中文Web信息作者同一认定技术研究
摘要
随着互联网的日益普及,网上出现了各种各样的Web信息,比如:网上论坛、博客、电子邮件等,这些信息成为人们生活和工作中重要的信息来源。然而,这些Web信息给人们带来便利的同时,也产生许多问题,比如:某些人通过网上论坛、博客及电子邮件等手段发布反动、诈骗、色情、威胁、赌博等违法信息,网络为违法犯罪分子提供了新的犯罪空间和手段,造成极其恶劣的影响,严重影响社会的稳定以及国家和政府的安全。
目前,抵制这种现象的主要方法就是安装过滤软件,把包含敏感词汇的信息过滤掉,但是,这种被动防御的方法不能杜绝非法Web信息的现象,因为,犯罪分子会使用一些替代词汇,突破过滤软件的防御。通过立法手段,追究犯罪分子的刑事责任,可以有力地打击这种犯罪行为,国家已经出台多项相关法律,有法可依,但是,由于缺乏有效的证据,而使类似案件无法立案侦查。如果能同一认定Web信息的作者,找出犯罪分子的犯罪证据,为计算机取证提供证据,对司法办案和促进社会的安全与稳定、净化网络环境都具有重要的应用价值和现实意义。
本文利用写作风格学的原理和技术,研究Web信息作者的写作风格,提取能代表作者写作特点的写作特征,利用机器学习算法自动辨别出作者的真实身份。本文的研究集中在以下几个方面:(1)对Web信息作者身份识别相关研究领域的国内外现状进行了全面、详细地调研和分析,提出Web信息作者身份识别的系统模型和系统框架;(2)针对Web页面和E-mail信息,提出本文对Web信息内容的提取方法;(3)提取能表达Web信息作者的写作特点的三方面特征,包括语言特征、结构特征和格式特征;(4)对支持向量机算法进行了改进,提出基于相似度的渐进直推支持向量机算法(PSTSVM),使其适合小样本分类识别;(5)研究和开发了中文Web信息作者识别实验系统;(6)为了调查犯罪分子的社会关系,对社会关系网络进行了研究,提出了基于作者身份真实性判断的社会关系网络建立方法。
为了验证本文提出的研究方法的有效性,搜集大量数据,设置多个实验,对本研究各种影响因素进行了验证。实验结果表明,本研究提出的三种特征提取方法是有效的,而且各种特征的特征组合比用单个特征的效果更好,文学作品、Blog、电子邮件数据集的分类识别正确率超过86%,实验结果表明本研究所提出的方法是有效的,此方法用于计算机取证是切实可行的。
With the increasing popularization of Internet, Various Web information such as BBS, Blog, E-mail etc arises, which become important information source in the daily life and work. However, this web information provide convenient to people, at the same time bring a lot of problems. Some illegal web information, such as antisocial information, fraud information, pornographic information, terroristic threatening information, gambling information appears by means of BBS, Blog or E-mail. The Internet provides criminals new criminous space and means. These phenomena cause wicked effect, which affect social stabilization and national security seriously.
Now, the main methods to prevent these phenomena are installing filtering software to filter the information containing sensitive words. But, the passive defensive methods can’t put an end of these phenomena of illegal web information, because criminal can make use of some substitute words to break through the defense of filtering software. Purnishing the criminals by means of law can strike these crimes effectively. Our state has come on interrelated law. There are laws to resort to. But due to lacking effective evidence, the law case can’t be put into court. If web information’s authorship is identified, criminal’s evidence can be found, evidence for computer forensic can be collected, which have important application value and practical significance to law enforcement, social safety and stabilization, Internet environments’purifying.
Making use of the theory and techniques of stylometry, the web information author’s writing style were investigated in this paper. Some writing features that could represent author’s writing style were extracted. The machine-learning algorithm was used to identify the authorship of web information. The main work was listed in the following. (1) The related research were investigated and analyzed comprehensive and detailedly. The model and framework of web information authorship identification were provided. (2) The methods for e-mail and web page’s content extraction were brought forward. (3) The linguistic features, structural features and format features that could express author’s writing style were extracted. (4) The support vector machine algorithm was improved. The PSTSVM algorithm that suited small sample’s classification was brought forward. (5) The Chinese web information authorship identification system was developed. (6) To investigate the criminal’s social relations, the social network was researched. The social network building methods based on authorship’s authenticity judgement were provided.
