The smart home platform integrates with Internet of Things(IoT)devices,smartphones,and cloud servers,enabling seamless and convenient services.It gathers and manages extensive user data,including personal information,...The smart home platform integrates with Internet of Things(IoT)devices,smartphones,and cloud servers,enabling seamless and convenient services.It gathers and manages extensive user data,including personal information,device operations,and patterns of user behavior.Such data plays an essential role in criminal inves-tigations,highlighting the growing importance of specialized smart home forensics.Given the rapid advancement in smart home software and hardware technologies,many companies are introducing new devices and services that expand the market.Consequently,scalable and platform-specific forensic research is necessary to support efficient digital investigations across diverse smart home ecosystems.This study thoroughly examines the core components and structures of smart homes,proposing a generalized architecture that represents various operational environments.A three-stage smart home forensics framework is introduced:(1)analyzing application functions to infer relevant data,(2)extracting and processing data from interconnected devices,and(3)identifying data valuable for investigative purposes.The framework’s applicability is validated using testbeds from Samsung SmartThings and Xiaomi Mi Home platforms,offering practical insights for real-world forensic applications.The results demonstrate that the proposed forensic framework effectively acquires and classifies relevant digital evidence in smart home platforms,confirming its practical applicability in smart home forensic investigations.展开更多
This themed issue of‘Episodes’is dedicated entirely to forensic geology.This provides an overview of how geologists assist the police and law enforcement to help investigate crimes.The documented application of geol...This themed issue of‘Episodes’is dedicated entirely to forensic geology.This provides an overview of how geologists assist the police and law enforcement to help investigate crimes.The documented application of geology to police and law enforcement dates back to the middle part of the 19th Century,and possibly to Roman times.Until the establishment of the International Union of Geological Sciences(IUGS),Initiative on Forensic Geology(IFG),in 2011,there was no international organization aimed at developing forensic geology on a global scale.Previously,forensic geologists worked in relative isolation from other fellow geologists.There were few incentives or opportunities for the advancement of forensic geology.IUGS-IFG has provided opportunities,incentives and the drive for the global development of forensic geology,as exemplified in this issue of Episodes.展开更多
With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed...With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.展开更多
An Ad Hoc Review Committee(ARC)was convened to consider the IUGS Initiative on Forensic Geology(FG).The meeting held on 4^(th) April 2016 at Piccadilly Place,Manchester,UK under the Chairmanship of Prof.Jose P.Calvo(J...An Ad Hoc Review Committee(ARC)was convened to consider the IUGS Initiative on Forensic Geology(FG).The meeting held on 4^(th) April 2016 at Piccadilly Place,Manchester,UK under the Chairmanship of Prof.Jose P.Calvo(JC),Secretary General,IUGS.The other attendees of the meeting were Prof.Marko Komac(MK),Vice-President of the IUGS,Dr.Laurence Donnelly(LD),Chair of the IUGS Initiative on Forensic Geology(IFG)and a Forensic Geologist and Police Search Adviser,Dr.Alastair Ruffel(AL),Forensic Geologist at Queens University,Belfast,who has significant experience in forensic geology and in working with law enforcement agencies,and Inspector Colin Hope(CH),National Search Advisor at the UK National Crime Agency.展开更多
In this research,we developed a plugin for our automated digital forensics framework to extract and preserve the evidence from the Android and the IOS-based mobile phone application,Instagram.This plugin extracts pers...In this research,we developed a plugin for our automated digital forensics framework to extract and preserve the evidence from the Android and the IOS-based mobile phone application,Instagram.This plugin extracts personal details from Instagram users,e.g.,name,user name,mobile number,ID,direct text or audio,video,and picture messages exchanged between different Instagram users.While developing the plugin,we identified resources available in both Android and IOS-based devices holding key forensics artifacts.We highlighted the poor privacy scheme employed by Instagram.This work,has shown how the sensitive data posted in the Instagram mobile application can easily be reconstructed,and how the traces,as well as the URL links of visual messages,can be used to access the privacy of any Instagram user without any critical credential verification.We also employed the anti-forensics method on the Instagram Android’s application and were able to restore the application from the altered or corrupted database file,which any criminal mind can use to set up or trap someone else.The outcome of this research is a plugin for our digital forensics ready framework software which could be used by law enforcement and regulatory agencies to reconstruct the digital evidence available in the Instagram mobile application directories on both Android and IOS-based mobile phones.展开更多
Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descen...Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descent to understand kinship,migration patterns,and population dynamics.Within forensic science,forensic investigative genetic genealogy(FIGG)has gained prominence by leveraging next-generation sequencing technologies and population-specific genomic resources,opening useful investigative avenues.In this review,we synthesize current knowledge,underscore recent advancements,and discuss the growing role of FIGG in forensic genomics.FIGG has been pivotal in revitalizing dormant inquiries and offering genetic leads in numerous cold cases.Its effectiveness relies on the extensive single-nucleotide polymorphism profiles contributed by individuals from diverse populations to specialized genomic databases.Advances in computational genomics and the growth of human genomic databases have spurred a profound shift in the application of genetic genealogy across forensics,anthropology,and ancient DNA studies.As the field progresses,FIGG is evolving from a nascent practice into a more sophisticated and specialized discipline,shaping the future of forensic investigations.展开更多
Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most...Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.展开更多
In today’s digital era,the rapid evolution of image editing technologies has brought about a significant simplification of image manipulation.Unfortunately,this progress has also given rise to the misuse of manipulat...In today’s digital era,the rapid evolution of image editing technologies has brought about a significant simplification of image manipulation.Unfortunately,this progress has also given rise to the misuse of manipulated images across various domains.One of the pressing challenges stemming from this advancement is the increasing difficulty in discerning between unaltered and manipulated images.This paper offers a comprehensive survey of existing methodologies for detecting image tampering,shedding light on the diverse approaches employed in the field of contemporary image forensics.The methods used to identify image forgery can be broadly classified into two primary categories:classical machine learning techniques,heavily reliant on manually crafted features,and deep learning methods.Additionally,this paper explores recent developments in image forensics,placing particular emphasis on the detection of counterfeit colorization.Image colorization involves predicting colors for grayscale images,thereby enhancing their visual appeal.The advancements in colorization techniques have reached a level where distinguishing between authentic and forged images with the naked eye has become an exceptionally challenging task.This paper serves as an in-depth exploration of the intricacies of image forensics in the modern age,with a specific focus on the detection of colorization forgery,presenting a comprehensive overview of methodologies in this critical field.展开更多
The integration of phytochemistry into forensic science has emerged as a groundbreaking frontier,providing unprecedented insights into nature's secrets through the precise application of phytochemical fingerprinti...The integration of phytochemistry into forensic science has emerged as a groundbreaking frontier,providing unprecedented insights into nature's secrets through the precise application of phytochemical fingerprinting of phytotoxins as a cutting-edge approach.This study explores the dynamic intersection of phytochemistry and forensic science,highlighting how the unique phytochemical profiles of toxic plants and their secondary metabolites,serve as distinctive markers for forensic investigations.By utilizing advanced techniques such as Ultra-High-Performance Liquid Chromatography(UHPLC)and High-Resolution Mass Spectrometry(HRMS),the detection and quantification of plant-derived are made more accurate in forensic contexts.Real-world case studies are presented to demonstrate the critical role of plant toxins in forensic outcomes and legal proceedings.The challenges,potential,and future prospects of integrating phytochemical fingerprinting of plant toxins into forensic science were discussed.This review aims to illuminate phytochemical fingerprinting of plant toxins as a promising tool to enhance the precision and depth of forensic analyses,offering new insights into the complex stories embedded in plant toxins.展开更多
Objective:With the continuous changes in social production,the consumption th inking of the masses obviously cannot keep up with the speed of social developmen t,and insurance disputes are increasingly emerging.Among ...Objective:With the continuous changes in social production,the consumption th inking of the masses obviously cannot keep up with the speed of social developmen t,and insurance disputes are increasingly emerging.Among them,the shortcomings of personal injury claims are not prominent,and the theoretical knowledge is not co mplete.In order to improve the quality of professional talents and reduce claims dis putes,the feasibility of integrating forensic medicine into personal injury claims is ex plored.Methods:The professional attributes,subject attributes,knowledge system an d employment data of forensic medicine are analyzed and compared with the actual work of personal injury claims.Main results:Forensic medicine has its uniqueness i n on-site investigation,injury-disease relationship analysis,and resolution of doubts.I t is irreplaceable by other subjects.The subject attributes are consistent with the pe rsonal injury claims major,and personal injury claims itself has basic medical courses,so it is easier to accept forensic medicine.Conclusion:Under the current social bac kground,through the study of the forensic medicine system in the personal injury cl aims major,it has positive practical significance for its professional construction and talent training.展开更多
