The AGCU X Plus STR system is a newly developed multiplex PCR kit that detects 32 X-chromosomal STR loci simultaneously.These are DXS6807,DXS9895,linkage group 1(DXS10148,DXS10135,DXS8378),DXS9902,DXS6795,DXS6810,DXS1...The AGCU X Plus STR system is a newly developed multiplex PCR kit that detects 32 X-chromosomal STR loci simultaneously.These are DXS6807,DXS9895,linkage group 1(DXS10148,DXS10135,DXS8378),DXS9902,DXS6795,DXS6810,DXS10159,DXS10162,DXS10164,DXS7132,linkage group 2(DXS10079,DXS10074,DXS10075),DXS981,DXS6800,DXS6803,DXS6809,DXS6789,DXS7424,DXS101,DXS7133,GATA172D05,GATA165B12,linkage group 3(DXS10103,HPRTB,DXS10101),GATA31E08 and linkage group 4(DXS8377,DXS10134,DXS7423).A major advantage of this kit is that it takes into account linkage between loci,in addition to detecting more X-STR loci.In order to evaluate the forensic application of 32 X-STR fl uorescence amplifi cation system,PCR settings,sensitivity,species specifi city,stability,DNA mixtures,concordance,stutter,sizing precision,and population genetics investigation were evaluated according to the Scientific Working Group on DNA Analysis Methods(SWGDAM)developmental validation guidelines.The study showed that the genotyping results of each locus were signifi cantly accurate when the DNA template was at least 62.5 pg.Complete profi les were obtained for the 1∶1 and 1∶3 combinations.A total of 209 unrelated individuals from Southern Chinese Han community,consisting of 84 females and 125 males,were selected for population studies,and 285 allele profi les were detected from 32 X-STR loci.The polymorphism information content(PIC)ranged from 0.2721 in DXS6800,to 0.9105 in DXS10135,with an average of 0.6798.DXS10135(PIC=0.9105)was the most polymorphic locus,with discrimination power(DP)of 0.9164 and 0.9871 for the male and female.The cumulative PD_(F),PD_(M),MEC_(trio) and MEC_(duo) valu es were all greater than 0.999999999.There were 78 different DXS10103-HPRTB-DXS10101 haplotypes among the 125 males,and the haplotype diversity was 0.9810.There was no signifi cant difference in the cumulative PD_(F),PD_(M),MEC_(trio) and MEC_(duo) values whether considering linkage or not.In summary,the new X-STR multiplex typing system is effective and reliable,which can be useful in human genetic analysis and kinship testing as a potent complement to autosomal STR typing.展开更多
In the early period of China,economy developed rapidly at the cost of environment.Recently,it is generally recognized that the heavily polluted environment not only puts a brake on economic development but also paces ...In the early period of China,economy developed rapidly at the cost of environment.Recently,it is generally recognized that the heavily polluted environment not only puts a brake on economic development but also paces negative impact on people’health as well as probably next decades of generations.Accordingly,the latest Environmental Protection Law revised in 2014 makes a clear‑cut division of environmental responsibility and regulates stricter penalties of breaching law.As the new environmental law is enforced gradually,environmental forensic is increasingly required in the process of ascertaining facts in judicial proceedings of environmental cases.Based on the outcomes of documentary analysis for all environmental cases judged on the basis of new environmental law,it is concluded that there still exists problems in the present system of environmental forensic.Thus,this paper is aimed to make proposition on improving Chinese environmental forensic system,which involves:(i)promoting capability of EFS to handle professional questions;(ii)develop price mechanism;(iii)multidepartments cooperate to establish unifying and complete EFS system;and(iv)enhance the probative value of results of EFS.Such protocol for amending present regulation on environmental forensic is of significant importance because a quality report of environmental forensic will contribute to provide strong probative evidence of culprits’activity of releasing contaminant into environment,degree of damages for victims,and above all,causality between the behavior of public nuisance and damages.展开更多
Network intrusion forensics is an important extension to present security infrastructure,and is becoming the focus of forensics research field.However,comparison with sophisticated multi-stage attacks and volume of se...Network intrusion forensics is an important extension to present security infrastructure,and is becoming the focus of forensics research field.However,comparison with sophisticated multi-stage attacks and volume of sensor data,current practices in network forensic analysis are to manually examine,an error prone,labor-intensive and time consuming process.To solve these problems,in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments,and fuse digital evidence from different sources such as hosts and sub-networks automatically.In the end,we evaluate the method on well-known KDD Cup1999 dataset.The results prove our method is very effective for real-time network forensics,and can provide comprehensible messages for a forensic investigators.展开更多
