Objective Flock fibres are proposed as a tracer in cases where secondary transfer of the tracer is needed. Methods The research was carried out following a case in which people were suspected to commit large numbers o...Objective Flock fibres are proposed as a tracer in cases where secondary transfer of the tracer is needed. Methods The research was carried out following a case in which people were suspected to commit large numbers of burglaries. Fibres were applied to the vehicle of the suspects and collected from later crime scenes. A device was developed to assist in the appli- cation of fibres and a number of experiments on secondary transfer were carried out. Results The device can be used to apply many fibres homogeneously in a short time. A single contact will not fully deplete the first surface from flock fibres. 1%~15% of the fibres are transferred to the 3rd surface representing the crime scene. The actual number of transferred fibres is dependent on variables such as the choice of surfaces. Conclusion The results indicate that, given the selected parameters, it is realistic to expect that relatively large numbers of fibres are transferred to a crime scene and can be collected.展开更多
Forensic anthropological knowledge has been used in disaster victim identification(DVI)for over a century,but over the past decades,there have been a number of disaster events which have seen an increasing role for th...Forensic anthropological knowledge has been used in disaster victim identification(DVI)for over a century,but over the past decades,there have been a number of disaster events which have seen an increasing role for the forensic anthropologist.The experiences gained from some of the latest DVI operations have provided valuable lessons that have had an effect on the role and perceived value of the forensic anthropologist as part of the team managing the DVI process.This paper provides an overview of the ways in which forensic anthropologists may contribute to DVI with emphasis on how recent experiences and developments in forensic anthropology have augmented these contributions.Consequently,this paper reviews the value of forensic anthropological expertise at the disaster scene and in the mortuary,and discusses the way in which forensic anthropologists may use imaging in DVI efforts.Tissue-sampling strategies for DNA analysis,especially in the case of disasters with a large amount of fragmented remains,are also discussed.Additionally,consideration is given to the identification of survivors;the statistical basis of identification;the challenges related to some specific disaster scenarios;and education and training.Although forensic anthropologists can play a valuable role in different phases of a DVI operation,they never practice in isolation.The DVI process requires a multidisciplinary approach and,therefore,has a close collaboration with a range of forensic specialists.展开更多
Attribute-based identification systems are essential for forensic investigations because they help in identifying individuals.An item such as clothing is a visual attribute because it can usually be used to describe p...Attribute-based identification systems are essential for forensic investigations because they help in identifying individuals.An item such as clothing is a visual attribute because it can usually be used to describe people.The method proposed in this article aims to identify people based on the visual information derived from their attire.Deep learning is used to train the computer to classify images based on clothing content.We first demonstrate clothing classification using a large scale dataset,where the proposed model performs relatively poorly.Then,we use clothing classification on a dataset containing popular logos and famous brand images.The results show that the model correctly classifies most of the test images with a success rate that is higher than 70%.Finally,we evaluate clothing classification using footage from surveillance cameras.The system performs well on this dataset,labelling 70%of the test images correctly.展开更多
This article studies the application of models of OpenFace(an open-source deep learning algorithm)to forensics by using multiple datasets.The discussion focuses on the ability of the software to identify similarities ...This article studies the application of models of OpenFace(an open-source deep learning algorithm)to forensics by using multiple datasets.The discussion focuses on the ability of the software to identify similarities and differences between faces based on images from forensics.Experiments using OpenFace on the Labeled Faces in the Wild(LFW)-raw dataset,the LFW-deep funnelled dataset,the Surveillance Cameras Face Database(SCface)and ForenFace datasets showed that as the resolution of the input images worsened,the effectiveness of the models degraded.In general,the effect of the quality of the query images on the efficiency of OpenFace was apparent.Therefore,OpenFace in its current form is inadequate for application to forensics,but can be improved to offer promising uses in the field.展开更多