Images and videos play an increasingly vital role in daily life and are widely utilized as key evidentiary sources in judicial investigations and forensic analysis.Simultaneously,advancements in image and video proces...Images and videos play an increasingly vital role in daily life and are widely utilized as key evidentiary sources in judicial investigations and forensic analysis.Simultaneously,advancements in image and video processing technologies have facilitated the widespread availability of powerful editing tools,such as Deepfakes,enabling anyone to easily create manipulated or fake visual content,which poses an enormous threat to social security and public trust.To verify the authenticity and integrity of images and videos,numerous approaches have been proposed,which are primarily based on content analysis and their effectiveness is susceptible to interference from various image or video post-processing operations.Recent research has highlighted the potential of file containers analysis as a promising forensic approach that offers efficient and interpretable results.However,there is still a lack of review articles on this kind of approach.In order to fill this gap,we present a comprehensive review of file containers-based image and video forensics in this paper.Specifically,we categorize the existing methods into two distinct stages,qualitative analysis and quantitative analysis.In addition,an overall framework is proposed to organize the exiting approaches.Then,the advantages and disadvantages of the schemes used across different forensic tasks are provided.Finally,we outline the trends in this research area,aiming to provide valuable insights and technical guidance for future research.展开更多
The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challe...The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.展开更多
The large scale and distribution of cloud computing storage have become the major challenges in cloud forensics for file extraction. Current disk forensic methods do not adapt to cloud computing well and the forensic ...The large scale and distribution of cloud computing storage have become the major challenges in cloud forensics for file extraction. Current disk forensic methods do not adapt to cloud computing well and the forensic research on distributed file system is inadequate. To address the forensic problems, this paper uses the Hadoop distributed file system （HDFS） as a case study and proposes a forensic method for efficient file extraction based on three-level （3L） mapping. First, HDFS is analyzed from overall architecture to local file system. Second, the 3L mapping of an HDFS file from HDFS namespace to data blocks on local file system is established and a recovery method for deleted files based on 3L mapping is presented. Third, a multi-node Hadoop framework via Xen virtualization platform is set up to test the performance of the method. The results indicate that the proposed method could succeed in efficient location of large files stored across data nodes, make selective image of disk data and get high recovery rate of deleted files.展开更多
Advances in technological developments in Geographic Information Systems(GIS)has enabled the application of GIS in landscape mapping,environmental management,natural hazard risk and disaster management.As geographical...Advances in technological developments in Geographic Information Systems(GIS)has enabled the application of GIS in landscape mapping,environmental management,natural hazard risk and disaster management.As geographical information becomes more widely available through satellite and aerial imagery,the cost of software decreases and GIS expertise expands,it is most likely that the use of GIS will increase.The methodology has practical applications for police,crime scene investigators and forensic geoscientists.The aim is to develop GIS use in forensic search beyond mapping to offer a set of decision support tools that utilise the spatial analytical capabilities of GIS.This enables better management and understanding of the complicated and interrelated nature of a ground search.展开更多
The aim of the present study was to evaluate the psychometric properties and dimensionality of the instrument Quality in Psychiatric Care-Forensic In-Patient Staff (QPC-FIPS) and to describe the perceived quality of p...The aim of the present study was to evaluate the psychometric properties and dimensionality of the instrument Quality in Psychiatric Care-Forensic In-Patient Staff (QPC-FIPS) and to describe the perceived quality of psychiatric care among forensic inpatient service staff. A sample of 348 forensic inpatient staff from 18 forensic wards in Sweden participated in the study. A confirmatory factor analysis revealed a seven-factor structure with item loadings > 0.50 on expected factors, indicating adequate psychometric properties. The staff’s ratings of quality of care were high, 94% being positive. The highest ratings were found for the secluded-environment dimension and the lowest for the secure-environment dimension. Several factors influenced the ratings of quality of care, for instance, staff’s time to perform their duties and staff’s age. It is concluded that the QPC-FIPS can give valuable information about staff’s perceptions of the quality of care provided at inpatient forensic psychiatric care services, which can be used to identify areas for quality improvement. Use of the QPC-FIPS is an easy and inexpensive way to evaluate quality in forensic inpatient care, preferably in conjunction with the QPC-FIP instrument developed for forensic inpatients and covering the same items and dimensions.展开更多