AIM To clarify the differences in views on forensic mental health(FMH) systems between the United Kingdom and Japan.METHODS We conducted a series of semi-structured interviews with six leading forensic psychiatrists. ...AIM To clarify the differences in views on forensic mental health(FMH) systems between the United Kingdom and Japan.METHODS We conducted a series of semi-structured interviews with six leading forensic psychiatrists. Based on a discussion by the research team, we created an interview form. After we finished conducting all the interviews, we qualitatively analyzed their content. RESULTS In the United Kingdom the core domain of FMH was risk assessment and management; however, in Japan, the core domain of FMH was psychiatric testimony. In the United Kingdom, forensic psychiatrists were responsible for ensuring public safety, and psychopathy was identified as a disease but deemed as not suitable for medical treatment. On the other hand, in Japan, psychopathy was not considered a mental illness. CONCLUSION In conclusion, there are considerable differences between the United Kingdom and Japan with regard to the concepts of FMH. Some ideas taken from both cultures for better FMH practice were suggested.展开更多
Objective Population genetic analysis based on genetic markers harbors valuable forensic applications.In this regard,it is informative and imperative to explore Han groups as they are the largest population of China.I...Objective Population genetic analysis based on genetic markers harbors valuable forensic applications.In this regard,it is informative and imperative to explore Han groups as they are the largest population of China.In particular,there is a largely underrepresented amount of information from recent decades regarding the southeast costal Han Chinese.Therefore,the aim of this study is to investigate the available genetic characteristics of the Han population living in the Jinjiang,Fujian Province,Southeastern China.Methods We sampled 858 saliva samples and used the commercially available Microreader^(TM) Y Prime Plus ID System to identify population data of Y-short tandem repeat(STR)loci of this region.Results A total of 822 different haplotypes were observed.The overall haplotype diversity,discriminatory power and haplotype match probability were 0.9999,0.9999 and 0.0012,respectively.Conclusion Our results showed that the Jinjiang Han population was closely genetically related to Han groups of China.Overall,we identified a set of 37 Y-STRs that are highly polymorphic,and that can provide meaningful information in forensic practice and human genetic research.展开更多
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 c...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.展开更多
The proliferation of cloud computing and internet of things has led to the connectivity of states and nations(developed and developing countries)worldwide in which global network provide platform for the connection.Di...The proliferation of cloud computing and internet of things has led to the connectivity of states and nations(developed and developing countries)worldwide in which global network provide platform for the connection.Digital forensics is a field of computer security that uses software applications and standard guidelines which support the extraction of evidences from any computer appliances which is perfectly enough for the court of law to use and make a judgment based on the comprehensiveness,authenticity and objectivity of the information obtained.Cybersecurity is of major concerned to the internet users worldwide due to the recent form of attacks,threat,viruses,intrusion among others going on every day among internet of things.However,it is noted that cybersecurity is based on confidentiality,integrity and validity of data.The aim of this work is make a systematic review on the application of machine learning algorithms to cybersecurity and cyber forensics and pave away for further research directions on the application of deep learning,computational intelligence,soft computing to cybersecurity and cyber forensics.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
Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the comp...Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.展开更多
Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hate...Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hatespeech, but they still suffer from ambiguity when differentiating between hateful and offensive content and theyalso lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm(WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs)for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to exploreand determine the optimal set of weights. The PSO algorithm adjusts the weights to optimize the performanceof the MLP as fine-tuning. Additionally, in this approach, two separate MLP models are employed. One MLPis dedicated to predicting degrees of truth membership, while the other MLP focuses on predicting degrees offalse membership. The difference between these memberships quantifies uncertainty, indicating the degree ofindeterminacy in predictions. The experimental results indicate the superior performance of our model comparedto previous work when evaluated on the Davidson dataset.展开更多
