调动网民力量服务网监工作

相对于数千万网民而言，全国范围内的网络警察的数量还是太少了，并且，单纯依靠网监行政管理，也很难获取全方位、深层次的违法犯罪活动信息。为了更好地维护网络环境，有效地打击网络违法犯罪行为，网络警察可以通过各种渠道获取有关公共信息网络安全方面的情况，建立网络安全信息员队伍就是获取这类情报的重要渠道。这对搞好公共信息网络安全监察工作也是大有用处的。     

青岛市侦破『博易通运动网』特大网络赌博案

自今年一月青岛市开展集中打击赌博违法犯罪专项行动以来，青岛市公安局网监支队组织专门力量加大对赌博违法犯罪线索的搜集与摸排，并主动加强与治安等相关部门的信息沟通，以提高打击的针对性和时效性。经过3个多月的网上侦察，初步掌握了该市网上赌博的基本情况，并确定了重点打击的赌博网站——“博易通运动网”。     

法律法规

截至目前,我国已制定、发布了多部有关信息网络安全的法律、法规、部门规章及规范性文件,其中不乏涉及网络违法犯罪的条款,新修订《刑法》中也增设了关于针对和利用计算机信息系统犯罪的条款。另外,“两高”还颁布了多条涉及网络违法犯罪行为的司法解释。为打击网络违法犯罪活动提供了必要的法律依据。     

2004年度美国互联网犯罪报告及思考

本文对"2004年度美国互联网犯罪报告"做了详细介绍,从互联网犯罪类型、犯罪嫌疑人、受害者、犯罪嫌疑人和受害者的关系等方面进行分别阐述,并进一步分析其对我国打击互联网违法犯罪的借鉴意义。     

首都信息网络犯罪特点与对策研究

北京市近年来面临网络违法犯罪突出,网络违法犯罪案件大幅上升趋势。针对网络犯罪的特点,本文提出了打击与防范网络犯罪的对策,以及信息安全的支撑环境,提高打击犯罪的能力、加强国际协作,共同构建和谐网络社会。     

当前虚假信息诈骗的防控策略

针对近期较为频繁的手机网络诈骗犯罪行为的防控和打击,总结研究了一套完善的打防策略,对于治理相关违法犯罪很有借鉴意义。     

基于Android平台恶意代码逆向分析技术的研究

文章针对当前基于安卓平台恶意代码分析技术的滞后性,介绍了安卓平台的基本结构,结合目前基于安卓平台恶意代码的主要破坏方式,采用静态分析机制,研究了基于安卓平台恶意代码逆向分析技术,为公安机关打击移动网络环境下的违法犯罪活动提供技术支持。     

我国打击网络赌博取得初步成果

网络赌博已成为在我国发展最为迅速的新型赌博形式。我国自开展集中打击赌博违法犯罪专项行动以来，各地公安机关通过前期调查取证工作，成功破获了数百起赌博大要案件，其中网络赌博案件249起，抓获了一批赌头、庄家、代理人，摧毁了一批赌博窝点、网站，使本次打击赌博违法犯罪专项行动取得了初步成果。     

西方国家对信息网络安全监管的经验及对我国的启示

针对各类网络违法犯罪活动日益泛滥的严峻形势,文章介绍了美国等西方互联网发达国家在立法、执法、司法、社会监督等方面已形成的相对成熟运作体系,以及在防治网络违法犯罪方面取得的经验,对加强网络安全监管及打击网络违法犯罪等方面都启示颇多.该文提出了应结合中国具体国情,从推进立法、明确服务商责任、推行网络实名制、推进全社会共同监管和加强国际交流合作等方面来开展治理工作,多种措施并举防治网络违法犯罪.     

公安机关应对虚拟网络社交犯罪问题对策研究

虚拟网络社交作为当前信息社会人类交往方式的一种,其发展规模和社会影响力不断扩大,已经成为一种重要的交往方式。本文有针对的分析了手机微信等虚拟网络社交活动存在引发犯罪活动等弊端,指出了公安机关必须高度重视利用虚拟网络社交,尤其是微信等网络社交工具从事违法犯罪的问题,加强对网络社交活动的监管,打击利用虚拟网络社交从事违法犯罪问题,维护国家和公共安全,保障人民群众生命财产安全。     

等级保护下言息系统的量化综合评估

该文针对目前信息系统评估方法多从财务、管理效能方面进行评价,缺乏安全风险方面的考量这一现状,首次将信息安全风险引入信息系统的评价中,利用层次分析法构建了等级保护的评估模型.并以此评估了在等保三级安全要求下,单机工作模式和集中管控模式的优劣,验证了该评估模型的有效性.     

模糊数学在基于MVC模式的通用教学评价系统中的应用

网络教学平台促进学生有效提高学习效果,通用教学评价系统则为网络教学平台提供保障,其中对网络教学资源的评价是通用教学评价系统中一个重要的部分,本文通过对通用教学评价系统的分析,同时提出了网络教学资源评价的指标、步骤、方法、论述了网络教学资源评价的意义,以模糊数学作为工具,建立了对网络教学资源评价模型,改善了网络教学环境.保证了网络教学平台健康运行和发展.     