Traditional approaches to digital forensics reconstruct events within digital systems that often are not built for the creation of evidence; however,there is an emerging discipline of forensic readiness that examines ...Traditional approaches to digital forensics reconstruct events within digital systems that often are not built for the creation of evidence; however,there is an emerging discipline of forensic readiness that examines what it takes to build systems and devices that produce digital data records for which admissibility is a requirement. This paper reviews the motivation behind research in this area,a generic technical solution that uses hardware-based security to bind digital records to a particular state of a device and proposed applications of this solution in concrete,practical scenarios. Research history in this area,the notion of secure digital evidence and a technical solution are discussed. A solution to creating hardware-based security in devices producing digital evidence was proposed in 2012. Additionally,this paper revises the proposal and discusses three distinct scenarios where forensic readiness of devices and secure digital evidence are relevant. It shows,how the different requirements of the three scenarios can be realized using a hardware-based solution. The scenarios are:lawful interception of voice communication,automotive black box,precise farming. These three scenarios come from very distinctive application domains. Nevertheless,they share a common set of security requirements for processes to be documented and data records to be stored.展开更多
Research in virtualization technology has gained significant developments in recent years, which brings not only opportunities to the forensic community, but challenges as well. This paper discusses the potential role...Research in virtualization technology has gained significant developments in recent years, which brings not only opportunities to the forensic community, but challenges as well. This paper discusses the potential roles of virtualization in digital forensics, examines the recent progresses which use the virtualization techniques to support modem computer forensics. The influences on digital forensics caused by virtualization technology are identified. Tools and methods in common digital forensic practices are analyzed, and experiences of our practice and reflections in this field are shared.展开更多
The power system frequency fluctuations could be captured by digital recordings and extracted to compare with a reference database for forensic timestamp verification.It is known as the Electric Network Frequency(ENF)...The power system frequency fluctuations could be captured by digital recordings and extracted to compare with a reference database for forensic timestamp verification.It is known as the Electric Network Frequency(ENF)criterion,enabled by the properties of random fluctuations and intra-grid consistency.In essence,this is a task of matching a short random sequence within a long reference,whose accuracy is mainly concerned with whether this match could be uniquely correct.In this paper,we comprehensively analyze the factors affecting the reliability of ENF matching,including the length of test recording,length of reference,temporal resolution,and Signal-to-Noise Ratio(SNR).For synthetic analysis,we incorporate the first-order AutoRegressive(AR)ENF model and propose an efficient Time-Frequency Domain noisy ENF synthesis method.Then,the reliability analysis schemes for both synthetic and real-world data are respectively proposed.Through a comprehensive study,we quantitatively reveal that while the SNR is an important external factor to determine whether timestamp verification is viable,the length of test recording is the most important inherent factor,followed by the length of reference.However,the temporal resolution has little impact on performance.Finally,a practical workflow of the ENF-based audio timestamp verification system is proposed,incorporating the discovered results.展开更多
We are living in a society constructed by many aspects as well as languages.There are many ways to deal with legal cases,language is also an active one among them.As it is proved that resultant of forensic linguistic ...We are living in a society constructed by many aspects as well as languages.There are many ways to deal with legal cases,language is also an active one among them.As it is proved that resultant of forensic linguistic researches do help around.展开更多
Automated and autonomous decisions of image classification systems have essential applicability in this modern age even.Image-based decisions are commonly taken through explicit or auto-feature engineering of images.I...Automated and autonomous decisions of image classification systems have essential applicability in this modern age even.Image-based decisions are commonly taken through explicit or auto-feature engineering of images.In forensic radiology,auto decisions based on images significantly affect the automation of various tasks.This study aims to assist forensic radiology in its biological profile estimation when only bones are left.A benchmarked dataset Radiology Society of North America(RSNA)has been used for research and experiments.Additionally,a locally developed dataset has also been used for research and experiments to cross-validate the results.A Convolutional Neural Network(CNN)-based model named computer vision and image processing-net(CVIP-Net)has been proposed to learn and classify image features.Experiments have also been performed on state-of-the-art pertained models,which are alex_net,inceptionv_3,google_net,Residual Network(resnet)_50,and Visual Geometry Group(VGG)-19.Experiments proved that the proposed CNN model is more accurate than other models when panoramic dental x-ray images are used to identify age and gender.The specially designed CNN-based achieved results in terms of standard evaluation measures including accuracy(98.90%),specificity(97.99%),sensitivity(99.34%),and Area under the Curve(AUC)-value(0.99)on the locally developed dataset to detect age.The classification rates of the proposed model for gender estimation were 99.57%,97.67%,98.99%,and 0.98,achieved in terms of accuracy,specificity,sensitivity,and AUC-value,respectively,on the local dataset.The classification rates of the proposed model for age estimation were 96.80%,96.80%,97.03%,and 0.99 achieved in terms of accuracy,specificity,sensitivity,and AUC-value,respectively,on the RSNA dataset.展开更多
