Recentred local profiles for authorship attribution
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2012
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 18, no. 3 (2012), p. 293-312
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- Description: Authorship attribution methods aim to determine the author of a document, by using information gathered from a set of documents with known authors. One method of performing this task is to create profiles containing distinctive features known to be used by each author. In this paper, a new method of creating an author or document profile is presented that detects features considered distinctive, compared to normal language usage. This recentreing approach creates more accurate profiles than previous methods, as demonstrated empirically using a known corpus of authorship problems. This method, named recentred local profiles, determines authorship accurately using a simple 'best matching author' approach to classification, compared to other methods in the literature. The proposed method is shown to be more stable than related methods as parameter values change. Using a weighted voting scheme, recentred local profiles is shown to outperform other methods in authorship attribution, with an overall accuracy of 69.9% on the ad-hoc authorship attribution competition corpus, representing a significant improvement over related methods. Copyright © Cambridge University Press 2011.
- Description: 2003010688
RBACS : Rootkit behavioral analysis and classification system
- Authors: Lobo, Desmond , Watters, Paul , Wu, Xinwen
- Date: 2010
- Type: Text , Conference paper
- Relation: Paper presented at 3rd International Conference on Knowledge Discovery and Data Mining, WKDD 2010, Phuket : 9th-10th January 2010 p. 75-80
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- Description: In this paper, we focus on rootkits, a special type of malicious software (malware) that operates in an obfuscated and stealthy mode to evade detection. Categorizing these rootkits will help in detecting future attacks against the business community. We first developed a theoretical framework for classifying rootkits. Based on our theoretical framework, we then proposed a new rootkit classification system and tested our system on a sample of rootkits that use inline function hooking. Our experimental results showed that our system could successfully categorize the sample using unsupervised clustering. © 2010 IEEE.
The seven scam types: Mapping the terrain of cybercrime
- Authors: Stabek, Amber , Watters, Paul , Layton, Robert
- Date: 2010
- Type: Text , Conference proceedings
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- Description: Threat of cybercrime is a growing danger to the economy. Industries and businesses are targeted by cyber-criminals along with members of the general public. Since cybercrime is often a symptom of more complex criminological regimes such as laundering, trafficking and terrorism, the true damage caused to society is unknown. Dissimilarities in reporting procedures and non-uniform cybercrime classifications lead international reporting bodies to produce incompatible results which cause difficulties in making valid comparisons. A cybercrime classification framework has been identified as necessary for the development of an inter-jurisdictional, transnational, and global approach to identify, intercept, and prosecute cyber-criminals. Outlined in this paper is a cybercrime classification framework which has been applied to the incidence of scams. Content analysis was performed on over 250 scam descriptions stemming from in excess of 35 scamming categories and over 80 static features derived. Using hierarchical cluster and discriminant function analysis, the sample was reduced from over 35 ambiguous categories into 7 scam types and the top four scamming functions - identified as scamming business processes, revealed. The results of this research bear significant ramifications to the current state of scam and cybercrime classification, research and analysis, as well as offer significant insight into the business processes and applications adopted by scammers and cyber-criminals. © 2010 IEEE.
The case for a consistent cyberscam classification framework (CCCF)
- Authors: Stabek, Amber , Brown, Simon , Watters, Paul
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at UIC-ATC 2009 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences, Brisbane : 7th-9th July 2009 p. 525-530
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- Description: Cyberscam classification schemes developed by international statistical reporting bodies, including the Bureau of Statistics (Australia), the Internet Crime Complaint Center (US), and the Environics Research Group (Canada), are diverse and largely incompatible. This makes comparisons of cyberscam incidence across jurisdictions very difficult. This paper argues that the critical first step towards the development of an inter-jurisdictional and global approach to identify and intercept cyberscams - and prosecute scammers - is a uniform classification system. © 2009 IEEE.