This review summarizes the scientific basis of forensic gait analysis and evaluates its use in the Netherlands,United Kingdom and Denmark,following recent critique on the admission of gait evidence in Canada.A useful ...This review summarizes the scientific basis of forensic gait analysis and evaluates its use in the Netherlands,United Kingdom and Denmark,following recent critique on the admission of gait evidence in Canada.A useful forensic feature is(1)measurable,(2)consistent within and(3)different between individuals.Reviewing the academic literature,this article found that(1)forensic gait features can be quantified or observed from surveillance video,but research into accuracy,validity and reliability of these methods is needed;(2)gait is variable within individuals under differing and constant circumstances,with speed having major influence;(3)the discriminative strength of gait features needs more research,although clearly variation exists between individuals.Nevertheless,forensic gait analysis has contributed to several criminal trials in Europe in the past 15 years.The admission of gait evidence differs between courts.The methods are mainly observer-based:multiple gait analysts(independently)assess gait features on video footage of a perpetrator and suspect.Using gait feature databases,likelihood ratios of the hypotheses that the observed individuals have the same or another identity can be calculated.Automated gait recognition algorithms calculate a difference measure between video clips,which is compared with a threshold value derived from a video gait recognition database to indicate likelihood.However,only partly automated algorithms have been used in practice.We argue that the scientific basis of forensic gait analysis is limited.However,gait feature databases enable its use in court for supportive evidence with relatively low evidential value.The recommendations made in this review are(1)to expand knowledge on inter-and intra-subject gait variabilities,discriminative strength and interdependency of gait features,method accuracies,gait feature databases and likelihood ratio estimations;(2)to compare automated and observer-based gait recognition methods;to design(3)an international standard method with known validity,reliability and proficiency tests for analysts;(4)an international standard gait feature data collection method resulting in database(s);(5)(inter)national guidelines for the admission of gait evidence in court;and(6)to decrease the risk for cognitive and contextual bias in forensic gait analysis.This is expected to improve admission of gait evidence in court and judgment of its evidential value.Several ongoing research projects focus on parts of these recommendations.展开更多
Malaysia Airlines flight 17 crashed on 17 July 2014 while flying over an area of armed conflict in eastern Ukraine.The first forensic trace evidence was collected after the human remains were transferred to a safe loc...Malaysia Airlines flight 17 crashed on 17 July 2014 while flying over an area of armed conflict in eastern Ukraine.The first forensic trace evidence was collected after the human remains were transferred to a safe location in the Netherlands for identification and repatriation.Disaster victim identification processes were therefore undertaken in concert with the forensic investigation.Prior to these processes,X-ray and computed tomography scanners were used to reveal foreign objects in the human remains,and a large number of these fragments were recovered after the forensic triage.A distinct group of metal fragments was identified as being potential remnants of high-energy foreign objects.Forensic analysis revealed that they were explosively deformed unalloyed steel fragments,some of which had shapes consistent with pre-formed metal fragments found in a 9N314M warhead used in Buk SA-11 missiles.Furthermore,thin film deposits of cockpit glass and aluminium were identified on the most heavily deformed side of some of the explosively deformed metal fragments,suggesting they came from outside the airplane.These findings supported early suspicions that Malaysia Airlines flight 17 was struck by a Buk SA-11 missile.展开更多
Interpreting a myocardial inflammation as causal,contributory or as of no significance at all in the cause of death can be challenging,especially in cases where other pathologic and/or medico-legal findings are also p...Interpreting a myocardial inflammation as causal,contributory or as of no significance at all in the cause of death can be challenging,especially in cases where other pathologic and/or medico-legal findings are also present.To further evaluate the significance of myocardial inflammation as a cause of death we performed a retrospective cohort study of forensic and clinical autopsy cases.We revised the spectrum of histological inflammatory parameters in the myocardium of 79 adult autopsy cases and related these to the reported cause of death.Myocardial slides were reviewed for the distribution and intensity of inflammatory cell infiltrations,the predominant inflammatory cell type,and the presence of inflammation-associated myocyte injury,fibrosis,edema and hemorrhage.Next,the cases were divided over three groups,based on the reported cause of death.Group 1(n=27)consisted of all individuals with an obvious unnatural cause of death.Group 2(n=29)included all individuals in which myocarditis was interpreted to be one out of more possible causes of death.Group 3(n=23)consisted of all individuals in which myocarditis was reported to be the only significant finding at autopsy,and no other cause of death was found.Systematic application of our histological parameters showed that only a diffuse increase of inflammatory cells could discriminate between an incidental presence of inflammation(Group 1)or a potentially significant one(Groups 2 and 3).No other histological parameter showed significant differences between the groups.Our results suggest that generally used histological parameters are often insufficient to differentiate an incidental myocarditis from a(potentially)significant one.展开更多
