An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social Media Forensics

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.

Evaluation of a Novel 32 X-STR Loci Multiplex System in the Forensic Application

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.

Hyper-Tuned Convolutional Neural Networks for Authorship Verification in Digital Forensic Investigations

Authorship verification is a crucial task in digital forensic investigations,where it is often necessary to determine whether a specific individual wrote a particular piece of text.Convolutional Neural Networks(CNNs)have shown promise in solving this problem,but their performance highly depends on the choice of hyperparameters.In this paper,we explore the effectiveness of hyperparameter tuning in improving the performance of CNNs for authorship verification.We conduct experiments using a Hyper Tuned CNN model with three popular optimization algorithms:Adaptive Moment Estimation(ADAM),StochasticGradientDescent(SGD),andRoot Mean Squared Propagation(RMSPROP).The model is trained and tested on a dataset of text samples collected from various authors,and the performance is evaluated using accuracy,precision,recall,and F1 score.We compare the performance of the three optimization algorithms and demonstrate the effectiveness of hyperparameter tuning in improving the accuracy of the CNN model.Our results show that the Hyper Tuned CNN model with ADAM Optimizer achieves the highest accuracy of up to 90%.Furthermore,we demonstrate that hyperparameter tuning can help achieve significant performance improvements,even using a relatively simple model architecture like CNNs.Our findings suggest that the choice of the optimization algorithm is a crucial factor in the performance of CNNs for authorship verification and that hyperparameter tuning can be an effective way to optimize this choice.Overall,this paper demonstrates the effectiveness of hyperparameter tuning in improving the performance of CNNs for authorship verification in digital forensic investigations.Our findings have important implications for developing accurate and reliable authorship verification systems,which are crucial for various applications in digital forensics,such as identifying the author of anonymous threatening messages or detecting cases of plagiarism.

CVIP-Net: A Convolutional Neural Network-Based Model for Forensic Radiology Image Classification

Automated and autonomous decisions of image classification systems have essential applicability in this modern age even.Image-based decisions are commonly taken through explicit or auto-feature engineering of images.In forensic radiology,auto decisions based on images significantly affect the automation of various tasks.This study aims to assist forensic radiology in its biological profile estimation when only bones are left.A benchmarked dataset Radiology Society of North America(RSNA)has been used for research and experiments.Additionally,a locally developed dataset has also been used for research and experiments to cross-validate the results.A Convolutional Neural Network(CNN)-based model named computer vision and image processing-net(CVIP-Net)has been proposed to learn and classify image features.Experiments have also been performed on state-of-the-art pertained models,which are alex_net,inceptionv_3,google_net,Residual Network(resnet)_50,and Visual Geometry Group(VGG)-19.Experiments proved that the proposed CNN model is more accurate than other models when panoramic dental x-ray images are used to identify age and gender.The specially designed CNN-based achieved results in terms of standard evaluation measures including accuracy(98.90%),specificity(97.99%),sensitivity(99.34%),and Area under the Curve(AUC)-value(0.99)on the locally developed dataset to detect age.The classification rates of the proposed model for gender estimation were 99.57%,97.67%,98.99%,and 0.98,achieved in terms of accuracy,specificity,sensitivity,and AUC-value,respectively,on the local dataset.The classification rates of the proposed model for age estimation were 96.80%,96.80%,97.03%,and 0.99 achieved in terms of accuracy,specificity,sensitivity,and AUC-value,respectively,on the RSNA dataset.

Research on Metaverse Security and Forensics

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

Forensic Study on Objective Evaluation of Visual Acuity of Ametropia with the Event-related Potential P3

Objective In this study,we aimed to assess the characteristics of the P3 component from an event-related potential(ERP)that was induced by visual acuity(VA)processing.Furthermore,we sought to provide electrophysiological evidence for the objective evaluation of VA.Methods We recruited 32 participants with myopia-related ametropia.They reported no other ocular diseases and had an uncorrected VA of 4.0 in both eyes.We used the block letter“E”at different visual angles and orientations as the graphic stimuli.The oddball paradigm,consisting of 4 modules,was used for ERP analysis.The standard stimuli of each module were identical,with a visual angle of 1°15′.The visual angles of the target stimuli were 1°15′,55′,24′,and 15′.The VA test was performed on each eye separately for all participants,and all characteristics of the P3 component were analyzed.Results There was no significant difference in the P3 peak letencies between the target stimulation angle 1°15′group and the 55′group,or between the target stimulation angle 24′group and the 15′group.There was a significant difference in the P3 peak letencies between the target stimulation angle 1°15′group and the 24′group as well as the 15′group.There was a significant difference in the P3 peak letencies between the target stimulation angle 55′group and the 24′group as well as the 15′group.No significant differences were observed in the P3 amplitude between modules.Conclusion In the oddball paradigm,P3 elicitation indicated a cognitive response to the target stimuli.These data showed that the characteristics of P3 can be used as an objective evaluation of VA.