The development of high technology,for public life to provide a justification at the same time,also encouraged the spirit of cybercrime,to become more and more rampant.In network crime,electronic data is usually used ...The development of high technology,for public life to provide a justification at the same time,also encouraged the spirit of cybercrime,to become more and more rampant.In network crime,electronic data is usually used as the main evidence to determine the facts of the crime and plays an important role in the smooth trial of the case.But because electronic data on dependent,concealment,easy destructive strong science and technology,the forensics work is now in trouble.The mature use of blockchain technology can avoid existing problems to a certain extent,which is helpful to the smooth progress of electronic forensics.This paper on electronic evidence how to more effectively,combined with research blockchain technology,improve the efficiency of electronic evidence collection work.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
In this study, we aimed to study the pattern visual evoked potentials (P-VEPs) in two eyes with varying visual acuity in one eye and to provide an objective estimation of visual acuity by comparing P-VEPs in one and...In this study, we aimed to study the pattern visual evoked potentials (P-VEPs) in two eyes with varying visual acuity in one eye and to provide an objective estimation of visual acuity by comparing P-VEPs in one and two eyes. Thirty subjects were chosen, who had one eye with an acuity of 5.0, 4.85, 4.6, 4.0, or scieropia and obstructed vision and the other eye with an acuity of 5.0, respectively. P-VEPs were detected under the large grating stimuli at 3x4 spatial frequency, moderate grating stimuli (12× 16 spatial frequency) and small grating stimuli (48×64 spatial frequency). Under large grating stimuli, there was no significant difference in P100 peak latency between the groups, nor was there a significant difference between the amplitude of two eyes and the amplitude of one normal-vision eye. Under moderate and small grating stimuli, there was a significant difference in P100 peak latency between the group with both eyes having an acuity of 5.0 and the group with visual acuity below 4.0 in one eye. There was a significant difference in P100 amplitude between the group with visual acuity of 5.0 in both eyes and the group with one normal-vision eye. There was no significant difference in the amplitude of two eyes and the amplitude of one normal-vision eye between any other two groups. In forensic identification, characteristics and variability of P-VEPs in one and two eyes can be used to identify malingering or decline in visual acuity.展开更多
Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchang...Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchangeable image file format (EXIF) information of image for images authen- tication. In particular, the authors can identify whether the current image has been modified or not by utilizing the relevance between noise and EXIF parameters and comparing the real values with the estimated values of the EXIF parameters. Experimental results validate the proposed method. That is, the detecting system can identify the doctored image effectively.展开更多
On March 26,2010 an underwater explosion(UWE)led to the sinking of the ROKS Cheonan.The official Multinational Civilian-Military Joint Investigation Group(MCMJIG)report concluded that the cause of the underwater explo...On March 26,2010 an underwater explosion(UWE)led to the sinking of the ROKS Cheonan.The official Multinational Civilian-Military Joint Investigation Group(MCMJIG)report concluded that the cause of the underwater explosion was a 250 kg net explosive weight(NEW)detonation at a depth of 6 9 m from a DPRK"CHT-02D"torpedo.Kim and Gitterman(2012a)determined the NEW and seismic magnitude as 136 kg at a depth of approximately 8m and 2.04,respectively using basic hydrodynamics based on theoretical and experimental methods as well as spectral analysis and seismic methods.The purpose of this study was to clarify the cause of the UWE via more detailed methods using bubble dynamics and simulation of propellers as well as forensic seismology.Regarding the observed bubble pulse period of 0.990 s,0.976 s and 1.030 s were found in case of a 136NEW at a detonation depth of 8 m using the boundary element method(BEM)and 3D bubble shape simulations derived for a 136kg NEW detonation at a depth of 8 m approximately 5 m portside from the hull centerline.Here we show through analytical equations,models and 3D bubble shape simulations that the most probable cause of this underwater explosion was a 136 kg NEW detonation at a depth of 8m attributable to a ROK littoral"land control"mine(LCM).展开更多
As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it ma...As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it may lead to potential social,legal or private consequences.To this end,it is very necessary and also challenging to find effective methods to differentiate between them.In this paper,a novel leading digit law,also called Benford's law,based method to identify computer graphics is proposed.More specifically,statistics of the most significant digits are extracted from image's Discrete Cosine Transform(DCT) coefficients and magnitudes of image's gradient,and then the Support Vector Machine(SVM) based classifiers are built.Results of experiments on the image datasets indicate that the proposed method is comparable to prior works.Besides,it possesses low dimensional features and low computational complexity.展开更多
