本文選題：垃圾郵件 + 特征選擇�。� 參考：《廈門大學(xué)》2014年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)的飛速發(fā)展,電子郵件已經(jīng)成為一種非常流行的溝通工具,被廣泛的應(yīng)用于個人通信和企業(yè)環(huán)境中。與之而來的垃圾郵件卻給網(wǎng)絡(luò)用戶帶來了非常大的安全隱患,這些安全隱患包括浪費使用者時間、存儲空間以及寶貴的網(wǎng)絡(luò)帶寬等。如今,有越來越多的人專注于制造垃圾郵件,只要企業(yè)和互聯(lián)網(wǎng)有郵件接口就不能豁免其影響,就連主流的社交網(wǎng)站,像是騰訊、新浪微博和谷歌這樣的知名企業(yè)都不能例外。由于垃圾郵件爆炸式的增長,也產(chǎn)生了眾多與之對應(yīng)的反垃圾郵件技術(shù)。這種‘掰手腕’式的技術(shù)對抗也使得反垃圾郵件的手段和技術(shù)逐年成熟。盡管在新的反垃圾郵件技術(shù)部署之后,垃圾郵件可以得到暫時的控制,但是制造者們也在不斷反過濾,產(chǎn)生更新的垃圾郵件技術(shù)。針對以上情況,本文開展了以下方面的研究工作： ●分析和研究當(dāng)下反垃圾郵件系統(tǒng)的設(shè)計原理、實現(xiàn)方法以及現(xiàn)狀,對典型的反垃圾郵件技術(shù)的特點進行歸納和總結(jié),了解和把握垃圾郵件識別技術(shù)新的發(fā)展趨勢； ●通過對大量垃圾郵件和正常郵件進行分析,發(fā)現(xiàn)二者的郵件發(fā)送者在意圖表現(xiàn)上有所不同,從而選取用于分類的意圖特征,研究如何高效而準(zhǔn)確地提取這些意圖特征,并在測試數(shù)據(jù)集中驗證其效率和準(zhǔn)確性； ●在大量郵件的基礎(chǔ)上,找出圖像形式的垃圾郵件,發(fā)現(xiàn)其特點,在垃圾郵件中分析圖像郵件與文本郵件的區(qū)別,分析基于機器學(xué)習(xí)的反圖像垃圾郵件技術(shù)存在的不足,提出了基于統(tǒng)計概率、規(guī)則和投票機制的圖像過濾選擇方法。 ●構(gòu)造一個高效的哈希生成算法,對垃圾郵件正文信息和附件進行采樣計算哈希值,生成指紋文件,再與在線指紋庫進行對比從而識別一封郵件是否為垃圾郵件。
[Abstract]:With the rapid development of the Internet, email has become a very popular communication tool, widely used in personal communications and enterprise environment. However, spam brings great security risks to network users, including wasting user time, storage space and valuable network bandwidth. Today, more and more people are focused on spamming, as long as businesses and the Internet have email interfaces, even mainstream social networking sites, such as Tencent, Sina Weibo and Google, are no exception. Because of the explosive growth of spam, there are many anti-spam technologies. This' wrist-breaking 'type of technical confrontation also makes anti-spam means and technology mature year by year. Although spam can be temporarily controlled after the deployment of the new anti-spam technology, manufacturers are also constantly de-filtering to produce newer spam technologies. In view of the above situation, this paper has carried out the following research work: This paper analyzes and studies the design principle, implementation method and present situation of the current anti-spam system, summarizes and summarizes the characteristics of typical anti-spam technology, and understands and grasps the new development trend of spam identification technology. Through the analysis of a large number of spam and normal mail, it is found that the two mail senders have different intention performance, and then select the intention features used for classification, and study how to extract these intention features efficiently and accurately. And verify its efficiency and accuracy in the test data set; On the basis of a large number of mail, we find out the image form of spam, find its characteristics, analyze the difference between image mail and text mail in spam, and analyze the shortcomings of anti-image spam technology based on machine learning. An image filtering selection method based on statistical probability, rule and voting mechanism is proposed. An efficient hash generation algorithm is constructed to sample and calculate the hash value of spam text information and attachments, generate fingerprint files, and then compare with the online fingerprint database to identify whether an email is spam or not.
【學(xué)位授予單位】：廈門大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.098

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