2013 Fourth Cybercrime and Trustworthy Computing Workshop最新文献

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.15

Simi Bajaj, J. Pieprzyk

{"title":"Can We CAN the Email Spam","authors":"Simi Bajaj, J. Pieprzyk","doi":"10.1109/CTC.2013.15","DOIUrl":"https://doi.org/10.1109/CTC.2013.15","url":null,"abstract":"The purpose of email spam is to advertise to sell, phishing attacks, DDOS attacks and many more. Many solutions of various kinds such as blacklisting, whitelisting, grey-listing, content filtering have been proposed at the sender and receiver levels. There has been some level of success but the email spam still hits the inbox and more so the problem is false positives and false negatives. The current filtering solutions used are mostly a combination of few of the available techniques, the most common being a combination of listing and content filtering techniques. Apart from any attacks, email spam causes a great loss in resources and productivity of the user. Apart from this, this problem of false negatives exists as there is non-existence of filters to address user's preferences and behaviors, timing of the day and year. The filters at the mail servers are trained with spam and ham training data that is generic in nature. Hence, there is need to address this problem. This paper aims to address all of the above i.e. an email that hits a particular users inbox by escaping the mail server spam filtering solutions. To do this, this paper describes the problem of spam, followed by the filtering mechanisms, techniques, learning email filter model and then proposes a model to fine tune the filter to increase the efficiency.","PeriodicalId":231676,"journal":{"name":"2013 Fourth Cybercrime and Trustworthy Computing Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129076743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Malicious Spam Emails Developments and Authorship Attribution 恶意垃圾邮件的发展和作者归属

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.16

M. Alazab, R. Layton, R. Broadhurst, Brigitte Bouhours

{"title":"Malicious Spam Emails Developments and Authorship Attribution","authors":"M. Alazab, R. Layton, R. Broadhurst, Brigitte Bouhours","doi":"10.1109/CTC.2013.16","DOIUrl":"https://doi.org/10.1109/CTC.2013.16","url":null,"abstract":"The Internet is a decentralized structure that offers speedy communication, has a global reach and provides anonymity, a characteristic invaluable for committing illegal activities. In parallel with the spread of the Internet, cybercrime has rapidly evolved from a relatively low volume crime to a common high volume crime. A typical example of such a crime is the spreading of spam emails, where the content of the email tries to entice the recipient to click a URL linking to a malicious Web site or downloading a malicious attachment. Analysts attempting to provide intelligence on spam activities quickly find that the volume of spam circulating daily is overwhelming; therefore, any intelligence gathered is representative of only a small sample, not of the global picture. While past studies have looked at automating some of these analyses using topic-based models, i.e. separating email clusters into groups with similar topics, our preliminary research investigates the usefulness of applying authorship-based models for this purpose. In the first phase, we clustered a set of spam emails using an authorship-based clustering algorithm. In the second phase, we analysed those clusters using a set of linguistic, structural and syntactic features. These analyses reveal that emails within each cluster were likely written by the same author, but that it is unlikely we have managed to group together all spam produced by each group. This problem of high purity with low recall, has been faced in past authorship research. While it is also a limitation of our research, the clusters themselves are still useful for the purposes of automating analysis, because they reduce the work needing to be performed. Our second phase revealed useful information on the group that can be utilized in future research for further analysis of such groups, for example, identifying further linkages behind spam campaigns.","PeriodicalId":231676,"journal":{"name":"2013 Fourth Cybercrime and Trustworthy Computing Workshop","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133130996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 51

Skype Traffic Classification Using Cost Sensitive Algorithms Skype流量分类使用成本敏感算法

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.11

A. Azab, R. Layton, M. Alazab, P. Watters

{"title":"Skype Traffic Classification Using Cost Sensitive Algorithms","authors":"A. Azab, R. Layton, M. Alazab, P. Watters","doi":"10.1109/CTC.2013.11","DOIUrl":"https://doi.org/10.1109/CTC.2013.11","url":null,"abstract":"Voice over IP (VoIP) technologies such as Skype are becoming increasingly popular and widely used in different organisations, and therefore identifying the usage of this service at the network level becomes very important. Reasons for this include applying Quality of Service (QoS), network planning, prohibiting its use in some networks and lawful interception of communications. Researchers have addressed VoIP traffic classification from different viewpoints, such as classifier accuracy, building time, classification time and online classification. This previous research tested their models using the same version of a VoIP product they used for training the model, giving generalizability only to that version of the product. This means that as new VoIP versions are released, these classifiers become obsolete. In this paper, we address if this approach is applicable to detecting new, untrained, versions of Skype. We suggest that using cost-sensitive classifiers can help to improve the accuracy of detecting untrained versions, by testing compared to other algorithms. Our experiment demonstrates promising preliminary results to detect Skype version 4, by building a cost sensitive classifier on Skype version 3, achieving an F-measure score of 0.57. This is a drastic improvement from not using cost sensitivity, which scores an F-measure of 0. This approach may be enhanced to improve the detection results and extended to improve detection for other applications that change protocols from version to version.","PeriodicalId":231676,"journal":{"name":"2013 Fourth Cybercrime and Trustworthy Computing Workshop","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129022935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

ICANN or ICANT: Is WHOIS an Enabler of Cybercrime? ICANN或ICANT: WHOIS是网络犯罪的推动者吗?

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.13

P. Watters, Aaron Herps, R. Layton, S. McCombie

引用次数: 12

Strategies for Covert Web Search 隐蔽网络搜索策略

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.10

G. Weir, David Igbako

引用次数: 1

Identifying Faked Hotel Reviews Using Authorship Analysis 使用作者分析识别虚假酒店评论

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.8

R. Layton, P. Watters, O. Ureche

引用次数: 5

Statistical Sampling Approach to Investigate Child Pornography Cases 调查儿童色情案件的统计抽样方法

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.14

N. Sarantinos, Ameer Al-Nemrat, U. Naeem

引用次数: 0

TLSH -- A Locality Sensitive Hash TLSH——位置敏感散列

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.9

Jonathan J. Oliver, C. Cheng, Yanggui Chen

引用次数: 142

Measuring Surveillance in Online Advertising: A Big Data Approach 测量在线广告监控:大数据方法

2013 Fourth Cybercrime and Trustworthy Computing Workshop Pub Date : 2013-11-21 DOI: 10.1109/CTC.2013.12

Aaron Herps, P. Watters, Guillermo Pineda-Villavicencio

引用次数: 2