to ensure that only data from highly reputable witnesses are utilised as contributing evidence for facilitating liability decisions.Finally,we formally verify the proposed framework against data integrity requirements using the Automated Verification of Internet Security Protocols and Applications(AVISPA)with High-Level Protocol Specification Language(HLPSL).Qualitative arguments show that our proposed framework is secured against identified security attacks and assures the reliability of data utilised for making liability decisions,while quantitative evaluations demonstrate that our proposal is practical for fully autonomous vehicle forensics.

关键词： Fully autonomous vehicles Electronic control units Blockchain Witness forensics Security Consensus Fairness Automated verification of internet security protocols and applications(AVISPA)

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Ensuring the Authenticity and Non-Misuse of Data Evidence in Digital forensics

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Journal of Harbin Institute of Technology(New Series) 2015年第1期22卷 85-90页

作者： Jingsha He Gongzheng Liu Bin Zhao Xuejiao Wan Na Huang School of Software Engineering Beijing University of Technology Dept. of Computer Science Jining University State Key Laboratory of Digital Publishing Technology Peking University Founder Group Co.Ltd

In forensic investigations,it is vital that the authenticity of digital evidence should be ensured. In addition,technical means should be provided to ensure that digital evidence collected cannot be misused for the purpose of perjury. In this paper,we present a method to ensure both authenticity and non-misuse of data extracted from wireless mobile devices. In the method,the device ID and a timestamp become a part of the original data and the Hash function is used to bind the data together. Encryption is applied to the data,which includes the digital evidence,the device ID and the timestamp. Both symmetric and asymmetric encryption systems are employed in the proposed method where a random session key is used to encrypt the data while the public key of the forensic server is used to encrypt the session key to ensure security and efficiency. With the several security mechanisms that we show are supported or can be implemented in wireless mobile devices such as the Android,we can ensure the authenticity and non-misuse of data evidence in digital forensics.

关键词： digital forensics authenticity non-misuse digital

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Security and Privacy in the Computer forensics Context

Security and Privacy in the Computer Forensics Context

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2006 10th International Conference on Communication Technology（ICCT 2006）

作者： S.Srinivasan Professor of Computer Information Systems Director Center for Information Assurance University of Louisville Louisville Kentucky 40292 USA

ISBN: (纸本)1424408016;9781424408016

Today computers are used in numerous day-to-day activities as a communications tool. In this regard several different applications are used to generate and store important documents. These documents contain vital data to the user and at times to an investigator in the event a crime is committed using that computer. The user would expect reasonable security precautions to be in place to protect the data on the computer, especially when the computer is connected to the Internet. The user with deceptive goals in mind would want to hide information where as a Computer forensics investigator would want to find out the hidden information for evidence. In this paper we examine several security features that are commonly used and how such precautions are thwarted by Computer forensics tools and their impact on privacy.

关键词： Computer security Privacy forensics Data security Information security Context Application software Computer crime Protection Internet

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Blockchain⁃Based Log Verification System for Cloud forensics

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Journal of Donghua University(English Edition) 2021年第5期38卷 449-458页

作者： AGBEDANU Promise Ricardo 王鹏伟雷颖慧 NORTEY Richard N RASOOL Abdul ODARTEY Lamptey K School of Computer Science and Technology Donghua UniversityShanghai 201620China

In this age when most organizations make use of cloud computing,it is important to not only protect cloud computing resources from cyber⁃attacks but also investigate these attacks.During forensic investigations in a cloud environment,the investigators fall on service providers for pieces of evidence like log files.The challenge,however,is the integrity of these logs provided by the service providers.To this end,we propose a blockchain⁃based log verification system called BlogVerifier that uses a decentralized approach to solve forensics issues in the cloud.BlogVerifier extracts logs produced in cloud environments,hashes these logs and stores the hashed values as transactional values on the blockchain.The transactions are then merged into blocks and shared on the blockchain.The proposed system also ensures the continuation of an investigation even when the primary source of a log is compromised by using encryption and smart contracts.The proposed system also makes it possible for any stakeholder involved in the forensic process to verify the authenticity of log files.The performance results show that BlogVerifier can be integrated into the cloud environment without any significant impact on system resources and increase in computational cost.

