Language translation for file paths

Forensic examiners are frequently confronted with content in languages that they do not understand, and they could benefit from machine translation into their native language. But automated translation of file paths is a difficult problem because of the minimal context for translation and the frequent mixing of multiple languages within a path. This work developed a prototype implementation of a file-path translator that first identifies the language for each directory segment of a path, and then translates to English those that are not already English nor artificial words. Brown's LA-Strings utility for language identification was tried, but its performance was found inadequate on short strings and it was supplemented with clues from dictionary lookup, Unicode character distributions for languages, country of origin, and language-related keywords. To provide better data for language inference, words used in each directory over a large corpus were aggregated for analysis. The resulting directory-language probabilities were combined with those for each path segment from dictionary lookup and character-type distributions to infer the segment's most likely language. Tests were done on a corpus of 50.1 million file paths looking for 35 different languages. Tests showed 90.4% accuracy on identifying languages of directories and 93.7% accuracy on identifying languages of directory/file segments of file paths, even after excluding 44.4% of the paths as obviously English or untranslatable. Two of seven proposed language clues were shown to impair directory-language identification. Experiments also compared three translation methods: the Systran translation tool, Google Translate, and word-for-word substitution using dictionaries. Google Translate usually performed the best, but all still made errors with European languages and a significant number of errors with Arabic and Chinese.     

浅谈数码照相在交通事故处理中的运用

目前,大多数基层公安机关,特别是一线交通事故处理部门仍然使用传统胶片相机,在一定程度上影响了办案效率和办案质量。文章试图对数码照相在交通事故处理中的作用做些粗浅的分析,旨在引起大家对数码照相在交通事故处理中重要性的认识,掌握运用数码照相机时应注意的问题。     

紫外分光光度法测定糖肾康颗粒中总多糖的含量

目的：建立分光光度法测定糖肾康颗粒中总多糖的含量。方法：紫外分光光度法，苯酚．硫酸法。结果：总多糖在1．0658-8．5262范围内呈良好线性关系，r=0．9997。平均回收率为99．14％，RSD为0．98％(n=5)。结论：方法简便准确，重复性好，可作为糖肾康颗粒的含量测定方法。     

Shifting forensic science focus from means to purpose: A path forward for the discipline?

Forensic science is facing a persistent crisis that is often addressed by organizational responses, with a strong focus on the improvement and standardisation of means and processes. However, organisations and processes are highly dependent on the political, economical and legal structures in which they operate. This may explain why most proposed solutions had difficulties in addressing the crisis up to now, as they could hardly be applied transversally to all forensic science models. Moreover, new tools and technologies are continuously developed by a quasi-infinite number of different scientific disciplines, thus leading to further diversity and fragmentation of forensic science. In this paper, it is proposed to shift the focus from means to purpose and consider forensic science current challenges in terms of discipline, before addressing organisations’ specific issues. As a distinct discipline, forensic science can refocus research and development on shared principles and purposes, such as reconstructing, monitoring, and preventing crime and security issues. This focus change will facilitate a better understanding of the trace as the object of study of forensic science and eventually lead to a more impactful and long-lasting effect. This approach will also foster the development of a forensic science culture (instead of a primarily technological culture) unified by purpose rather than means through more relevant education and research.     

Descrambling data on solid-state disks by reverse-engineering the firmware

Data recovery is an important component of digital forensic research. Although recovering data from hard drives or small-scale mobile devices has been well studied, solid-state disks (SSDs) have a very different internal architecture and some additional functions, and it is not clear whether these differences will have an effect on data recovery. Data scrambling is an additional function of an SSD controller which can improve data reliability, but makes data recovery difficult. In this research, the dedicated flash software was first introduced that can acquire the physical image of an SSD without destroying the device hardware. Based on the software, a validation experiment was presented to evaluate the effect of data scrambling on data recovery and the causes of the effect were analyzed. Then two approaches to descrambling the data in the flash chips were proposed and their advantages and disadvantages discussed. After that, a procedure to identify the scrambling seeds that are used to descramble the scrambled data was described. Finally, descrambling software was implemented based on the second descrambling method. The experiment shows that this software can successfully descramble the data from an SSD flash drive regardless of the internal structure of the scrambler in the SSD controller and can generate an unscrambled physical image on which most existing data-recovery techniques can be effective.     