As a common medium in our daily life,images are important for most people to gather information.There are also people who edit or even tamper images to deliberately deliver false information under different purposes.T...As a common medium in our daily life,images are important for most people to gather information.There are also people who edit or even tamper images to deliberately deliver false information under different purposes.Thus,in digital forensics,it is necessary to understand the manipulating history of images.That requires to verify all possible manipulations applied to images.Among all the image editing manipulations,recoloring is widely used to adjust or repaint the colors in images.The color information is an important visual information that image can deliver.Thus,it is necessary to guarantee the correctness of color in digital forensics.On the other hand,many image retouching or editing applications or software are equipped with recoloring function.This enables ordinary people without expertise of image processing to apply recoloring for images.Hence,in order to secure the color information of images,in this paper,a recoloring detection method is proposed.The method is based on convolutional neural network which is quite popular in recent years.Unlike the traditional linear classifier,the proposed method can be employed for binary classification as well as multiple labels classification.The classification performance of different structure for the proposed architecture is also investigated in this paper.展开更多
Objective To evaluate the usefulness of quantitative electroencephalogram (QEEG), flash visual evoked potential (F-VEP) and auditory brainstem responses (ABR) as indicators of general neurological status. Method...Objective To evaluate the usefulness of quantitative electroencephalogram (QEEG), flash visual evoked potential (F-VEP) and auditory brainstem responses (ABR) as indicators of general neurological status. Methods Comparison was conducted on healthy controls (N=30) and patients with brain concussion (N=60) within 24 h after traumatic brain injury. Follow-up study of patient group was completed with the same standard paradigm 3 months later. All participants were recorded in multi-modality related potential testing in both early and late concussion at the same clinical setting. Glasgow coma scale, CT scanning, and physical examinations of neuro-psychological function, optic and auditory nervous system were performed before electroencephalogram (EEG) and evoked potential (EEG-EP) testing. Any participants showed abnormal changes of clinical examinations were excluded from the study. Average power of frequency spectrum and power ratios were selected for QEEG testing, and latency and amplitude of F-VEP and ABR were recorded. Results Between patients and normal controls, the results indicated: (1) Highly significance (P 〈 0.01) in average power of α1 and power ratios of θ/α1, 0/α2, α1/α2 of EEG recording; (2) N70-P 100 amplitude of F-VEP in significant difference at early brain concussion; and (3) apparent prolongation of Ⅰ~Ⅲ inter-peak latency of ABR appeared in some individuals at early stage after concussion. The follow-up study showed that some patients with concussion were also afflicted with characteristic changes of EEG components for both increments of α1 average power and θ/α2 power ratio after 3 months recording. Conclusion EEG testing has been shown to be more effective and sensitive than evoked potential tests alone on detecting functional state of patients with mild traumatic brain injury (MTBI). Increments of α1 average power and θ/α2 power ratio are the sensitive EEG parameters to determining early concussion and evaluating outcome of postconcussion symptoms (PCS). Follow-up study associated with persistent PCS may be consistent with the postulate of substantial biological, rather than psychological origin. The study suggests that combination of EEG and EP parameters can contribute to the evaluation of brain function as a whole for clinical and forensic applications.展开更多
In the paper,a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images.Compared with conventional convolutional neural network,color images can be proces...In the paper,a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images.Compared with conventional convolutional neural network,color images can be processed in a holistic manner in the proposed scheme,which makes full use of the correlation between RGB channels.And due to the use of convolutional neural network,it can effectively avoid the one-sidedness of artificial features.Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection.展开更多
According to the requirement of computer forensic and network forensic, a novel forensic computing model is presented, which exploits XML/OEM/RM data model, Data fusion technology, forensic knowledgebase, inference me...According to the requirement of computer forensic and network forensic, a novel forensic computing model is presented, which exploits XML/OEM/RM data model, Data fusion technology, forensic knowledgebase, inference mechanism of expert system and evidence mining engine. This model takes advantage of flexility and openness, so it can be widely used in mining evidence.展开更多