Recent years have witnessed significant developments in deep learning and artificial intelligence[1].For instance,remarkable improvements have been made in automated face comparison systems by using deep learning,comp...Recent years have witnessed significant developments in deep learning and artificial intelligence[1].For instance,remarkable improvements have been made in automated face comparison systems by using deep learning,compared with the classic approaches[2].The term“deep learning”is often used to refer to certain kinds of neural networks.The first publications on biological neural networks and the brain date back to the late 1800s[3].It was not until the rediscovery of the back-propagation algorithm[4]in 1986 that interest in the field was reignited.An artificial neural network is designed following a simple modelling of the brain,and involves a representation of neurons.A neuron receives a specific signal and converts to a different one.Neurons can also be used to learn from examples.They adjust a transfer function.Many neurons are linked together,and are often used in multiple layers.A visual overview is provided in Figure 1.An example of the application of neural networks is face recognition[5],where these networks examine images of people’s faces and find features,such as shapes of nose,ears,and mouth.In such networks,the parameters of thousands or more neurons are adjusted based on training to improve recognition performance.Combined with improved pattern recognition to detect the eyes,mouth,and the position of the face,they yield better results.展开更多
Human-made and natural disasters can result in severely fragmented,compromised,and commingled human remains.The related disaster victim identification(DVI)operations are invariably challenging,with the state of the re...Human-made and natural disasters can result in severely fragmented,compromised,and commingled human remains.The related disaster victim identification(DVI)operations are invariably challenging,with the state of the remains potentially precluding some identifications.Practitioners involved in these DVI operations will routinely face logistical,practical,and ethical challenges.This review provides information and guidance derived from firsthand experiences to individuals tasked with managing DVI operations with fragmented human remains.We outline several key issues that should be addressed during disaster preparedness planning and at the outset of an operation,when incident-specific strategies are developed.Specific challenges during recovery and examination of fragmented remains are addressed,highlighting the importance of experienced specialists at the scene and in the mortuary.DNA sample selection and sampling techniques are reviewed,as well as downstream effects of commingling and contamination,which can complicate reconciliation and emphasise the need for rigorous quality control.We also touch on issues that may arise during communication with families.While recommendations are provided,they are not intended as proscriptive policy but rather as an addition to the general recommendations given in the International Criminal Police Organization(INTERPOL)DVI Guide,to inform preparative discussions between government officials,judiciary,police,and forensic specialists.展开更多
Google Location Timeline,once activated,allows to track devices and save their locations.This feature might be useful in the future as available data for evidence in investigations.For that,the court would be interest...Google Location Timeline,once activated,allows to track devices and save their locations.This feature might be useful in the future as available data for evidence in investigations.For that,the court would be interested in the reliability of these data.The position is presented in the form of a pair of coordinates and a radius,hence the estimated area for tracked device is enclosed by a circle.This research focuses on the assessment of the accuracy of the locations given by Google Location History Timeline,which variables affect this accuracy and the initial steps to develop a linear multivariate model that can potentially predict the actual error with respect to the true location considering environmental variables.The determination of the potential influential variables(configuration of mobile device connectivity,speed of movement and environment)was set through a series of experiments in which the true position of the device was recorded with a reference Global Positioning System(GPS)device with a superior order of accuracy.The accuracy was assessed measuring the distance between the Google provided position and the de facto one,later referred to as Google error.If this Google error distance is less than the radius provided,we define it as a hit.The configuration that has the largest hit rate is when the mobile device has GPS available,with a 52%success.Then the use of 3G and 2G connection go with 38%and 33%respectively.The Wi-Fi connection only has a hit rate of 7%.Regarding the means of transport,when the connection is 2G or 3G,the worst results are in Still with a hit rate of 9%and the best in Car with 57%.Regarding the prediction model,the distances and angles from the position of the device to the three nearest cell towers,and the categorical(nonnumerical)variables of Environment and means of transport were taking as input variables in this initial study.To evaluate the usability of a model,a Model hit is defined when the actual observation is within the 95%confidence interval provided by the model.Out of the models developed,the one that shows the best results was the one that predicted the accuracy when the used network is 2G,with 76%of Model hits.The second model with best performance had only a 23%success(with the mobile network set to 3G).展开更多