Country crime analysis using the self-organizing map,with special regard to demographic factors

Modern research on criminal phenomena has been revolving not only around preventing existing offenses, but also around analyzing the criminal phenomena as a whole so as to overcome potential happenings of similar incidents. Criminologists and international law enforcement have been attracted to the cause of examining demographic context on which a crime is likely to arise. Traditionally, little has been explored in using demographic variables as determinants of the aggregate level of crime in the crime literature. Rapid development and ubiquitous application of information technology enables academic field to perform crime analysis using visualization techniques. Automation and networking make it available to access massive amounts of crime data, typically in the form of crime statistics. In numerous fields, studies and research have shown that visualization techniques are valuable; in crime research, nevertheless, there is a general lack of its application. In order to efficiently and effectively process crime data, criminologists and law enforcement are in demand of a more powerful tool. The self-organizing map (SOM), one of the widely used neural network algorithms, may be an appropriate technique for this application. The purpose of this study is to apply the SOM to mapping countries with different situations of crime. A total of 56 countries and 28 variables are included in the study. We found that some roughly definite patterns of crime situation can be identified in traditionally homogeneous countries. In different countries, positive correlation on crime in some countries may have negative correlation in other countries. Overall, correlation of some factors on crime can still be concluded in most groups. Results of the study prove that the SOM can be a new tool for mapping criminal phenomena through processing of large amounts of crime data.     

CrimeTelescope: crime hotspot prediction based on urban and social media data fusion

Crime is a complex social issue impacting a considerable number of individuals within a society. Preventing and reducing crime is a top priority in many countries. Given limited policing and crime reduction resources, it is often crucial to identify effective strategies to deploy the available resources. Towards this goal, crime hotspot prediction has previously been suggested. Crime hotspot prediction leverages past data in order to identify geographical areas susceptible of hosting crimes in the future. However, most of the existing techniques in crime hotspot prediction solely use historical crime records to identify crime hotspots, while ignoring the predictive power of other data such as urban or social media data. In this paper, we propose CrimeTelescope, a platform that predicts and visualizes crime hotspots based on a fusion of different data types. Our platform continuously collects crime data as well as urban and social media data on the Web. It then extracts key features from the collected data based on both statistical and linguistic analysis. Finally, it identifies crime hotspots by leveraging the extracted features, and offers visualizations of the hotspots on an interactive map. Based on real-world data collected from New York City, we show that combining different types of data can effectively improve the crime hotspot prediction accuracy (by up to 5.2%), compared to classical approaches based on historical crime records only. In addition, we demonstrate the usability of our platform through a System Usability Scale (SUS) survey on a full prototype of CrimeTelescope.     

基于．NET平台绩效考核系统的开发和实现

绩效考核是对员工一段时间的工作、绩效等的考核,其结果可以为相关人事决策,个人制定发展计划,绩效管理体系的完善和提高等提供依据。该文设计一种基于绩效指标的绩效考核系统,以上下级考评方式为基础,并以ASP．NET为前台、SQL-SERVER为后台实现了该绩效考核的整个流程,结果表明该系统是一个实用,有效的绩效考核系统。     

Developing a frame of reference for <Emphasis Type="Italic">ex-ante</Emphasis> IT/IS investment evaluation

Investment appraisal techniques are an integral part of many traditional capital budgeting processes. However, the adoption of Information Systems (IS) and the development of resulting infrastructures are being increasingly viewed on the basis of consumption. Consequently, decision-makers are now moving away from the confines of rigid capital budgeting processes, which have traditionally compared IS with non-IS-related investments. With this in mind, the authors seek to dissect investment appraisal from the broader capital budgeting process to allow a deeper understanding of the mechanics involved with IS justification. This analysis presents conflicting perspectives surrounding the scope and sensitivity of traditional appraisal methods. In contributing to this debate, the authors present taxonomies of IS benefit types and associated natures, and discuss the resulting implications of using traditional appraisal techniques during the IS planning and decision-making process. A frame of reference that can be used to navigate through the variety of appraisal methods available to decision-makers is presented and discussed. Taxonomies of appraisal techniques that are classified by their respective characteristics are also presented. Perspectives surrounding the degree of involvement that financial appraisal should play during decision making and the limitations surrounding investment appraisal techniques are identified.     

基于.NET平台绩效考核系统的开发和实现

绩效考核是对员工一段时间的工作、绩效等的考核,其结果可以为相关人事决策,个人制定发展计划,绩效管理体系的完善和提高等提供依据。该文设计一种基于绩效指标的绩效考核系统,以上下级考评方式为基础,并以ASP.NET为前台、SQL-SERVER为后台实现了该绩效考核的整个流程,结果表明该系统是一个实用,有效的绩效考核系统。     

网上评标系统模型的研究与实现

针对现行评标过程中存在的不足,提出了更加完善、合理的基于群决策层次分析法的评标模型,并介绍了以此模型为基础的网上评标系统的总体结构、主要功能模块、开发平台及开发工具。经实例验证,借助于新提出的评标模型及网上评标系统进行评标,较目前使用的评标方法更加科学、公正、快捷。     

一种新的基于AUC的多类分类评估方法

基于ROC曲线分析的AUC方法最初用于评估二类分类,不能直接解决多类别的评估,如何有效地将其推广到多类别评估中是研究的热点问题。首先介绍一种基于一对多方法的多类别AUC评估方法F-AUC,在此基础上根据二叉树的构造思想提出一种新的多类别评估方法B-AUC。该方法在MBNC实验平台上编程实现,并和F-AUC方法进行比较和分析,结果表明该方法是可行的,在评估效果和速度效果上有良好的性能。