计算机犯罪及其立法和理论之回应(一)

计算机犯罪尤其是网络犯罪与传统犯罪的巨大差异,对于现行刑法典、刑事诉讼法典及刑事司法协助规范形成巨大冲击,同时也造成传统刑法理论与现实犯罪态势的冲突,导致立法和理论略显滞后而与时代不合拍.对于国内立法、国际刑法与刑事司法协助、刑法理论创新以及刑事司法方面进行全方位的反思,对于惩罚和防范日益猖獗的计算机犯罪,是当务之急.     

计算机犯罪及其立法和理论之回应(二)

二、立法和理论的应有回应 面对计算机犯罪所导致的立法滞后与理论滞后,刑法理论界应当直面挑战,先于立法机关而从理论上探讨反计算机犯罪立法的可行模式与法条设置,并及时修正传统刑法理论,指导刑事司法。 (一)立法的回应 与世界上发达国家相比,中国当前惩治计算机犯罪的刑事立法以及处罚计算机违法行为的行政法规略显滞后,难以适应司法现实。我们认为,总体而言,应当从以下几个方面加以完善。 1.制定专门的反计算机犯罪法 由于计算机犯罪尤其是网络环境中的计算机犯罪与传统犯罪相比较,存在诸多独特之处,因而发达国家在立法上往往倾向于制定、颁行专门的反计算机犯罪法,而不是仅在刑     

我国电子商务欺诈犯罪的刑事法律界定

关于电子商务欺诈犯罪的刑法定位问题，目前国内有两种观点，一种观点认为电子商务犯罪与一般刑事犯罪存在不同特征(主体特定性、危害严重性、证据缺乏性等)，加上现行刑事立法对电子商务诈骗犯罪的规定存在不足，所以认为应该修改现行立法，增设专门的“电子商务诈骗罪”罪名；另一种观点主张电子商务欺诈犯罪属于以计算机为犯罪工具实施的传统财产型犯罪，并非真正意义上的能够成为一种独立犯罪类型的计算机犯罪。     

网络犯罪刑事管辖权问题研究

与传统犯罪相比,网络犯罪呈现出许多新的特点与形式,并由此引发出一些与传统刑事法律法规和刑法理论研究相冲突的问题。 本文试图以网络犯罪刑事管辖权作为研究的视角,以期对立法与司法有所裨益。     

我国的网络犯罪及其法律规制

网络犯罪是理论上提出的概念，或者说是依据犯罪学研究的特点进行归类划分的犯罪类型，而非我国刑法中规定的法定犯罪类型。正因如此，刑法理论界对什么是网络犯罪众说纷纭。如有的观点认为，网络犯罪是指以计算机资产为攻击对象或利用计算机为工具而实施的危害社会并应处以刑罚的行为；有的观点认为，网络犯罪是指以接入互联网的信息系统及其存储、传输的信息为犯罪对象，     

传统犯罪的e网络化及应对措施

传统犯罪的网络化方式及其类型 借助网络进行的传统犯罪.这类犯罪中,网络只起辅助工具的作用,使犯罪变得更加方便.没有网络,犯罪分子通过其他途径仍然可以实施该犯罪,其中一部分已在我国<刑法>第二百八十七条中规定.     

使用计算机诈骗罪比较研究

使用计算机诈骗是随着计算机科学技术的发展新出现的一种犯罪现象,它有不同于传统的普通诈骗罪的构成特征,其行为类型多种多样,不同类型案件的着手与既遂时间也各不相同.我国现行刑法没有规定使用计算机诈骗罪,对这类行为,理论界有人主张定盗窃罪,笔者主张定诈骗罪,并认为今后有必要借鉴国外的立法经验,增设单独的使用计算机诈骗罪.     