Comparison Study and Forensic Analysis between Experiment and Coupled Dynamics Simulation for Submerged Floating Tunnel Segment with Free Ends under Wave Excitations

This paper presents dynamic-behavior comparisons and related forensic analyses of a submerged floating tunnel(SFT)between numerical simulation and physical experiment under regular and irregular waves.The experiments are conducted in the 3Dwave tank with 1:33.3 scale,and the corresponding coupled time-domain simulation tool is devised for comparison.The entire SFT systemconsists of a long concrete tunnel and 12 tubular aluminummooring lines.Two numerical simulation models,the Cummins equation with 3D potential theory including second-order wave-body interaction effects and the much simpler Morison-equation-based formula with the lumped-massbased line model,are designed and compared.Forensic analyses for mooring-line adjustments in the simulation are carried out in view of the best representation of the physical system.After that,the measured pre-tension distribution and systemstiffness of twelvemooring lines arewell reproduced in the numericalmodel.Subsequently,the dynamic responses and mooring tensions of the SFT are compared under regular and irregular waves.The measured and simulated results coincide reasonably well for both regular-and irregular-wave conditions.

Enhancing CNN for Forensics Age Estimation Using CGAN and Pseudo-Labelling

Age estimation using forensics odontology is an important process in identifying victims in criminal or mass disaster cases.Traditionally,this process is done manually by human expert.However,the speed and accuracy may vary depending on the expertise level of the human expert and other human factors such as level of fatigue and attentiveness.To improve the recognition speed and consistency,researchers have proposed automated age estimation using deep learning techniques such as Convolutional Neural Network(CNN).CNN requires many training images to obtain high percentage of recognition accuracy.Unfortunately,it is very difficult to get large number of samples of dental images for training the CNN due to the need to comply to privacy acts.A promising solution to this problem is a technique called Generative Adversarial Network(GAN).GAN is a technique that can generate synthetic images that has similar statistics as the training set.A variation of GAN called Conditional GAN(CGAN)enables the generation of the synthetic images to be controlled more precisely such that only the specified type of images will be generated.This paper proposes a CGAN for generating new dental images to increase the number of images available for training a CNN model to perform age estimation.We also propose a pseudolabelling technique to label the generated images with proper age and gender.We used the combination of real and generated images to trainDentalAge and Sex Net(DASNET),which is a CNN model for dental age estimation.Based on the experiment conducted,the accuracy,coefficient of determination(R2)and Absolute Error(AE)of DASNET have improved to 87%,0.85 and 1.18 years respectively as opposed to 74%,0.72 and 3.45 years when DASNET is trained using real,but smaller number of images.

Computer Forensics Framework for Efficient and Lawful Privacy-Preserved Investigation

Privacy preservation(PP)in Digital forensics(DF)is a conflicted and non-trivial issue.Existing solutions use the searchable encryption concept and,as a result,are not efficient and support only a keyword search.Moreover,the collected forensic data cannot be analyzed using existing well-known digital tools.This research paper first investigates the lawful requirements for PP in DF based on the organization for economic co-operation and development OECB)privacy guidelines.To have an efficient investigation process and meet the increased volume of data,the presented framework is designed based on the selective imaging concept and advanced encryption standard(AES).The proposed framework has two main modules,namely Selective Imaging Module(SIM)and Selective Analysis Module(SAM).The SIM and SAM modules are implemented based on advanced forensic format 4(AFF4)and SleuthKit open source forensics frameworks,respectively,and,accordingly,the proposed framework is evaluated in a forensically sound manner.The evaluation result is compared with other relevant works and,as a result,the proposed solution provides a privacy-preserving,efficient forensic imaging and analysis process while having also sufficient methods.Moreover,the AFF4 forensic image,produced by the SIM module,can be analyzed not only by SAM,but also by other well-known analysis tools available on the market.

Internet of Things for Digital Forensics Application in Saudi Arabia

Despite the extensive empirical literature relating to the Internet of Things (IoT), surprisingly few attempts have sought to establish the ways in which digital forensics can be applied to undertake detailed examinations regarding IoT frameworks. The existing digital forensic applications have effectively held back efforts to align the IoT with digital forensic strategies. This is because the forensic applications are ill-suited to the highly complex IoT frameworks and would, therefore, struggle to amass, analyze and test the necessary evidence that would be required by a court. As such, there is a need to develop a suitable forensic framework to facilitate forensic investigations in IoT settings. Nor has considerable progress been made in terms of collecting and saving network and server logs from IoT settings to enable examinations. Consequently, this study sets out to develop and test the FB system which is a lightweight forensic framework capable of improving the scope of investigations in IoT environments. The FB system can organize the management of various IoT devices found in a smart apartment, all of which is controlled by the owner’s smart watch. This will help to perform useful functions, automate the decision-making process, and ensure that the system remains secure. A Java app is utilized to simulate the FB system, learning the user’s requirements and security expectations when installed and employing the MySQL server as a means of logging the communications of the various IoT devices.