Law enforcement agencies have a restricted area in which their powers apply,which is called their jurisdiction.These restrictions also apply to the Internet.However,on the Internet,the physical borders of the jurisdic...Law enforcement agencies have a restricted area in which their powers apply,which is called their jurisdiction.These restrictions also apply to the Internet.However,on the Internet,the physical borders of the jurisdiction,typically country borders,are hard to discover.In our case,it is hard to establish whether someone involved in criminal online behavior is indeed a Dutch citizen.We propose a way to overcome the arduous task of manually investigating whether a user on an Internet forum is Dutch or not.More precisely,we aim to detect that a given English text is written by a Dutch native author.To develop a detector,we follow a machine learning approach.Therefore,we need to prepare a specific training corpus.To obtain a corpus that is representative for online forums,we collected a large amount of English forum posts from Dutch and non-Dutch authors on Reddit.To learn a detection model,we used a bag-of-words representation to capture potential misspellings,grammatical errors or unusual turns of phrases that are characteristic of the mother tongue of the authors.For this learning task,we compare the linear support vector machine and regularized logistic regression using the appropriate performance metrics f1 score,precision,and average precision.Our results show logistic regression with frequency-based feature selection performs best at predicting Dutch natives.Further study should be directed to the general applicability of the results that is to find out if the developed models are applicable to other forums with comparable high performance.展开更多
In this paper,camera recognition with the use of deep learning technique is introduced.To identify the various cameras,their characteristic photo-response non-uniformity(PRNU)noise pattern was extracted.In forensic sc...In this paper,camera recognition with the use of deep learning technique is introduced.To identify the various cameras,their characteristic photo-response non-uniformity(PRNU)noise pattern was extracted.In forensic science,it is important,especially for child pornography cases,to link a photo or a set of photos to a specific camera.Deep learning is a sub-field of machine learning which trains the computer as a human brain to recognize similarities and differences by scanning it,in order to identify an object.The innovation of this research is the use of PRNU noise patterns and a deep learning technique in order to achieve camera identification.In this paper,AlexNet was modified producing an improved training procedure with high maximum accuracy of 80%–90%.DIGITS showed to have identified correctly six cameras out of 10 with a success rate higher than 75%in the database.However,many of the cameras were falsely identified indicating a fault occurring during the procedure.A possible explanation for this is that the PRNU signal is based on the quality of the sensor and the artefacts introduced during the production process of the camera.Some manufacturers may use the same or similar imaging sensors,which could result in similar PRNU noise patterns.In an attempt to form a database which contained different cameras of the same model as different categories,the accuracy rate was low.This provided further proof of the limitations of this technique,since PRNU is stochastic in nature and should be able to distinguish between different cameras from the same brand.Therefore,this study showed that current convolutional neural networks(CNNs)cannot achieve individualization with PRNU patterns.Nevertheless,the paper provided material for further research.展开更多
文摘Objective Flock fibres are proposed as a tracer in cases where secondary transfer of the tracer is needed. Methods The research was carried out following a case in which people were suspected to commit large numbers of burglaries. Fibres were applied to the vehicle of the suspects and collected from later crime scenes. A device was developed to assist in the appli- cation of fibres and a number of experiments on secondary transfer were carried out. Results The device can be used to apply many fibres homogeneously in a short time. A single contact will not fully deplete the first surface from flock fibres. 1%~15% of the fibres are transferred to the 3rd surface representing the crime scene. The actual number of transferred fibres is dependent on variables such as the choice of surfaces. Conclusion The results indicate that, given the selected parameters, it is realistic to expect that relatively large numbers of fibres are transferred to a crime scene and can be collected.
