The maximum degree & diameter-bounded subgraph and its applications
- Authors: Dekker, Anthony , Pérez-Rosés, Hebert , Pineda-Villavicencio, Guillermo , Watters, Paul
- Date: 2012
- Type: Text , Journal article
- Relation: Journal of Mathematical Modelling and Algorithms Vol. 11, no. 3 (2012), p. 249-268
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- Description: We introduce the problem of finding the largest subgraph of a given weighted undirected graph (host graph), subject to constraints on the maximum degree and the diameter. We discuss some applications in security, network design and parallel processing, and in connection with the latter we derive some bounds for the order of the largest subgraph in host graphs of practical interest: the mesh and the hypercube. We also present a heuristic strategy to solve the problem, and we prove an approximation ratio for the algorithm. Finally, we provide some experimental results with a variety of host networks, which show that the algorithm performs better in practice than the prediction provided by our theoretical approximation ratio.
Challenges to automated allegory resolution in open source intelligence
- Authors: Watters, Paul
- Date: 2012
- Type: Text , Conference proceedings
- Full Text: false
- Description: The resolution of lexical ambiguity in machine translation systems often involves the automated, on-line selection of the correct sense of polysemous target words in the context of a clause, phrase or sentence. However, the performance of machine translation systems in emulating this aspect of human language processing has not been entirely successful, to the extent that resolution of entities and terms in natural language could be automated for open source intelligence analysis. Whilst some of these systems confine themselves to processing domain-specific knowledge (e.g., medical terminology), with some success, the popular general-purpose direct translation systems now freely available on the World Wide Web (WWW) are investigated for characteristic semantic processing errors in this study. A ubiquitous sentence ("The quick brown fox jumps over the lazy dog"), an equative metaphor, and a simile are translated into four romance and one Germanic language, with the translation then inverted back to English using the same translation system. It is found that in addition to expected differences in correctly mapping shades of meaning (e.g., "quick" is mapped to "fast"), some spatial meanings are incorrectly transformed, especially for verbs (e.g., "jumps over" becomes "branches over" or "jumps on"). The most serious error is the addition of extra semantic features to individual words, particularly features associated with nouns (e.g., the gender-neutral "fox" becomes the female "vixen"). The implications of these types of errors for the automatic translation of human language - with respect to semantic representation in open source intelligence - are discussed. © 2012 IEEE.
- Description: 2003011052
Internet subcultures and pathways to the use of child pornography
- Authors: Prichard, Jeremy , Watters, Paul , Spiranovic, Caroline
- Date: 2011
- Type: Text , Journal article
- Relation: Computer Law and Security Review Vol. 27, no. 6 (2011), p. 585-600
- Full Text: false
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- Description: With continual advances in Internet capability the child pornography market is experiencing a boom in demand and supply. Attempts to reduce the market challenge legislators, law enforcement agencies, practitioners and researchers alike - due in large part to the decentralised and global nature of the Internet. Much research has focused on frequent users of child pornography and whether such behaviour is interrelated with child sexual assaults. This article instead draws attention to onset, the first deliberate viewing of child pornography. It presents the results of a three-month study of a global Peer-to-Peer network, isoHunt. Analysis of the site's Top 300 search terms indicated that child pornography is consistently shared. Risk factors for onset are discussed, including the potential normalisation of child pornography among Internet subcultures. Strategies are discussed to encourage subcultures to inhibit child pornography use and to increase understanding of the harms associated with such material. Implications for legal systems, policy and research are explored. © 2011 Jeremy Prichard, Paul A. Watters & Caroline Spiranovic. Published by Elsevier Ltd. All rights reserved.