文摘The AGCU X Plus STR system is a newly developed multiplex PCR kit that detects 32 X-chromosomal STR loci simultaneously.These are DXS6807,DXS9895,linkage group 1(DXS10148,DXS10135,DXS8378),DXS9902,DXS6795,DXS6810,DXS10159,DXS10162,DXS10164,DXS7132,linkage group 2(DXS10079,DXS10074,DXS10075),DXS981,DXS6800,DXS6803,DXS6809,DXS6789,DXS7424,DXS101,DXS7133,GATA172D05,GATA165B12,linkage group 3(DXS10103,HPRTB,DXS10101),GATA31E08 and linkage group 4(DXS8377,DXS10134,DXS7423).A major advantage of this kit is that it takes into account linkage between loci,in addition to detecting more X-STR loci.In order to evaluate the forensic application of 32 X-STR fl uorescence amplifi cation system,PCR settings,sensitivity,species specifi city,stability,DNA mixtures,concordance,stutter,sizing precision,and population genetics investigation were evaluated according to the Scientific Working Group on DNA Analysis Methods(SWGDAM)developmental validation guidelines.The study showed that the genotyping results of each locus were signifi cantly accurate when the DNA template was at least 62.5 pg.Complete profi les were obtained for the 1∶1 and 1∶3 combinations.A total of 209 unrelated individuals from Southern Chinese Han community,consisting of 84 females and 125 males,were selected for population studies,and 285 allele profi les were detected from 32 X-STR loci.The polymorphism information content(PIC)ranged from 0.2721 in DXS6800,to 0.9105 in DXS10135,with an average of 0.6798.DXS10135(PIC=0.9105)was the most polymorphic locus,with discrimination power(DP)of 0.9164 and 0.9871 for the male and female.The cumulative PD_(F),PD_(M),MEC_(trio) and MEC_(duo) valu es were all greater than 0.999999999.There were 78 different DXS10103-HPRTB-DXS10101 haplotypes among the 125 males,and the haplotype diversity was 0.9810.There was no signifi cant difference in the cumulative PD_(F),PD_(M),MEC_(trio) and MEC_(duo) values whether considering linkage or not.In summary,the new X-STR multiplex typing system is effective and reliable,which can be useful in human genetic analysis and kinship testing as a potent complement to autosomal STR typing.
文摘In the early period of China,economy developed rapidly at the cost of environment.Recently,it is generally recognized that the heavily polluted environment not only puts a brake on economic development but also paces negative impact on people’health as well as probably next decades of generations.Accordingly,the latest Environmental Protection Law revised in 2014 makes a clear‑cut division of environmental responsibility and regulates stricter penalties of breaching law.As the new environmental law is enforced gradually,environmental forensic is increasingly required in the process of ascertaining facts in judicial proceedings of environmental cases.Based on the outcomes of documentary analysis for all environmental cases judged on the basis of new environmental law,it is concluded that there still exists problems in the present system of environmental forensic.Thus,this paper is aimed to make proposition on improving Chinese environmental forensic system,which involves:(i)promoting capability of EFS to handle professional questions;(ii)develop price mechanism;(iii)multidepartments cooperate to establish unifying and complete EFS system;and(iv)enhance the probative value of results of EFS.Such protocol for amending present regulation on environmental forensic is of significant importance because a quality report of environmental forensic will contribute to provide strong probative evidence of culprits’activity of releasing contaminant into environment,degree of damages for victims,and above all,causality between the behavior of public nuisance and damages.
基金supported by the National Natural Science Foundation of China under Grant No.60903166 the National High Technology Research and Development Program of China(863 Program) under Grants No.2012AA012506,No.2012AA012901,No.2012AA012903+9 种基金 Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20121103120032 the Humanity and Social Science Youth Foundation of Ministry of Education of China under Grant No.13YJCZH065 the Opening Project of Key Lab of Information Network Security of Ministry of Public Security(The Third Research Institute of Ministry of Public Security) under Grant No.C13613 the China Postdoctoral Science Foundation General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China under Grant No.km201410005012 the Research on Education and Teaching of Beijing University of Technology under Grant No.ER2013C24 the Beijing Municipal Natural Science Foundation Sponsored by Hunan Postdoctoral Scientific Program Open Research Fund of Beijing Key Laboratory of Trusted Computing Funds for the Central Universities, Contract No.2012JBM030
文摘Network intrusion forensics is an important extension to present security infrastructure,and is becoming the focus of forensics research field.However,comparison with sophisticated multi-stage attacks and volume of sensor data,current practices in network forensic analysis are to manually examine,an error prone,labor-intensive and time consuming process.To solve these problems,in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments,and fuse digital evidence from different sources such as hosts and sub-networks automatically.In the end,we evaluate the method on well-known KDD Cup1999 dataset.The results prove our method is very effective for real-time network forensics,and can provide comprehensible messages for a forensic investigators.