To test validity of the method in this paper, large datasets were collected. Several experiments were done. Some influencing fators were tested in the experiments. Experimental results proved that the three feature extraction methods were effective. The three features combination had a better result than single feature. The classification accuracy for dataset of literature, blog and e-mail exceeded 86 percent. The experimental results proved that the method of the research was effective and it was feasible to apply for computer forensic.
目前,抵制这种现象的主要方法就是安装过滤软件,把包含敏感词汇的信息过滤掉,但是,这种被动防御的方法不能杜绝非法Web信息的现象,因为,犯罪分子会使用一些替代词汇,突破过滤软件的防御。通过立法手段,追究犯罪分子的刑事责任,可以有力地打击这种犯罪行为,国家已经出台多项相关法律,有法可依,但是,由于缺乏有效的证据,而使类似案件无法立案侦查。如果能同一认定Web信息的作者,找出犯罪分子的犯罪证据,为计算机取证提供证据,对司法办案和促进社会的安全与稳定、净化网络环境都具有重要的应用价值和现实意义。
本文利用写作风格学的原理和技术,研究Web信息作者的写作风格,提取能代表作者写作特点的写作特征,利用机器学习算法自动辨别出作者的真实身份。本文的研究集中在以下几个方面:(1)对Web信息作者身份识别相关研究领域的国内外现状进行了全面、详细地调研和分析,提出Web信息作者身份识别的系统模型和系统框架;(2)针对Web页面和E-mail信息,提出本文对Web信息内容的提取方法;(3)提取能表达Web信息作者的写作特点的三方面特征,包括语言特征、结构特征和格式特征;(4)对支持向量机算法进行了改进,提出基于相似度的渐进直推支持向量机算法(PSTSVM),使其适合小样本分类识别;(5)研究和开发了中文Web信息作者识别实验系统;(6)为了调查犯罪分子的社会关系,对社会关系网络进行了研究,提出了基于作者身份真实性判断的社会关系网络建立方法。
为了验证本文提出的研究方法的有效性,搜集大量数据,设置多个实验,对本研究各种影响因素进行了验证。实验结果表明,本研究提出的三种特征提取方法是有效的,而且各种特征的特征组合比用单个特征的效果更好,文学作品、Blog、电子邮件数据集的分类识别正确率超过86%,实验结果表明本研究所提出的方法是有效的,此方法用于计算机取证是切实可行的。
With the increasing popularization of Internet, Various Web information such as BBS, Blog, E-mail etc arises, which become important information source in the daily life and work. However, this web information provide convenient to people, at the same time bring a lot of problems. Some illegal web information, such as antisocial information, fraud information, pornographic information, terroristic threatening information, gambling information appears by means of BBS, Blog or E-mail. The Internet provides criminals new criminous space and means. These phenomena cause wicked effect, which affect social stabilization and national security seriously.
Now, the main methods to prevent these phenomena are installing filtering software to filter the information containing sensitive words. But, the passive defensive methods can’t put an end of these phenomena of illegal web information, because criminal can make use of some substitute words to break through the defense of filtering software. Purnishing the criminals by means of law can strike these crimes effectively. Our state has come on interrelated law. There are laws to resort to. But due to lacking effective evidence, the law case can’t be put into court. If web information’s authorship is identified, criminal’s evidence can be found, evidence for computer forensic can be collected, which have important application value and practical significance to law enforcement, social safety and stabilization, Internet environments’purifying.
Making use of the theory and techniques of stylometry, the web information author’s writing style were investigated in this paper. Some writing features that could represent author’s writing style were extracted. The machine-learning algorithm was used to identify the authorship of web information. The main work was listed in the following. (1) The related research were investigated and analyzed comprehensive and detailedly. The model and framework of web information authorship identification were provided. (2) The methods for e-mail and web page’s content extraction were brought forward. (3) The linguistic features, structural features and format features that could express author’s writing style were extracted. (4) The support vector machine algorithm was improved. The PSTSVM algorithm that suited small sample’s classification was brought forward. (5) The Chinese web information authorship identification system was developed. (6) To investigate the criminal’s social relations, the social network was researched. The social network building methods based on authorship’s authenticity judgement were provided.
To test validity of the method in this paper, large datasets were collected. Several experiments were done. Some influencing fators were tested in the experiments. Experimental results proved that the three feature extraction methods were effective. The three features combination had a better result than single feature. The classification accuracy for dataset of literature, blog and e-mail exceeded 86 percent. The experimental results proved that the method of the research was effective and it was feasible to apply for computer forensic.
引文
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