网络猥亵儿童犯罪与传统刑法之间张力研究——以骆某猥亵儿童案为例

信息网络时代为猥亵犯罪行为搭建了新的犯罪平台，倒逼传统刑法体系更新迭代。在骆某猥亵儿童案中，传统的刑法概念无法完全涵摄新型犯罪行为，以致无法在刑事层面对其予以合理规制。暴露出传统刑法的滞后性与信息时代之间具有不可忽视的张力，在网络猥亵儿童犯罪中，主要包括猥亵行为类型不够全面、“公共场所”的内涵模糊、“聚众实施”情节无明确判断标准等问题，对二者之间张力，需要从细化行为类型、扩充概念外延、明确判断标准等方面予以消解，以展现刑法推陈出新的包容姿态。     

网络环境下的治安问题研究与对策

随着网络的不断发展,网络环境下的违法犯罪层出不穷,许多的犯罪方式对我国的立法、刑事司法和治安管理工作提出了新的要求,笔者通过对网络环境下的传统违法犯罪的几种形式,得出互联网的特性对传统犯罪的影响,提出传统犯罪网络化的特点,在此基础之上,剖析我国网络环境下违法犯罪多发的原因,并以上述探析结论为根据,提出了构建完整的计算机网络环境下的犯罪法律体系的建议,提出了治理网络环境下的违法犯罪应该走的途径:通过各种法律手段及非法律手段相结合,预防和控制网络环境下的违法犯罪。     

利用网上支付平台实施犯罪的现实状况及其法律规制

网络第三方支付平台作为依托互联网、计算机信息系统发展及金融支付模式改革而出现的电子支付中介,是一种高科技、高智能工具,与传统犯罪相区别,利用网络第三方支付平台实施犯罪呈现出犯罪主体智能化、犯罪侦查取证难等特点。有必要通过加强金融监管、完善税收规则、积极建构网络犯罪立法等措施对利用网上支付平台实施犯罪的行为进行有效的法律规制。     

Proposed Methodology for Cyber Criminal Profiling

ABSTRACT

Criminal profiling is an important tool employed by law enforcement agencies in their investigations. Criminal profiling is much more than an educated guess; it requires a scientific-based methodology. Cyber crimes are occurring at an alarming rate globally. Law enforcement agencies follow similar techniques to traditional crimes. As is the case in traditional criminal investigation, cyber criminal profiling is a key component in cyber crime investigations as well. This paper examines cyber criminal profiling techniques prevalent today, including inductive and deductive profiling, and the need for employing a hybrid technique that incorporates both inductive and deductive profiling. This paper proposes a cyber criminal profiling methodology based on the hybrid technique. Criminal behavior and characteristics are identified by analyzing the data against a predefined set of metrics.     

基于异构信息网络的假币犯罪信息分析系统

传统的犯罪查询的查询条件是文本信息,查询结果是有序的文档列表,这种方式无法展示结果之间的关系.基于异构信息网络以信息网络的形式重构假币犯罪信息数据,构建了假币犯罪信息网络,使用人名消歧的技术建立假币犯罪信息网络中嫌疑人之间的关系,并使用排序学习方法研究假币犯罪信息网络中的节点相关性问题,设计并实现了假币犯罪信息分析系统,通过以实体对象为查询项和网络图为查询结果的方式解决假币犯罪数据的查询问题.     

Legal limits of search and seizure for digital forensic in Korea

Policy actions against various cyberspace crimes should respond both systematically and specifically to the nature of each crime and its accompanying evidence. Voice phishing as an emerging internet fraud practice has already victimized many unsuspecting consumers and hit the headlines frequently; cyber prostitution, pornography, illegal duplication of software, and online gambling have also become routine problems. Anonymity and facelessness in cyberspace distort one’s sense of guilt and allow for rapid collection, modification, and distribution of illegal and harmful information that disrupts social order and public safety. The purpose of this research is to examine the concept and type of cyber crime and to trace its trend in the Republic of Korea in the recent years. Due to its informational, national, global, and networking properties, cyber crime often puts serious restraints on conventional criminal justice procedures that cannot compromise such legal issues as individual safety and protection of privacy. If made accessible, information stored in private computers has potential to serve as decisive evidence in many criminal litigations. The Korean criminal procedure law promulgated on July 18, 2011 and enforced since January 1, 2012 contains an express provision permitting the search and seizure of digital evidence. But this partial code does not explicitly define the admissibility of digital evidence and acceptable methods of examining it. Hence, it is one of the goals of this research to identify problems pertaining to this law and suggest ways to improve it.     