基金Supported by The Ministry of Health,Labour and Welfare of Japan from a Grant-in-Aid for Scientific Research,entitled "Tagai-koui wo sita seishin-shougai-sha no shakai-fukki-katei no kokusai-hikaku to iryou-keizai-teki-bunseki(International comparison of the process of rehabilitation and medical economic analysis of mentally disordered offenders)"
文摘AIM To clarify the differences in views on forensic mental health(FMH) systems between the United Kingdom and Japan.METHODS We conducted a series of semi-structured interviews with six leading forensic psychiatrists. Based on a discussion by the research team, we created an interview form. After we finished conducting all the interviews, we qualitatively analyzed their content. RESULTS In the United Kingdom the core domain of FMH was risk assessment and management; however, in Japan, the core domain of FMH was psychiatric testimony. In the United Kingdom, forensic psychiatrists were responsible for ensuring public safety, and psychopathy was identified as a disease but deemed as not suitable for medical treatment. On the other hand, in Japan, psychopathy was not considered a mental illness. CONCLUSION In conclusion, there are considerable differences between the United Kingdom and Japan with regard to the concepts of FMH. Some ideas taken from both cultures for better FMH practice were suggested.
基金This study was supported by the Shaanxi Basic Research Program of Natural Science(No.2021JQ-392).
文摘Objective Population genetic analysis based on genetic markers harbors valuable forensic applications.In this regard,it is informative and imperative to explore Han groups as they are the largest population of China.In particular,there is a largely underrepresented amount of information from recent decades regarding the southeast costal Han Chinese.Therefore,the aim of this study is to investigate the available genetic characteristics of the Han population living in the Jinjiang,Fujian Province,Southeastern China.Methods We sampled 858 saliva samples and used the commercially available Microreader^(TM) Y Prime Plus ID System to identify population data of Y-short tandem repeat(STR)loci of this region.Results A total of 822 different haplotypes were observed.The overall haplotype diversity,discriminatory power and haplotype match probability were 0.9999,0.9999 and 0.0012,respectively.Conclusion Our results showed that the Jinjiang Han population was closely genetically related to Han groups of China.Overall,we identified a set of 37 Y-STRs that are highly polymorphic,and that can provide meaningful information in forensic practice and human genetic research.
基金National Natural Science Foundation of China(No.61602109)Distinguished Young Professor Program of Donghua University,China(No.LZB2019003)+1 种基金Shanghai Science and Technology Innovation Action Plan,China(No.19511101802)Fundamental Research Funds for the Central Universities。
文摘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.
文摘The proliferation of cloud computing and internet of things has led to the connectivity of states and nations(developed and developing countries)worldwide in which global network provide platform for the connection.Digital forensics is a field of computer security that uses software applications and standard guidelines which support the extraction of evidences from any computer appliances which is perfectly enough for the court of law to use and make a judgment based on the comprehensiveness,authenticity and objectivity of the information obtained.Cybersecurity is of major concerned to the internet users worldwide due to the recent form of attacks,threat,viruses,intrusion among others going on every day among internet of things.However,it is noted that cybersecurity is based on confidentiality,integrity and validity of data.The aim of this work is make a systematic review on the application of machine learning algorithms to cybersecurity and cyber forensics and pave away for further research directions on the application of deep learning,computational intelligence,soft computing to cybersecurity and cyber forensics.
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.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2024-RS-2024-00437494)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.
文摘Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hatespeech, but they still suffer from ambiguity when differentiating between hateful and offensive content and theyalso lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm(WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs)for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to exploreand determine the optimal set of weights. The PSO algorithm adjusts the weights to optimize the performanceof the MLP as fine-tuning. Additionally, in this approach, two separate MLP models are employed. One MLPis dedicated to predicting degrees of truth membership, while the other MLP focuses on predicting degrees offalse membership. The difference between these memberships quantifies uncertainty, indicating the degree ofindeterminacy in predictions. The experimental results indicate the superior performance of our model comparedto previous work when evaluated on the Davidson dataset.