我国司法鉴定立法涉及的重大问题研究

2005年,全国人民代表大会常务委员会通过的《关于司法鉴定管理问题的决定》(以下简称《决定》)作为司法鉴定领域内唯一的专门法律性文件,其颁布与实施初步实现了统一司法鉴定管理体制。但随着目前法治的进步及司法鉴定领域出现的诸多问题亟需法律予以规制,司法鉴定立法再次成为关注焦点。司法鉴定立法不仅面临着《决定》制定中遗留的老问题,亦交织着《决定》施行后衍生的新问题。需要在已有制度运行基础上,对司法鉴定立法涉及的重大问题展开深入研究,分别从宏观、中观和微观层面来予以探讨,以期能够逐渐形成具有系统性、前瞻性和相对成熟性的立法共识。

Forensics: Collection of Sound Digital Evidence

This summary paper will discuss the concept of forensic evidence and evidence collection methods. Emphasis will be placed on the techniques used to collect forensically sound digital evidence for the purpose of introduction to digital forensics. This discussion will thereafter result in identifying and categorizing the different types of digital forensics evidence and a clear procedure for how to collect forensically sound digital evidence. This paper will further discuss the creation of awareness and promote the idea that competent practice of computer forensics collection is important for admissibility in court.

区块链电子取证技术的公安应用及法律规制研究

区块链技术作为一种去中心化的分布式账本技术,具有防止证据篡改,实现证据可追溯性的特点,有力契合了公安机关取证工作的需要。本文通过对公安机关应用区块链电子技术的实践价值和理论风险的分析,论证了区块链取证和区块链存证所面临的实践问题。以实际案例探讨区块链电子取证技术的可行路径,构想了公安机关区块链电子取证平台方案,并结合平台建设和运营中的关键技术和难点问题,提出具体的应用场景方案和推广建议。针对上链前、上链中、上链后的取证核心程序,归纳以“技术自证”为核心的电子数据证据鉴真规则,补齐“技治主义”治理规则,制定电子数据的非法证据排除规则,构建去中心化的“司法+联盟链”办案系统。

深圳汉族人群42个常染色体短串联重复序列基因座的遗传多态性

【目的】调查深圳汉族人群42个常染色体短串联重复序列(STR)基因座(含41个非CODIS系统STR基因座)等位基因的遗传多态性,研究其在法医鉴定中的应用价值。【方法】采用AGCU21+1和阅微MR23荧光扩增试剂盒对深圳汉族人群435个无关个体STR基因座进行序列多态性分析。通过Modified-Powerstates和arlequin v3.5软件统计等位基因频率、法医遗传学参数并进行Hardy-Weinberg平衡检验。【结果】深圳汉族人群435个无关个体共检出418个等位基因,均符合Hardy-Weinberg平衡定律(P>0.05/42),频率分布在0.0011~0.5529之间。D1S1656和D21S1270基因座多态性最高,均检出16个等位基因;D4S2408基因座检出的等位基因最少;个体识别能力(DP)为0.7988(D1S1627)~0.9686(D7S3048),多态性信息含量(PIC)为0.5680(D1S1627)~0.8598(D7S3048),杂合度(H)为0.6276(D1S1627)~0.8782(D20S470)。【结论】42个常染色体STR基因座的等位基因在深圳地区汉族群体遗传多态性较好,具有较高的个体识别能力,在个体识别和亲权鉴定尤其是单亲或出现基因突变的情况下具有较高的应用价值;所得的数据亦为STR群体遗传学提供基础数据。

1例错误否定父权的嵌合体STR分析

随着科学技术的不断发展,亲子鉴定中的嵌合体案例逐渐被发现。亲子鉴定目前通常是在现场采取血样,也有少数机构采取口腔拭子进行STR分型检测。在排除医源性人造异源嵌合体和检材被污染风险因素后,当不同基因座出现多个等位基因异常情况时,往往会考虑被检者为先天嵌合体。但是,如果嵌合体的血液中只存在一种细胞群的时候,血样常染色体STR分型不会出现异常,很容易得出错误的鉴定结论,直接排除亲缘关系。本文所分析案例,就属此类非常罕见的情况。