文摘Forensic anthropological knowledge has been used in disaster victim identification(DVI)for over a century,but over the past decades,there have been a number of disaster events which have seen an increasing role for the forensic anthropologist.The experiences gained from some of the latest DVI operations have provided valuable lessons that have had an effect on the role and perceived value of the forensic anthropologist as part of the team managing the DVI process.This paper provides an overview of the ways in which forensic anthropologists may contribute to DVI with emphasis on how recent experiences and developments in forensic anthropology have augmented these contributions.Consequently,this paper reviews the value of forensic anthropological expertise at the disaster scene and in the mortuary,and discusses the way in which forensic anthropologists may use imaging in DVI efforts.Tissue-sampling strategies for DNA analysis,especially in the case of disasters with a large amount of fragmented remains,are also discussed.Additionally,consideration is given to the identification of survivors;the statistical basis of identification;the challenges related to some specific disaster scenarios;and education and training.Although forensic anthropologists can play a valuable role in different phases of a DVI operation,they never practice in isolation.The DVI process requires a multidisciplinary approach and,therefore,has a close collaboration with a range of forensic specialists.
基金supported by the Netherlands Forensic Institute.
文摘Attribute-based identification systems are essential for forensic investigations because they help in identifying individuals.An item such as clothing is a visual attribute because it can usually be used to describe people.The method proposed in this article aims to identify people based on the visual information derived from their attire.Deep learning is used to train the computer to classify images based on clothing content.We first demonstrate clothing classification using a large scale dataset,where the proposed model performs relatively poorly.Then,we use clothing classification on a dataset containing popular logos and famous brand images.The results show that the model correctly classifies most of the test images with a success rate that is higher than 70%.Finally,we evaluate clothing classification using footage from surveillance cameras.The system performs well on this dataset,labelling 70%of the test images correctly.
基金supported by the Netherlands Forensic Institute.
文摘This article studies the application of models of OpenFace(an open-source deep learning algorithm)to forensics by using multiple datasets.The discussion focuses on the ability of the software to identify similarities and differences between faces based on images from forensics.Experiments using OpenFace on the Labeled Faces in the Wild(LFW)-raw dataset,the LFW-deep funnelled dataset,the Surveillance Cameras Face Database(SCface)and ForenFace datasets showed that as the resolution of the input images worsened,the effectiveness of the models degraded.In general,the effect of the quality of the query images on the efficiency of OpenFace was apparent.Therefore,OpenFace in its current form is inadequate for application to forensics,but can be improved to offer promising uses in the field.
文摘This review summarizes the scientific basis of forensic gait analysis and evaluates its use in the Netherlands,United Kingdom and Denmark,following recent critique on the admission of gait evidence in Canada.A useful forensic feature is(1)measurable,(2)consistent within and(3)different between individuals.Reviewing the academic literature,this article found that(1)forensic gait features can be quantified or observed from surveillance video,but research into accuracy,validity and reliability of these methods is needed;(2)gait is variable within individuals under differing and constant circumstances,with speed having major influence;(3)the discriminative strength of gait features needs more research,although clearly variation exists between individuals.Nevertheless,forensic gait analysis has contributed to several criminal trials in Europe in the past 15 years.The admission of gait evidence differs between courts.The methods are mainly observer-based:multiple gait analysts(independently)assess gait features on video footage of a perpetrator and suspect.Using gait feature databases,likelihood ratios of the hypotheses that the observed individuals have the same or another identity can be calculated.Automated gait recognition algorithms calculate a difference measure between video clips,which is compared with a threshold value derived from a video gait recognition database to indicate likelihood.However,only partly automated algorithms have been used in practice.We argue that the scientific basis of forensic gait analysis is limited.However,gait feature databases enable its use in court for supportive evidence with relatively low evidential value.The recommendations made in this review are(1)to expand knowledge on inter-and intra-subject gait variabilities,discriminative strength and interdependency of gait features,method accuracies,gait feature databases and likelihood ratio estimations;(2)to compare automated and observer-based gait recognition methods;to design(3)an international standard method with known validity,reliability and proficiency tests for analysts;(4)an international standard gait feature data collection method resulting in database(s);(5)(inter)national guidelines for the admission of gait evidence in court;and(6)to decrease the risk for cognitive and contextual bias in forensic gait analysis.This is expected to improve admission of gait evidence in court and judgment of its evidential value.Several ongoing research projects focus on parts of these recommendations.