Cybersickness and anxiety during simulated motion : Implications for VRET
- Authors: Bruck, Susan , Watters, Paul
- Date: 2009
- Type: Text , Journal article
- Relation: Cyberpsychology & Behavior Vol. 12, no. 5 (2009), p. 593
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Accessible virtual reality therapy using portable media devices
- Authors: Bruck, Susan , Watters, Paul
- Date: 2010
- Type: Text , Journal article
- Relation: Annual Review of CyberTherapy and Telemedicine Vol. 8, no. 1 (2010), p. 69-72
- Full Text: false
- Description: Simulated immersive environments displayed on large screens are a valuable therapeutic asset in the treatment of a range of psychological disorders. Permanent environments are expensive to build and maintain, require specialized clinician training and technical support and often have limited accessibility for clients. Ideally, virtual reality exposure therapy (VRET) could be accessible to the broader community if we could use inexpensive hardware with specifically designed software. This study tested whether watching a handheld non-immersive media device causes nausea and other cybersickness responses. Using a repeated measure design we found that nausea, general discomfort, eyestrain, blurred vision and an increase in salivation significantly increased in response to handheld non-immersive media device exposure.
Selecting parameters for phase space reconstruction of the electrocorticogram (ECoG)
- Authors: Watters, Paul
- Date: 2005
- Type: Text , Journal article
- Relation: Journal of Integrative Neuroscience Vol. 4, no. 2 (2005), p. 169-182
- Full Text: false
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- Description: The selection of parameters for phase space reconstruction of empirically observed data has been a source of criticism when estimating the correlation dimension (D2) from observed data rather than from the solution of differential equations, when analyzing noisy and potentially non-stationary signals, such as the electroencephalogram (EEG). The largely arbitrary selection of the time-delay reconstruction (T) of temporal dynamics, and for the embedding (M) of these series, has been widely criticized. This study adopted an analytic and statistical framework within which the scaling behavior of D2 with respect to T and M, could be examined over five data lengths (N = 4096, 8192, 12288, 16384, and 20480) over an 8 × 8 grid of cat EEG. It was found that D2 was invariant over all data lengths only within a very narrow T range (T = 10–16) for M = 4. A statistically significant T by M interaction was found using multiple analysis of variance, with D2 being highly correlated over T as a function of M. Finally, an examination of phase-randomized surrogates indicated that statistically significant differences existed between EEG and phase-randomized surrogates over all data lengths, with time delays (T = 10–16), indicating that the D2 for EEG is phase-dependent when it is invariant with respect to data length. The implications of these findings are discussed with respect to current models of ECoG generation, and their implication with respect to the integration in the brain. [ABSTRACT FROM AUTHOR]
- Description: 2003007802
A preliminary profiling of internet money mules : An Australian perspective
- Authors: Aston, Manny , McCombie, Stephen , Reardon, Ben , Watters, Paul
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC '09, Brisbane, Queensland : 7th-9th July 2009 p. 482-487
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- Description: Along with the massive growth in Internet commerce over the last ten years there has been a corresponding boom in Internet related crime, or cybercrime. According to research recently released by the Australian Bureau of Statistics in 2006 57,000 Australians aged 15 years and over fell victim to phishing and related Internet scams. Of all the victims of cybercrime, only one group is potentially subject to criminal prosecution: `Internet money mules'-those who, either knowingly or unknowingly, launder money. This paper examines the demographic profile-specifically age, gender and postcode-related to 660 confirmed money mule incidents recorded during the calendar year 2007, for a major Australian financial institution. This data is compared to ABS statistics of Internet usage in 2006. There is clear evidence of a strong gender bias towards males, particularly in the older age group. This is directly relevant when considering education and training programs for both corporations and the community on the issues surrounding Internet money mule scams and in ultimately understanding the problem of Internet banking fraud.