说话人音频攻击与对抗技术研究综述

文中概括了说话人音频攻击与对抗技术的最新进展。由于说话人音频攻击已经成为语音应用安全的严重威胁,以WaveNet、Transformer和GAN三种模型在音频攻击技术中的应用作为节点,分别介绍以其为基础的音频攻击技术。音频对抗技术则以涵盖的攻击技术分为3类,分别是基础音频攻击、重放攻击和深度伪造攻击。系统地阐述了音频攻击与对抗技术的最新研究成果,并分析比较了各算法在不同条件下的优劣,同时还介绍了音频技术常用的数据集。最后结合该领域目前的研究现状,提出了说话人音频攻防对抗技术研究中亟待关注与研究的问题。

多个Y-STR等位基因缺失及AZF分析

本文探讨多个Y-STR基因座等位基因分型缺失特点及其与AZF(无精子因子)缺失相关性,为法医学应用提供参考。使用Y-STR试剂盒(Yfller Platinum、SureID PathFinder Plus)对23461份男性家系个体血样分析,发现4个及4个以上Y-STR分型缺失样本共14例,使用Y染色体微缺失检测试剂盒检测序列标签位点(sequence-tagged site,STS),根据缺失STS,评价样本Y染色体AZF区缺失情况。结果显示:多个Y-STR分型缺失比例为0.0597%(14/23461),短臂1例,长臂13例,来自不同家系,分型互不相同;13例长臂多个分型缺失样本在AZF区均检出STS缺失,1例短臂多个分型缺失样本未检见异常。本研究提示发生于Y染色体长臂多个STR分型缺失与AZF区微缺失存在对应性,该类分型个体存在不育的生物学基础。

论面向虚拟世界的多点并行取证规则

面对虚拟世界中的违规经营活动,传统电子取证固证技术面临取证成本高、证据易被篡改和合法性欠缺等问题。多点并行取证技术规则从间接证明理论出发,借助时空跨度大、随机性强的多个取证节点,以可控的经济成本对电子商务经营者的侵权或违约事实进行更有效的证据收集,同时赋予经营者合理的反证机会。这种技术规则在行政执法和消费者维权场域都具有广泛的适用空间,但在构建行政执法系统时需联系既有的监管标准,在取证和固证环节通过人机分离、数据备份等技术措施确保环境清洁。在搭建面向消费者的取证平台时,需恪守最小必要原则,通过审查平台企业经营资质等方式实现平台中立,利用公开透明的取证手段和完整的证据链条确保电子证据的证据能力。

利用犬类嗅觉搜索人体遗骸研究进展

命案侦查过程中,准确找到被丢弃、掩埋的人体遗骸至关重要。寻找人体遗骸的方法主要有人类的视觉搜索、空中探测、地球物理技术、远程成像技术以及犬类嗅觉搜索技术等。犬类嗅觉搜索人体遗骸技术是一种公认的具有时效性的非侵入性搜索方法,是法医调查中最有价值的搜索工具。本文通过系统查阅和总结相关文献资料,以人体遗骸分解产生的挥发性有机化合物为理论基础,探寻犬类嗅觉搜索人体遗骸技术的基本原理,对以人类血迹、人体组织、尸体腐败液、气味替代物作为嗅源训练犬类搜索人体遗骸技术在法医调查中的使用进行综述,从尸体腐败过程中挥发性有机化合物的检测、气味替代物和吸附装置的研发、犬类训练与使用的技战法等角度展望犬类嗅觉搜索人体遗骸技术的应用前景,以期为我国犬类嗅觉搜索人体遗骸技术的相关研究提供参考。

利用液相色谱-高分辨质谱研究5F-UR-144在家兔体内的代谢产物

本文分析5F-UR-144在家兔尿中的代谢物,探索其代谢方式及路径,从而建立5F-UR-144代谢物的检测方法。将家兔分为5F-UR-144组和空白对照组,采用液相色谱-高分辨质谱联用仪对肌注实验家兔的尿液经乙腈沉淀蛋白后进行检测,通过代谢软件建立代谢物筛查库,筛查出来的组分根据高分辨质谱碎片信息和结构解析软件分析其化学结构。经过仪器检测和数据分析家兔尿液中的代谢物,发现5F-UR-144通过氟基羧基化、烷基氧化羟基化和羧基化,部分与葡萄糖醛酸结合,产生了11种代谢物,并推断出其代谢路径。高分辨质谱可以准确测定化合物的分子式,通过二级碎片高分辨结果也能精确计算出碎片的化学元素组成,对比其他质谱在代谢物化学结构分析上有独特优势。该检测方法为吸食5F-UR-144案件的判定、代谢物检验和合成戒断药物提供了参考。