文摘The smart home platform integrates with Internet of Things(IoT)devices,smartphones,and cloud servers,enabling seamless and convenient services.It gathers and manages extensive user data,including personal information,device operations,and patterns of user behavior.Such data plays an essential role in criminal inves-tigations,highlighting the growing importance of specialized smart home forensics.Given the rapid advancement in smart home software and hardware technologies,many companies are introducing new devices and services that expand the market.Consequently,scalable and platform-specific forensic research is necessary to support efficient digital investigations across diverse smart home ecosystems.This study thoroughly examines the core components and structures of smart homes,proposing a generalized architecture that represents various operational environments.A three-stage smart home forensics framework is introduced:(1)analyzing application functions to infer relevant data,(2)extracting and processing data from interconnected devices,and(3)identifying data valuable for investigative purposes.The framework’s applicability is validated using testbeds from Samsung SmartThings and Xiaomi Mi Home platforms,offering practical insights for real-world forensic applications.The results demonstrate that the proposed forensic framework effectively acquires and classifies relevant digital evidence in smart home platforms,confirming its practical applicability in smart home forensic investigations.
文摘This themed issue of‘Episodes’is dedicated entirely to forensic geology.This provides an overview of how geologists assist the police and law enforcement to help investigate crimes.The documented application of geology to police and law enforcement dates back to the middle part of the 19th Century,and possibly to Roman times.Until the establishment of the International Union of Geological Sciences(IUGS),Initiative on Forensic Geology(IFG),in 2011,there was no international organization aimed at developing forensic geology on a global scale.Previously,forensic geologists worked in relative isolation from other fellow geologists.There were few incentives or opportunities for the advancement of forensic geology.IUGS-IFG has provided opportunities,incentives and the drive for the global development of forensic geology,as exemplified in this issue of Episodes.
基金supported by the National Fund Cultivation Project from China People’s Police University(Grant Number:JJPY202402)National Natural Science Foundation of China(Grant Number:62172165).
文摘With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.
文摘An Ad Hoc Review Committee(ARC)was convened to consider the IUGS Initiative on Forensic Geology(FG).The meeting held on 4^(th) April 2016 at Piccadilly Place,Manchester,UK under the Chairmanship of Prof.Jose P.Calvo(JC),Secretary General,IUGS.The other attendees of the meeting were Prof.Marko Komac(MK),Vice-President of the IUGS,Dr.Laurence Donnelly(LD),Chair of the IUGS Initiative on Forensic Geology(IFG)and a Forensic Geologist and Police Search Adviser,Dr.Alastair Ruffel(AL),Forensic Geologist at Queens University,Belfast,who has significant experience in forensic geology and in working with law enforcement agencies,and Inspector Colin Hope(CH),National Search Advisor at the UK National Crime Agency.
基金This research was supported by the Korea Institute for Advancement of Technology(KIAT)Grant Funded by the Korea Government(MOTIE)(P0012724,The Competency Development Program for Industry Specialist)and the Soonchunhyang University Research Fund.
文摘In this research,we developed a plugin for our automated digital forensics framework to extract and preserve the evidence from the Android and the IOS-based mobile phone application,Instagram.This plugin extracts personal details from Instagram users,e.g.,name,user name,mobile number,ID,direct text or audio,video,and picture messages exchanged between different Instagram users.While developing the plugin,we identified resources available in both Android and IOS-based devices holding key forensics artifacts.We highlighted the poor privacy scheme employed by Instagram.This work,has shown how the sensitive data posted in the Instagram mobile application can easily be reconstructed,and how the traces,as well as the URL links of visual messages,can be used to access the privacy of any Instagram user without any critical credential verification.We also employed the anti-forensics method on the Instagram Android’s application and were able to restore the application from the altered or corrupted database file,which any criminal mind can use to set up or trap someone else.The outcome of this research is a plugin for our digital forensics ready framework software which could be used by law enforcement and regulatory agencies to reconstruct the digital evidence available in the Instagram mobile application directories on both Android and IOS-based mobile phones.