- Description: 2003007858
Enabling access to British birth cohort studies: A secure web interface for the NSHD (SWIFT)
- Authors: Watters, Paul , Kuh, Diana , Latham, Susan , Garwood, Kevin , Shah, Imran
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at Healthcom 2009: 11th IEEE International Conference on e-Health Networking, Applications & Services
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The factor structure of cybersickness
- Authors: Bruck, Susan , Watters, Paul
- Date: 2011
- Type: Text , Journal article
- Relation: Displays Vol. 32, no. 4 (2011), p. 153-158
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- Description: Cybersickness embraces a range of clinical symptoms reported in response to simulated motion in a computer generated, virtual reality environment. The Simulator Sickness Questionnaire (SSQ) has been the standard tool for measuring observed responses; however, many of the observed SSQ variables are highly correlated, so it is not clear which ones are appropriate to use as a basis for building an explanatory model. In this study, responses to the SSQ were analyzed using principal components analysis, and four significant factors - general cybersickness, vision, arousal and fatigue - were identified. An initial interpretation of these factors is provided in the context of a broader cybersickness model, with a view to constructing a new questionnaire with fewer, more focused questions. © 2011 Elsevier B.V. All rights reserved.
Unsupervised authorship analysis of phishing webpages
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2012
- Type: Text , Conference proceedings
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- Description: Authorship analysis on phishing websites enables the investigation of phishing attacks, beyond basic analysis. In authorship analysis, salient features from documents are used to determine properties about the author, such as which of a set of candidate authors wrote a given document. In unsupervised authorship analysis, the aim is to group documents such that all documents by one author are grouped together. Applying this to cyber-attacks shows the size and scope of attacks from specific groups. This in turn allows investigators to focus their attention on specific attacking groups rather than trying to profile multiple independent attackers. In this paper, we analyse phishing websites using the current state of the art unsupervised authorship analysis method, called NUANCE. The results indicate that the application produces clusters which correlate strongly to authorship, evaluated using expert knowledge and external information as well as showing an improvement over a previous approach with known flaws. © 2012 IEEE.
- Description: 2003010678
Authorship attribution of IRC messages using inverse author frequency
- Authors: Layton, Robert , McCombie, Stephen , Watters, Paul
- Date: 2012
- Type: Text , Conference proceedings
- Full Text: false
- Description: Internet Relay Chat (IRC) is a useful and relativelysimple protocol for text based chat online, used in a variety ofareas online such as for discussion and technical support. IRC isalso used for cybercrime, with online rooms selling stolen creditcard details, botnet access and malware. The reasons for theuse of IRC in cybercrime include the widespread adoption andease of use, but also focus around the anonymity granted bythe protocol, allowing users to hide behind aliases that can bechanged regularly. In this research, we apply authorship analysistechniques to be able to attribute chat messages to known aliases.A preliminary experiment shows that this application is verydifficult, due to the short messages and repeated information.To improve the accuracy, we apply inverse-author-frequency(iaf) weighting, which gives higher weights to features used byfewer authors. This research is the first time that iaf has beenapplied to character n-gram models, previously being applied toword based models of authorship. We find that this improvesthe accuracy significantly for the RLP method and provides aplatform for successful applications of authorship analysis in thefuture. Overall, the method achieves accuracies of over 55% ina very difficult application domain. © 2012 IEEE.
- Description: 2003011051
Local n-grams for author identification: Notebook for PAN at CLEF 2013 C3 - CEUR Workshop Proceedings
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Conference proceedings
- Full Text:
- Description: Our approach to the author identification task uses existing authorship attribution methods using local n-grams (LNG) and performs a weighted ensemble. This approach came in third for this year's competition, using a relatively simple scheme of weights by training set accuracy. LNG models create profiles, consisting of a list of character n-grams that best represent a particular author's writing. The use of a weighted ensemble improved upon the accuracy of the method without reducing the speed of the algorithm; the submitted solution was not only near the top of the leaderboard in terms of accuracy, but it was also one of the faster algorithms submitted.