基金President’s Fund Natural Science Project Plan of Tarim University,“Research on Blockchain-based Electronic Evidence Fixation Method”(Project No.:TDZKSS202439)。
文摘The development of high technology,for public life to provide a justification at the same time,also encouraged the spirit of cybercrime,to become more and more rampant.In network crime,electronic data is usually used as the main evidence to determine the facts of the crime and plays an important role in the smooth trial of the case.But because electronic data on dependent,concealment,easy destructive strong science and technology,the forensics work is now in trouble.The mature use of blockchain technology can avoid existing problems to a certain extent,which is helpful to the smooth progress of electronic forensics.This paper on electronic evidence how to more effectively,combined with research blockchain technology,improve the efficiency of electronic evidence collection work.
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In this study, we aimed to study the pattern visual evoked potentials (P-VEPs) in two eyes with varying visual acuity in one eye and to provide an objective estimation of visual acuity by comparing P-VEPs in one and two eyes. Thirty subjects were chosen, who had one eye with an acuity of 5.0, 4.85, 4.6, 4.0, or scieropia and obstructed vision and the other eye with an acuity of 5.0, respectively. P-VEPs were detected under the large grating stimuli at 3x4 spatial frequency, moderate grating stimuli (12× 16 spatial frequency) and small grating stimuli (48×64 spatial frequency). Under large grating stimuli, there was no significant difference in P100 peak latency between the groups, nor was there a significant difference between the amplitude of two eyes and the amplitude of one normal-vision eye. Under moderate and small grating stimuli, there was a significant difference in P100 peak latency between the group with both eyes having an acuity of 5.0 and the group with visual acuity below 4.0 in one eye. There was a significant difference in P100 amplitude between the group with visual acuity of 5.0 in both eyes and the group with one normal-vision eye. There was no significant difference in the amplitude of two eyes and the amplitude of one normal-vision eye between any other two groups. In forensic identification, characteristics and variability of P-VEPs in one and two eyes can be used to identify malingering or decline in visual acuity.
基金supported by the National Natural Science Foundation of China under Grant Nos.61370195and 11101048Beijing Natural Science Foundation under Grant No.4132060the National Cryptography Development Foundation of China under Grant No.MMJJ201201002
文摘Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchangeable image file format (EXIF) information of image for images authen- tication. In particular, the authors can identify whether the current image has been modified or not by utilizing the relevance between noise and EXIF parameters and comparing the real values with the estimated values of the EXIF parameters. Experimental results validate the proposed method. That is, the detecting system can identify the doctored image effectively.
文摘On March 26,2010 an underwater explosion(UWE)led to the sinking of the ROKS Cheonan.The official Multinational Civilian-Military Joint Investigation Group(MCMJIG)report concluded that the cause of the underwater explosion was a 250 kg net explosive weight(NEW)detonation at a depth of 6 9 m from a DPRK"CHT-02D"torpedo.Kim and Gitterman(2012a)determined the NEW and seismic magnitude as 136 kg at a depth of approximately 8m and 2.04,respectively using basic hydrodynamics based on theoretical and experimental methods as well as spectral analysis and seismic methods.The purpose of this study was to clarify the cause of the UWE via more detailed methods using bubble dynamics and simulation of propellers as well as forensic seismology.Regarding the observed bubble pulse period of 0.990 s,0.976 s and 1.030 s were found in case of a 136NEW at a detonation depth of 8 m using the boundary element method(BEM)and 3D bubble shape simulations derived for a 136kg NEW detonation at a depth of 8 m approximately 5 m portside from the hull centerline.Here we show through analytical equations,models and 3D bubble shape simulations that the most probable cause of this underwater explosion was a 136 kg NEW detonation at a depth of 8m attributable to a ROK littoral"land control"mine(LCM).
文摘As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it may lead to potential social,legal or private consequences.To this end,it is very necessary and also challenging to find effective methods to differentiate between them.In this paper,a novel leading digit law,also called Benford's law,based method to identify computer graphics is proposed.More specifically,statistics of the most significant digits are extracted from image's Discrete Cosine Transform(DCT) coefficients and magnitudes of image's gradient,and then the Support Vector Machine(SVM) based classifiers are built.Results of experiments on the image datasets indicate that the proposed method is comparable to prior works.Besides,it possesses low dimensional features and low computational complexity.