文摘Malaysia Airlines flight 17 crashed on 17 July 2014 while flying over an area of armed conflict in eastern Ukraine.The first forensic trace evidence was collected after the human remains were transferred to a safe location in the Netherlands for identification and repatriation.Disaster victim identification processes were therefore undertaken in concert with the forensic investigation.Prior to these processes,X-ray and computed tomography scanners were used to reveal foreign objects in the human remains,and a large number of these fragments were recovered after the forensic triage.A distinct group of metal fragments was identified as being potential remnants of high-energy foreign objects.Forensic analysis revealed that they were explosively deformed unalloyed steel fragments,some of which had shapes consistent with pre-formed metal fragments found in a 9N314M warhead used in Buk SA-11 missiles.Furthermore,thin film deposits of cockpit glass and aluminium were identified on the most heavily deformed side of some of the explosively deformed metal fragments,suggesting they came from outside the airplane.These findings supported early suspicions that Malaysia Airlines flight 17 was struck by a Buk SA-11 missile.
文摘Interpreting a myocardial inflammation as causal,contributory or as of no significance at all in the cause of death can be challenging,especially in cases where other pathologic and/or medico-legal findings are also present.To further evaluate the significance of myocardial inflammation as a cause of death we performed a retrospective cohort study of forensic and clinical autopsy cases.We revised the spectrum of histological inflammatory parameters in the myocardium of 79 adult autopsy cases and related these to the reported cause of death.Myocardial slides were reviewed for the distribution and intensity of inflammatory cell infiltrations,the predominant inflammatory cell type,and the presence of inflammation-associated myocyte injury,fibrosis,edema and hemorrhage.Next,the cases were divided over three groups,based on the reported cause of death.Group 1(n=27)consisted of all individuals with an obvious unnatural cause of death.Group 2(n=29)included all individuals in which myocarditis was interpreted to be one out of more possible causes of death.Group 3(n=23)consisted of all individuals in which myocarditis was reported to be the only significant finding at autopsy,and no other cause of death was found.Systematic application of our histological parameters showed that only a diffuse increase of inflammatory cells could discriminate between an incidental presence of inflammation(Group 1)or a potentially significant one(Groups 2 and 3).No other histological parameter showed significant differences between the groups.Our results suggest that generally used histological parameters are often insufficient to differentiate an incidental myocarditis from a(potentially)significant one.
文摘Recent years have witnessed significant developments in deep learning and artificial intelligence[1].For instance,remarkable improvements have been made in automated face comparison systems by using deep learning,compared with the classic approaches[2].The term“deep learning”is often used to refer to certain kinds of neural networks.The first publications on biological neural networks and the brain date back to the late 1800s[3].It was not until the rediscovery of the back-propagation algorithm[4]in 1986 that interest in the field was reignited.An artificial neural network is designed following a simple modelling of the brain,and involves a representation of neurons.A neuron receives a specific signal and converts to a different one.Neurons can also be used to learn from examples.They adjust a transfer function.Many neurons are linked together,and are often used in multiple layers.A visual overview is provided in Figure 1.An example of the application of neural networks is face recognition[5],where these networks examine images of people’s faces and find features,such as shapes of nose,ears,and mouth.In such networks,the parameters of thousands or more neurons are adjusted based on training to improve recognition performance.Combined with improved pattern recognition to detect the eyes,mouth,and the position of the face,they yield better results.
文摘Human-made and natural disasters can result in severely fragmented,compromised,and commingled human remains.The related disaster victim identification(DVI)operations are invariably challenging,with the state of the remains potentially precluding some identifications.Practitioners involved in these DVI operations will routinely face logistical,practical,and ethical challenges.This review provides information and guidance derived from firsthand experiences to individuals tasked with managing DVI operations with fragmented human remains.We outline several key issues that should be addressed during disaster preparedness planning and at the outset of an operation,when incident-specific strategies are developed.Specific challenges during recovery and examination of fragmented remains are addressed,highlighting the importance of experienced specialists at the scene and in the mortuary.DNA sample selection and sampling techniques are reviewed,as well as downstream effects of commingling and contamination,which can complicate reconciliation and emphasise the need for rigorous quality control.We also touch on issues that may arise during communication with families.While recommendations are provided,they are not intended as proscriptive policy but rather as an addition to the general recommendations given in the International Criminal Police Organization(INTERPOL)DVI Guide,to inform preparative discussions between government officials,judiciary,police,and forensic specialists.
基金supported by the Nederlands Forensisch Instituut.