基金supported by the National Natural Science Foundation of China(82202078)the Major Project of the National Social Science Foundation of China(23&ZD203)+3 种基金the Open Project of the Key Laboratory of Forensic Genetics of the Ministry of Public Security(2022FGKFKT05)the Center for Archaeological Science of Sichuan University(23SASA01)the 1‧3‧5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(ZYJC20002)the Sichuan Science and Technology Program(2024NSFSC1518).
文摘Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descent to understand kinship,migration patterns,and population dynamics.Within forensic science,forensic investigative genetic genealogy(FIGG)has gained prominence by leveraging next-generation sequencing technologies and population-specific genomic resources,opening useful investigative avenues.In this review,we synthesize current knowledge,underscore recent advancements,and discuss the growing role of FIGG in forensic genomics.FIGG has been pivotal in revitalizing dormant inquiries and offering genetic leads in numerous cold cases.Its effectiveness relies on the extensive single-nucleotide polymorphism profiles contributed by individuals from diverse populations to specialized genomic databases.Advances in computational genomics and the growth of human genomic databases have spurred a profound shift in the application of genetic genealogy across forensics,anthropology,and ancient DNA studies.As the field progresses,FIGG is evolving from a nascent practice into a more sophisticated and specialized discipline,shaping the future of forensic investigations.
文摘Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2021R1I1A3049788).
文摘In today’s digital era,the rapid evolution of image editing technologies has brought about a significant simplification of image manipulation.Unfortunately,this progress has also given rise to the misuse of manipulated images across various domains.One of the pressing challenges stemming from this advancement is the increasing difficulty in discerning between unaltered and manipulated images.This paper offers a comprehensive survey of existing methodologies for detecting image tampering,shedding light on the diverse approaches employed in the field of contemporary image forensics.The methods used to identify image forgery can be broadly classified into two primary categories:classical machine learning techniques,heavily reliant on manually crafted features,and deep learning methods.Additionally,this paper explores recent developments in image forensics,placing particular emphasis on the detection of counterfeit colorization.Image colorization involves predicting colors for grayscale images,thereby enhancing their visual appeal.The advancements in colorization techniques have reached a level where distinguishing between authentic and forged images with the naked eye has become an exceptionally challenging task.This paper serves as an in-depth exploration of the intricacies of image forensics in the modern age,with a specific focus on the detection of colorization forgery,presenting a comprehensive overview of methodologies in this critical field.
文摘The integration of phytochemistry into forensic science has emerged as a groundbreaking frontier,providing unprecedented insights into nature's secrets through the precise application of phytochemical fingerprinting of phytotoxins as a cutting-edge approach.This study explores the dynamic intersection of phytochemistry and forensic science,highlighting how the unique phytochemical profiles of toxic plants and their secondary metabolites,serve as distinctive markers for forensic investigations.By utilizing advanced techniques such as Ultra-High-Performance Liquid Chromatography(UHPLC)and High-Resolution Mass Spectrometry(HRMS),the detection and quantification of plant-derived are made more accurate in forensic contexts.Real-world case studies are presented to demonstrate the critical role of plant toxins in forensic outcomes and legal proceedings.The challenges,potential,and future prospects of integrating phytochemical fingerprinting of plant toxins into forensic science were discussed.This review aims to illuminate phytochemical fingerprinting of plant toxins as a promising tool to enhance the precision and depth of forensic analyses,offering new insights into the complex stories embedded in plant toxins.
文摘Objective:With the continuous changes in social production,the consumption th inking of the masses obviously cannot keep up with the speed of social developmen t,and insurance disputes are increasingly emerging.Among them,the shortcomings of personal injury claims are not prominent,and the theoretical knowledge is not co mplete.In order to improve the quality of professional talents and reduce claims dis putes,the feasibility of integrating forensic medicine into personal injury claims is ex plored.Methods:The professional attributes,subject attributes,knowledge system an d employment data of forensic medicine are analyzed and compared with the actual work of personal injury claims.Main results:Forensic medicine has its uniqueness i n on-site investigation,injury-disease relationship analysis,and resolution of doubts.I t is irreplaceable by other subjects.The subject attributes are consistent with the pe rsonal injury claims major,and personal injury claims itself has basic medical courses,so it is easier to accept forensic medicine.Conclusion:Under the current social bac kground,through the study of the forensic medicine system in the personal injury cl aims major,it has positive practical significance for its professional construction and talent training.