文摘As a common medium in our daily life,images are important for most people to gather information.There are also people who edit or even tamper images to deliberately deliver false information under different purposes.Thus,in digital forensics,it is necessary to understand the manipulating history of images.That requires to verify all possible manipulations applied to images.Among all the image editing manipulations,recoloring is widely used to adjust or repaint the colors in images.The color information is an important visual information that image can deliver.Thus,it is necessary to guarantee the correctness of color in digital forensics.On the other hand,many image retouching or editing applications or software are equipped with recoloring function.This enables ordinary people without expertise of image processing to apply recoloring for images.Hence,in order to secure the color information of images,in this paper,a recoloring detection method is proposed.The method is based on convolutional neural network which is quite popular in recent years.Unlike the traditional linear classifier,the proposed method can be employed for binary classification as well as multiple labels classification.The classification performance of different structure for the proposed architecture is also investigated in this paper.
基金This work was supported in part by grants from National Natural Science Foundation of China (No. 30571909) China Postdoctoral Science Foundation (No. 32134006) Foundation of Soozhow University (No. Q4134405).
文摘Objective To evaluate the usefulness of quantitative electroencephalogram (QEEG), flash visual evoked potential (F-VEP) and auditory brainstem responses (ABR) as indicators of general neurological status. Methods Comparison was conducted on healthy controls (N=30) and patients with brain concussion (N=60) within 24 h after traumatic brain injury. Follow-up study of patient group was completed with the same standard paradigm 3 months later. All participants were recorded in multi-modality related potential testing in both early and late concussion at the same clinical setting. Glasgow coma scale, CT scanning, and physical examinations of neuro-psychological function, optic and auditory nervous system were performed before electroencephalogram (EEG) and evoked potential (EEG-EP) testing. Any participants showed abnormal changes of clinical examinations were excluded from the study. Average power of frequency spectrum and power ratios were selected for QEEG testing, and latency and amplitude of F-VEP and ABR were recorded. Results Between patients and normal controls, the results indicated: (1) Highly significance (P 〈 0.01) in average power of α1 and power ratios of θ/α1, 0/α2, α1/α2 of EEG recording; (2) N70-P 100 amplitude of F-VEP in significant difference at early brain concussion; and (3) apparent prolongation of Ⅰ~Ⅲ inter-peak latency of ABR appeared in some individuals at early stage after concussion. The follow-up study showed that some patients with concussion were also afflicted with characteristic changes of EEG components for both increments of α1 average power and θ/α2 power ratio after 3 months recording. Conclusion EEG testing has been shown to be more effective and sensitive than evoked potential tests alone on detecting functional state of patients with mild traumatic brain injury (MTBI). Increments of α1 average power and θ/α2 power ratio are the sensitive EEG parameters to determining early concussion and evaluating outcome of postconcussion symptoms (PCS). Follow-up study associated with persistent PCS may be consistent with the postulate of substantial biological, rather than psychological origin. The study suggests that combination of EEG and EP parameters can contribute to the evaluation of brain function as a whole for clinical and forensic applications.
基金The work was supported in part by the Natural Science Foundation of China under Grants(Nos.61772281,61502241,61272421,61232016,61402235 and 61572258)in part by the Natural Science Foundation of Jiangsu Province,China under Grant BK20141006+1 种基金in part by the Natural Science Foundation of the Universities in Jiangsu Province under Grant 14KJB520024the PAPD fund and the CICAEET fund.
文摘In the paper,a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images.Compared with conventional convolutional neural network,color images can be processed in a holistic manner in the proposed scheme,which makes full use of the correlation between RGB channels.And due to the use of convolutional neural network,it can effectively avoid the one-sidedness of artificial features.Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection.
基金Supported by the Scientific and TechnologicalBureau of the Ministry of Public Security of P.R.China ,the Projectof the Network Supervising Bureau(2005yycxhbst117) the Project ofthe 15th Overall Plan of Education Department of Hubei Province(2004d349) the Project of the 15th Overall Plan of Social ScienceFund of Hubei Province([2005]073)
文摘According to the requirement of computer forensic and network forensic, a novel forensic computing model is presented, which exploits XML/OEM/RM data model, Data fusion technology, forensic knowledgebase, inference mechanism of expert system and evidence mining engine. This model takes advantage of flexility and openness, so it can be widely used in mining evidence.