文摘Google Location Timeline,once activated,allows to track devices and save their locations.This feature might be useful in the future as available data for evidence in investigations.For that,the court would be interested in the reliability of these data.The position is presented in the form of a pair of coordinates and a radius,hence the estimated area for tracked device is enclosed by a circle.This research focuses on the assessment of the accuracy of the locations given by Google Location History Timeline,which variables affect this accuracy and the initial steps to develop a linear multivariate model that can potentially predict the actual error with respect to the true location considering environmental variables.The determination of the potential influential variables(configuration of mobile device connectivity,speed of movement and environment)was set through a series of experiments in which the true position of the device was recorded with a reference Global Positioning System(GPS)device with a superior order of accuracy.The accuracy was assessed measuring the distance between the Google provided position and the de facto one,later referred to as Google error.If this Google error distance is less than the radius provided,we define it as a hit.The configuration that has the largest hit rate is when the mobile device has GPS available,with a 52%success.Then the use of 3G and 2G connection go with 38%and 33%respectively.The Wi-Fi connection only has a hit rate of 7%.Regarding the means of transport,when the connection is 2G or 3G,the worst results are in Still with a hit rate of 9%and the best in Car with 57%.Regarding the prediction model,the distances and angles from the position of the device to the three nearest cell towers,and the categorical(nonnumerical)variables of Environment and means of transport were taking as input variables in this initial study.To evaluate the usability of a model,a Model hit is defined when the actual observation is within the 95%confidence interval provided by the model.Out of the models developed,the one that shows the best results was the one that predicted the accuracy when the used network is 2G,with 76%of Model hits.The second model with best performance had only a 23%success(with the mobile network set to 3G).
文摘Law enforcement agencies have a restricted area in which their powers apply,which is called their jurisdiction.These restrictions also apply to the Internet.However,on the Internet,the physical borders of the jurisdiction,typically country borders,are hard to discover.In our case,it is hard to establish whether someone involved in criminal online behavior is indeed a Dutch citizen.We propose a way to overcome the arduous task of manually investigating whether a user on an Internet forum is Dutch or not.More precisely,we aim to detect that a given English text is written by a Dutch native author.To develop a detector,we follow a machine learning approach.Therefore,we need to prepare a specific training corpus.To obtain a corpus that is representative for online forums,we collected a large amount of English forum posts from Dutch and non-Dutch authors on Reddit.To learn a detection model,we used a bag-of-words representation to capture potential misspellings,grammatical errors or unusual turns of phrases that are characteristic of the mother tongue of the authors.For this learning task,we compare the linear support vector machine and regularized logistic regression using the appropriate performance metrics f1 score,precision,and average precision.Our results show logistic regression with frequency-based feature selection performs best at predicting Dutch natives.Further study should be directed to the general applicability of the results that is to find out if the developed models are applicable to other forums with comparable high performance.
基金funded by the Netherlands Forensic Institute Den Haag,Netherlands.
文摘In this paper,camera recognition with the use of deep learning technique is introduced.To identify the various cameras,their characteristic photo-response non-uniformity(PRNU)noise pattern was extracted.In forensic science,it is important,especially for child pornography cases,to link a photo or a set of photos to a specific camera.Deep learning is a sub-field of machine learning which trains the computer as a human brain to recognize similarities and differences by scanning it,in order to identify an object.The innovation of this research is the use of PRNU noise patterns and a deep learning technique in order to achieve camera identification.In this paper,AlexNet was modified producing an improved training procedure with high maximum accuracy of 80%–90%.DIGITS showed to have identified correctly six cameras out of 10 with a success rate higher than 75%in the database.However,many of the cameras were falsely identified indicating a fault occurring during the procedure.A possible explanation for this is that the PRNU signal is based on the quality of the sensor and the artefacts introduced during the production process of the camera.Some manufacturers may use the same or similar imaging sensors,which could result in similar PRNU noise patterns.In an attempt to form a database which contained different cameras of the same model as different categories,the accuracy rate was low.This provided further proof of the limitations of this technique,since PRNU is stochastic in nature and should be able to distinguish between different cameras from the same brand.Therefore,this study showed that current convolutional neural networks(CNNs)cannot achieve individualization with PRNU patterns.Nevertheless,the paper provided material for further research.