论网络犯罪对刑事证据制度的冲击

本文将结合网络犯罪的发展态势,针对刑事法律在网络犯罪狂潮所面临的挑战,分析、探索刑事证据制度如何应对网络犯罪的冲击。     

论网络犯罪形成的心理因素与防控

现代生活中计算机网络已经越来越普及,在人们享受网络科技带来的快捷方便的同时,网络犯罪也悄悄潜入了人们的生活,黑客病毒、网络诈骗以及色情暴力信息随着网络如潮水般涌来,对网络犯罪进行防控已经刻不容缓。本文简要介绍了目前网络犯罪的特点,然后从心理学的角度分析了网络犯罪形成的原因,最后针对网络犯罪心理的成因,从政府部门的角度提出了一些预防措施。     

网络赌博犯罪现状分析与污染探讨

随着计算机网络技术的迅速发展和普及,网络犯罪接踵而来。网络空间最大的特征是其虚拟性,利用网络犯罪的行为和造成的后果却是客观存在的、应给与否定评价的现实实际。网络赌博犯罪中,网络因素的介入,使得传统赌博犯罪的构成要素、表现形态有了新的样态。网络赌博犯罪活动越来越猖獗,已经严重危害社会治安秩序。传统刑法理论如何应对网络赌博犯罪的冲击,摆脱适用的尴尬局面,是研究网络犯罪迫切需要解决的难题。     

Controlling computer crime in Germany

The main means employed to fight growing computer misuse in Germany has been to invoke the use of criminal law. This article details the relevant provisions of substantive German criminal law and discusses the emerging problems in criminal procedure and in the practice of prosecuting computer crime. The term ‘computer crime’ and its meaning in criminal law and legal theory are also described in greater detail. The approach adopted by the German legislature to fight computer crime, which is characterized by using very complex and special statutes, enacted parallel to existing and less complex traditional statutes is criticized. This article argues that within the vast field of computer crime, two types of offences should be differentiated. The first group comprises offences which are accidentally committed by using a computer, while the second group consists of crimes that structurally did not exist before. It is argued that in respect of this second category of ‘real computer crime'—and in light of the emerging problems in criminal procedure—a new paradigm of information law is needed.     

基于聚类的数据加权优化在犯罪预测中的应用

近年来，我国传统暴力犯罪与成年人犯罪呈下降态势，但是，犯罪案由层出不穷。为有效提升公安实践工作中犯罪预测能力，打击各类违法犯罪事件,本文针对犯罪数据，提出一种新型犯罪预测模型。利用密度聚类分析方法将犯罪数据分类，然后进行数据降维提取关键属性生成特征数据，继而对特征数据进行加权优化并采用机器学习的方式对特征数据进行学习，从而预测犯罪案由。实验结果表明，与传统方法相比，本文方法具有更好的预测效果，为公安实践工作中类似案件的侦破和预防，提供新的路径支撑。     

数据恢复技术在计算机犯罪侦查中的应用

在计算机犯罪案件中,犯罪分子往往破坏现场、毁灭证据,以逃脱罪责。数据恢复技术具有将被破坏的数据还原为原始数据的功能。把数据恢复技术应用于计算机犯罪侦查中,将为我们有效地打击计算机犯罪开辟一条新的途径。     

Classification System for Serial Criminal Patterns

The data mining field in computer science specializes in extracting implicit information that is distributed across the stored data records and/or exists as associations among groups of records. Criminal databases contain information on the crimes themselves, the offenders, the victims as well as the vehicles that were involved in the crime. Among these records lie groups of crimes that can be attributed to serial criminals who are responsible for multiple criminal offenses and usually exhibit patterns in their operations, by specializing in a particular crime category (i.e., rape, murder, robbery, etc.), and applying a specific method for implementing their crimes. Discovering serial criminal patterns in crime databases is, in general, a clustering activity in the area of data mining that is concerned with detecting trends in the data by classifying and grouping similar records. In this paper, we report on the different statistical and neural network approaches to the clustering problem in data mining in general, and as it applies to our crime domain in particular. We discuss our approach of using a cascaded network of Kohonen neural networks followed by heuristic processing of the networks outputs that best simulated the experts in the field. We address the issues in this project and the reasoning behind this approach, including: the choice of neural networks, in general, over statistical algorithms as the main tool, and the use of Kohonen networks in particular, the choice for the cascaded approach instead of the direct approach, and the choice of a heuristics subsystem as a back-end subsystem to the neural networks. We also report on the advantages of this approach over both the traditional approach of using a single neural network to accommodate all the attributes, and that of applying a single clustering algorithm on all the data attributes.