技术侦察中应用数字图像技术问题探讨

数字图像技术与传统图像技术比较有许多长处,应用于秘密照相取证、秘密录像取证及电子监控取证等技术侦察工作中有助于提高查控犯罪效率。应用中应保证正确性、有效性,提高规范化水平。     

试论格式条款的缺陷及修订建议

由于格式条款本身存在一些无法克服的局限,加之我国在制定合同法时受当时的历史和环境的影响,不可避免地使格式条款存在一些缺陷。这种缺陷在一定程度上可能背离契约自由和公平合理的原则。建议通过修订的方式来进一步完善我国合同法中的格式条款,以达到契约的公平、合理、正义。     

HPLC测定盐酸左布比卡因右旋异构体含量

目的:建立盐酸左布比卡因右旋异构体的测定方法。方法:采用手性色谱柱(CHROMTECH AGP 100.0 mm×4.0 mm,5μm),以0.02 mol/L的磷酸盐缓冲液-异丙醇(90∶10)为流动相,检测波长215 nm。结果:盐酸左布比卡因左旋异构体和右旋异构体达到基线分离,定量限为2 ng,检测限为0.6 ng。结论:HPLC能够有效分离、检测左布比卡因原料及注射液中的右旋异构体。     

The 2013 CLSR-LSPI seminar on electronic identity: The global challenge – Presented at the 8th International Conference on Legal,Security and Privacy issues in IT Law (LSPI) November 11–15, 2013, Tilleke & Gibbins International Ltd., Bangkok,Thailand

We are the middle of a global identity crisis. New notions of identity are made possible in the online world where people eagerly share their personal data and leave ‘digital footprints’. Multiple, partial identities emerge distributed across cyberspace divorced from the physical person. The representation of personal characteristics in data sets, together with developing technologies and systems for identity management, in turn change how we are identified. Trustworthy means of electronic identification is now a key issue for business, governments and individuals in the fight against online identity crime. Yet, along with the increasing economic value of digital identity, there are also risks of identity misuse by organisations that mine large data sets for commercial purposes and in some cases by governments. Data proliferation and the non-transparency of processing practices make it impossible for the individual to track and police their use. Potential risks encompass not only threats to our privacy, but also knowledge-engineering that can falsify digital profiles attributed to us with harmful consequences. This panel session will address some of the big challenges around identity in the digital age and what they mean for policy and law (its regulation and protection). Questions for discussion include: What does identity mean today? What types of legal solutions are fit for purpose to protect modern identity interests? What rights, obligations and responsibilities should be associated with our digital identities? Should identity management be regulated and who should be held liable and for what? What should be the role of private and public sectors in identity assurance schemes? What are the global drivers of identity policies? How can due process be ensured where automated technologies affect the rights and concerns of citizens? How can individuals be more empowered to control their identity data and give informed consent to its use? How are biometrics and location-tracking devices used in body surveillance changing the identity landscape?     

Automated evaluation of approximate matching algorithms on real data

Bytewise approximate matching is a relatively new area within digital forensics, but its importance is growing quickly as practitioners are looking for fast methods to screen and analyze the increasing amounts of data in forensic investigations. The essential idea is to complement the use of cryptographic hash functions to detect data objects with bytewise identical representation with the capability to find objects with bytewise similar representations.Unlike cryptographic hash functions, which have been studied and tested for a long time, approximate matching ones are still in their early development stages and evaluation methodology is still evolving. Broadly, prior approaches have used either a human in the loop to manually evaluate the goodness of similarity matches on real world data, or controlled (pseudo-random) data to perform automated evaluation.This work's contribution is to introduce automated approximate matching evaluation on real data by relating approximate matching results to the longest common substring (LCS). Specifically, we introduce a computationally efficient LCS approximation and use it to obtain ground truth on the t5 set. Using the results, we evaluate three existing approximate matching schemes relative to LCS and analyze their performance.