关键词： cloud computing forensics blockchain cryptography security

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Vulnerability Analysis of MEGA Encryption Mechanism

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Computers, Materials & Continua 2022年第10期73卷 817-829页

作者： Qingbing Ji Zhihong Rao Lvlin Ni Wei Zhao Jing Fu School of Cybersecurity Northwestern Polytechnical UniversityXi’an710072China No.30 Institute of CETC Chengdu610041China Eberly College of Science Pennsylvania State University-University ParkPA16802USA

MEGA is an end-to-end encrypted cloud storage platform controlled by users.Moreover,the communication between MEGA client and server is carried out under the protection of Transport Layer Security(TLS)encryption,it is difficult to intercept the key data packets in the process of MEGA registration,login,file data upload,and download.These characteristics of MEGA have brought great difficulties to its forensics.This paper presents a method to attack MEGA to provide an effective method for MEGA’s forensics.By debugging the open-source code of MEGA and analyzing the security white paper published,this paper first clarifies the encryption mechanism of MEGA,including the detailed process of registration,login,and file encryption,studies the encryption mechanism of MEGA from the perspective of protocol analysis,and finds out the vulnerability of MEGA encryption mechanism.On this basis,a method to attack MEGA is proposed,and the secret data stored in the MEGA server can be accessed or downloaded;Finally,the efficiency of the attack method is analyzed,and some suggestions to resist this attack method are put forward.

关键词： TLS advanced encryption standard forensics protocol analysis vulnerability

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Metaheuristics with Optimal Deep Transfer Learning Based Copy-Move Forgery Detection Technique

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Intelligent Automation & Soft Computing 2023年第1期35卷 881-899页

作者： C.D.Prem Kumar S.Saravana Sundaram Department of Information Technology Hindusthan College of Engineering and TechnologyCoimbatore641032TamilnaduIndia Department of Electrical and Electronics Engineering Hindusthan College of Engineering and TechnologyCoimbatore641032TamilnaduIndia

The extensive availability of advanced digital image technologies and image editing tools has simplified the way of manipulating the image content.An effective technique for tampering the identification is the copy-move forgery.Conventional image processing techniques generally search for the patterns linked to the fake content and restrict the usage in massive data classification.Contrast-ingly,deep learning(DL)models have demonstrated significant performance over the other statistical techniques.With this motivation,this paper presents an Optimal Deep Transfer Learning based Copy Move Forgery Detection(ODTL-CMFD)technique.The presented ODTL-CMFD technique aims to derive a DL model for the classification of target images into the original and the forged/tampered,and then localize the copy moved regions.To perform the feature extraction process,the political optimizer(PO)with Mobile Networks(MobileNet)model has been derived for generating a set of useful vectors.Finally,an enhanced bird swarm algorithm(EBSA)with least square support vector machine(LS-SVM)model has been employed for classifying the digital images into the original or the forged ones.The utilization of the EBSA algorithm helps to properly modify the parameters contained in the Multiclass Support Vector Machine(MSVM)technique and thereby enhance the classification performance.For ensuring the enhanced performance of the ODTL-CMFD technique,a series of simulations have been performed against the benchmark MICC-F220,MICC-F2000,and MICC-F600 datasets.The experimental results have demonstrated the improvised performance of the ODTL-CMFD approach over the other techniques in terms of several evaluation measures.

关键词： Copy move detection image forgery deep learning machine learning parameter tuning forensics

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A Survey of Blind forensics Techniques for JPEG Image Tampering

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Journal of Computer and Communications 2019年第10期7卷 1-13页

作者： Xueling Chu Haiming Li College of Computer Science and Technology Shanghai University of Electric Power Shanghai China

Blind forensics of JPEG image tampering as a kind of digital image blind forensics technology is gradually becoming a new research hotspot in the field of image security. Firstly, the main achievements of domestic and foreign scholars in the blind forensic technology of JPEG image tampering were briefly described. Then, according to the different methods of tampering and detection, the current detection was divided into two types: double JPEG compression detection and block effect inconsistency detection. This paper summarized the existing methods of JPEG image blind forensics detection, and analyzed the two methods. Finally, the existing problems and future research trends were analyzed and prospected to provide further theoretical support for the research of JPEG image blind forensics technology.

关键词： Image forensics Tamper Detection JPEG Image forensics JPEG Block Effect

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