Forensic Analysis of Digital Dynamic Signatures: New Methods for Data Treatment and Feature Evaluation

This study explored digital dynamic signatures containing quantifiable dynamic data. The change in data content and nature necessitates the development of new data treatment approaches. A SignPad Omega digitizing tablet was used to assess measurement reproducibility, as well as within‐writer variation and the occurrence of correctly simulated features. Measurement reproducibility was found to be high except for pressure information. Within‐writer variation was found to be higher between days than on a same day. Occurrence of correct simulation was low for features such as signature size, trajectory length, and total signature time. Feature discrimination factors combining within‐writer variability and the occurrence of correctly simulated features were computed and show that signature size, trajectory length, and signature time are the features that perform the best for discriminating genuine from simulated signatures. A final experiment indicates that dynamic information can be used to create connections between simulation cases.     

Using Cluster Analysis and ICP‐MS to Identify Groups of Ecstasy Tablets in Sao Paulo State,Brazil

The variations found in the elemental composition in ecstasy samples result in spectral profiles with useful information for data analysis, and cluster analysis of these profiles can help uncover different categories of the drug. We provide a cluster analysis of ecstasy tablets based on their elemental composition. Twenty‐five elements were determined by ICP‐MS in tablets apprehended by Sao Paulo's State Police, Brazil. We employ the K‐means clustering algorithm along with C4.5 decision tree to help us interpret the clustering results. We found a better number of two clusters within the data, which can refer to the approximated number of sources of the drug which supply the cities of seizures. The C4.5 model was capable of differentiating the ecstasy samples from the two clusters with high prediction accuracy using the leave‐one‐out cross‐validation. The model used only Nd, Ni, and Pb concentration values in the classification of the samples.     

iCLIC Data Mining and Data Sharing workshop: The present and future of data mining and data sharing in the EU

Held at Southampton University's Highfield campus and hosted by iCLIC, an interdisciplinary core on Law, the Internet and Culture, the Data Mining and Data Sharing workshop brought together attendees and speakers from industry, government, academia and a range of disciplines alike. The workshop comprised two sessions, each with a keynote and an associated panel. The first session was chaired by Eleonora Rosati and dealt with copyright and database rights, data mining and data sharing. The second session, chaired by Sophie Stalla-Bourdillon, focussed on data protection, data mining and data sharing. The following report covers both sessions, associated panel discussions and the subsequent question and answer sessions.     

Validating TrueAllele® DNA mixture interpretation

Abstract: DNA mixtures with two or more contributors are a prevalent form of biological evidence. Mixture interpretation is complicated by the possibility of different genotype combinations that can explain the short tandem repeat (STR) data. Current human review simplifies this interpretation by applying thresholds to qualitatively treat STR data peaks as all‐or‐none events and assigning allele pairs equal likelihood. Computer review, however, can work instead with all the quantitative data to preserve more identification information. The present study examined the extent to which quantitative computer interpretation could elicit more identification information than human review from the same adjudicated two‐person mixture data. The base 10 logarithm of a DNA match statistic is a standard information measure that permits such a comparison. On eight mixtures having two unknown contributors, we found that quantitative computer interpretation gave an average information increase of 6.24 log units (min = 2.32, max = 10.49) over qualitative human review. On eight other mixtures with a known victim reference and one unknown contributor, quantitative interpretation averaged a 4.67 log factor increase (min = 1.00, max = 11.31) over qualitative review. This study provides a general treatment of DNA interpretation methods (including mixtures) that encompasses both quantitative and qualitative review. Validation methods are introduced that can assess the efficacy and reproducibility of any DNA interpretation method. An in‐depth case example highlights 10 reasons (at 10 different loci) why quantitative probability modeling preserves more identification information than qualitative threshold methods. The results validate TrueAllele^® DNA mixture interpretation and establish a significant information improvement over human review.     

微软复合文档结构分析及文件恢复

本文分析了微软复合文档类型的结构,对于数据恢复中因文件头损坏不能正常打开的情况,可通过分析整个文件结构,合理重构文件头,修复文件。     

针对海量数据的数字取证模型

随着互联网技术的发展,电子产品被广泛应用在各个领域。与此同时,涉及到数字证据的犯罪案件日益增多。目前,侦查取证人员面临的巨大挑战是需要在短时间内在存有海量数据的大容量存储介质中进行搜查取证活动,传统的数字取证模型难以应对。     

The Future of Consumer Web Data: A European/US Perspective

The article considers the subject of clickstream data from aEuropean/US perspective, taking into account the Data ProtectionFramework (Data Protection Directive 95/46/EC; Directive onPrivacy and Electronic Communications 2002/58/EC) and the USlegal framework and in particular, the Wiretap Act U.S.C. 2701(2004) and related statutes. It examines the extent to whichclickstream data is considered "personal data" within the DataProtection Directive and the implications to consumers and businesses.     

Allele frequencies for nine STR loci (D3S1358, vWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317, D7S820) in the Italian population

Genotype and allele frequencies for STR loci D3S1358, vWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317, D7S820 were investigated in 289 unrelated Italian Caucasian individuals from the North and South regions. After co-amplification by polymerase chain reaction, automatic DNA profiling of these nine STR loci was performed by ABI PRISM((R)) 310 DNA Genetic Analyzer. For each locus, statistical parameters for forensic and paternity purposes were then calculated; the combined power of discrimination and the combined power of exclusion of all nine loci were 0.9999999999917 and 0.99992 for the Northern population and 0.9999999999921 and 0.99991 for the Southern population.     

STR data for the 15 AmpFlSTR identifiler loci in the Western Romanian population

Allele frequencies for the 15 tetranucleotide short tandem repeat loci contained in the AmpFlSTR Identifiler kit were obtained from a population sample of 219 unrelated individuals born in the western part of Romania.