基金supported in part by Natural Science Foundation of Hubei Province of China under Grant 2023AFB016the 2022 Opening Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering under Grant 2022SDSJ02the Construction Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering under Grant 2019ZYYD007.
文摘Images and videos play an increasingly vital role in daily life and are widely utilized as key evidentiary sources in judicial investigations and forensic analysis.Simultaneously,advancements in image and video processing technologies have facilitated the widespread availability of powerful editing tools,such as Deepfakes,enabling anyone to easily create manipulated or fake visual content,which poses an enormous threat to social security and public trust.To verify the authenticity and integrity of images and videos,numerous approaches have been proposed,which are primarily based on content analysis and their effectiveness is susceptible to interference from various image or video post-processing operations.Recent research has highlighted the potential of file containers analysis as a promising forensic approach that offers efficient and interpretable results.However,there is still a lack of review articles on this kind of approach.In order to fill this gap,we present a comprehensive review of file containers-based image and video forensics in this paper.Specifically,we categorize the existing methods into two distinct stages,qualitative analysis and quantitative analysis.In addition,an overall framework is proposed to organize the exiting approaches.Then,the advantages and disadvantages of the schemes used across different forensic tasks are provided.Finally,we outline the trends in this research area,aiming to provide valuable insights and technical guidance for future research.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.
基金Supported by the National High Technology Research and Development Program of China(863 Program)(2015AA016006)the National Natural Science Foundation of China(60903220)
文摘The large scale and distribution of cloud computing storage have become the major challenges in cloud forensics for file extraction. Current disk forensic methods do not adapt to cloud computing well and the forensic research on distributed file system is inadequate. To address the forensic problems, this paper uses the Hadoop distributed file system （HDFS） as a case study and proposes a forensic method for efficient file extraction based on three-level （3L） mapping. First, HDFS is analyzed from overall architecture to local file system. Second, the 3L mapping of an HDFS file from HDFS namespace to data blocks on local file system is established and a recovery method for deleted files based on 3L mapping is presented. Third, a multi-node Hadoop framework via Xen virtualization platform is set up to test the performance of the method. The results indicate that the proposed method could succeed in efficient location of large files stored across data nodes, make selective image of disk data and get high recovery rate of deleted files.
文摘Advances in technological developments in Geographic Information Systems(GIS)has enabled the application of GIS in landscape mapping,environmental management,natural hazard risk and disaster management.As geographical information becomes more widely available through satellite and aerial imagery,the cost of software decreases and GIS expertise expands,it is most likely that the use of GIS will increase.The methodology has practical applications for police,crime scene investigators and forensic geoscientists.The aim is to develop GIS use in forensic search beyond mapping to offer a set of decision support tools that utilise the spatial analytical capabilities of GIS.This enables better management and understanding of the complicated and interrelated nature of a ground search.
文摘The aim of the present study was to evaluate the psychometric properties and dimensionality of the instrument Quality in Psychiatric Care-Forensic In-Patient Staff (QPC-FIPS) and to describe the perceived quality of psychiatric care among forensic inpatient service staff. A sample of 348 forensic inpatient staff from 18 forensic wards in Sweden participated in the study. A confirmatory factor analysis revealed a seven-factor structure with item loadings > 0.50 on expected factors, indicating adequate psychometric properties. The staff’s ratings of quality of care were high, 94% being positive. The highest ratings were found for the secluded-environment dimension and the lowest for the secure-environment dimension. Several factors influenced the ratings of quality of care, for instance, staff’s time to perform their duties and staff’s age. It is concluded that the QPC-FIPS can give valuable information about staff’s perceptions of the quality of care provided at inpatient forensic psychiatric care services, which can be used to identify areas for quality improvement. Use of the QPC-FIPS is an easy and inexpensive way to evaluate quality in forensic inpatient care, preferably in conjunction with the QPC-FIP instrument developed for forensic inpatients and covering the same items and dimensions.
文摘Traditional approaches to digital forensics reconstruct events within digital systems that often are not built for the creation of evidence; however,there is an emerging discipline of forensic readiness that examines what it takes to build systems and devices that produce digital data records for which admissibility is a requirement. This paper reviews the motivation behind research in this area,a generic technical solution that uses hardware-based security to bind digital records to a particular state of a device and proposed applications of this solution in concrete,practical scenarios. Research history in this area,the notion of secure digital evidence and a technical solution are discussed. A solution to creating hardware-based security in devices producing digital evidence was proposed in 2012. Additionally,this paper revises the proposal and discusses three distinct scenarios where forensic readiness of devices and secure digital evidence are relevant. It shows,how the different requirements of the three scenarios can be realized using a hardware-based solution. The scenarios are:lawful interception of voice communication,automotive black box,precise farming. These three scenarios come from very distinctive application domains. Nevertheless,they share a common set of security requirements for processes to be documented and data records to be stored.
文摘Research in virtualization technology has gained significant developments in recent years, which brings not only opportunities to the forensic community, but challenges as well. This paper discusses the potential roles of virtualization in digital forensics, examines the recent progresses which use the virtualization techniques to support modem computer forensics. The influences on digital forensics caused by virtualization technology are identified. Tools and methods in common digital forensic practices are analyzed, and experiences of our practice and reflections in this field are shared.
基金funded by National Natural Science Foundation of China(No.62272347,62072343,and 61802284)National Key Research Development Program of China(No.2019QY(Y)0206).
文摘The power system frequency fluctuations could be captured by digital recordings and extracted to compare with a reference database for forensic timestamp verification.It is known as the Electric Network Frequency(ENF)criterion,enabled by the properties of random fluctuations and intra-grid consistency.In essence,this is a task of matching a short random sequence within a long reference,whose accuracy is mainly concerned with whether this match could be uniquely correct.In this paper,we comprehensively analyze the factors affecting the reliability of ENF matching,including the length of test recording,length of reference,temporal resolution,and Signal-to-Noise Ratio(SNR).For synthetic analysis,we incorporate the first-order AutoRegressive(AR)ENF model and propose an efficient Time-Frequency Domain noisy ENF synthesis method.Then,the reliability analysis schemes for both synthetic and real-world data are respectively proposed.Through a comprehensive study,we quantitatively reveal that while the SNR is an important external factor to determine whether timestamp verification is viable,the length of test recording is the most important inherent factor,followed by the length of reference.However,the temporal resolution has little impact on performance.Finally,a practical workflow of the ENF-based audio timestamp verification system is proposed,incorporating the discovered results.
文摘We are living in a society constructed by many aspects as well as languages.There are many ways to deal with legal cases,language is also an active one among them.As it is proved that resultant of forensic linguistic researches do help around.
文摘Automated and autonomous decisions of image classification systems have essential applicability in this modern age even.Image-based decisions are commonly taken through explicit or auto-feature engineering of images.In forensic radiology,auto decisions based on images significantly affect the automation of various tasks.This study aims to assist forensic radiology in its biological profile estimation when only bones are left.A benchmarked dataset Radiology Society of North America(RSNA)has been used for research and experiments.Additionally,a locally developed dataset has also been used for research and experiments to cross-validate the results.A Convolutional Neural Network(CNN)-based model named computer vision and image processing-net(CVIP-Net)has been proposed to learn and classify image features.Experiments have also been performed on state-of-the-art pertained models,which are alex_net,inceptionv_3,google_net,Residual Network(resnet)_50,and Visual Geometry Group(VGG)-19.Experiments proved that the proposed CNN model is more accurate than other models when panoramic dental x-ray images are used to identify age and gender.The specially designed CNN-based achieved results in terms of standard evaluation measures including accuracy(98.90%),specificity(97.99%),sensitivity(99.34%),and Area under the Curve(AUC)-value(0.99)on the locally developed dataset to detect age.The classification rates of the proposed model for gender estimation were 99.57%,97.67%,98.99%,and 0.98,achieved in terms of accuracy,specificity,sensitivity,and AUC-value,respectively,on the local dataset.The classification rates of the proposed model for age estimation were 96.80%,96.80%,97.03%,and 0.99 achieved in terms of accuracy,specificity,sensitivity,and AUC-value,respectively,on the RSNA dataset.