Zero-day malware detection based on supervised learning algorithms of API call signatures
- Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul , Alazab, Moutaz
- Date: 2011
- Type: Text , Conference proceedings
- Full Text:
- Description: Zero-day or unknown malware are created using code obfuscation techniques that can modify the parent code to produce offspring copies which have the same functionality but with different signatures. Current techniques reported in literature lack the capability of detecting zero-day malware with the required accuracy and efficiency. In this paper, we have proposed and evaluated a novel method of employing several data mining techniques to detect and classify zero-day malware with high levels of accuracy and efficiency based on the frequency of Windows API calls. This paper describes the methodology employed for the collection of large data sets to train the classifiers, and analyses the performance results of the various data mining algorithms adopted for the study using a fully automated tool developed in this research to conduct the various experimental investigations and evaluation. Through the performance results of these algorithms from our experimental analysis, we are able to evaluate and discuss the advantages of one data mining algorithm over the other for accurately detecting zero-day malware successfully. The data mining framework employed in this research learns through analysing the behavior of existing malicious and benign codes in large datasets. We have employed robust classifiers, namely Naïve Bayes (NB) Algorithm, k-Nearest Neighbor (kNN) Algorithm, Sequential Minimal Optimization (SMO) Algorithm with 4 differents kernels (SMO - Normalized PolyKernel, SMO - PolyKernel, SMO - Puk, and SMO- Radial Basis Function (RBF)), Backpropagation Neural Networks Algorithm, and J48 decision tree and have evaluated their performance. Overall, the automated data mining system implemented for this study has achieved high true positive (TP) rate of more than 98.5%, and low false positive (FP) rate of less than 0.025, which has not been achieved in literature so far. This is much higher than the required commercial acceptance level indicating that our novel technique is a major leap forward in detecting zero-day malware. This paper also offers future directions for researchers in exploring different aspects of obfuscations that are affecting the IT world today. © 2011, Australian Computer Society, Inc.
- Description: 2003009506
Illicit image detection using erotic pose estimation based on kinematic constraints
- Authors: Islam, Mofakharul , Watters, Paul , Yearwood, John , Hussain, Mazher , Swarna, Lubaba
- Date: 2013
- Type: Text , Book chapter
- Relation: Innovations and Advances in Computer, Information, Systems Sciences, and Engineering p. 481-495
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- Description: With the advent of the Internet along with sophisticated digital image processing technology, the Internet quickly became the principal medium for the distribution of pornographic content favouring pornography to become a drug of the millennium. With the advent of GPRS mobile telephone networks, and with the large scale arrival of the 3G networks, along with the cheap availability of latest mobile sets and a variety of forms of wireless connections, the internet has already gone to mobile, drives us toward a new degree of complexity. The detection of pornography remains an important and significant research problem, since there is great potential to minimize harm to the community. In this paper, we propose a novel approach to investigate and implement a pornography detection technique towards a framework for automated detection of pornography based on most commonly found erotic poses. Compared to the results published in recent works, our proposed approach yields the highest accuracy in recognition. © 2013 Springer Science+Business Media.
Information security governance: The art of detecting hidden malware
- Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul
- Date: 2013
- Type: Text , Book chapter
- Relation: IT Security governance innovations: Theory and research p. 293-315
- Full Text: false
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- Description: Detecting malicious software or malware is one of the major concerns in information security governance as malware authors pose a major challenge to digital forensics by using a variety of highly sophisticated stealth techniques to hide malicious code in computing systems, including smartphones. The current detection techniques are futile, as forensic analysis of infected devices is unable to identify all the hidden malware, thereby resulting in zero day attacks. This chapter takes a key step forward to address this issue and lays foundation for deeper investigations in digital forensics. The goal of this chapter is, firstly, to unearth the recent obfuscation strategies employed to hide malware. Secondly, this chapter proposes innovative techniques that are implemented as a fully-automated tool, and experimentally tested to exhaustively detect hidden malware that leverage on system vulnerabilities. Based on these research investigations, the chapter also arrives at an information security governance plan that would aid in addressing the current and future cybercrime situations.
Patterns of ownership of child model sites : Profiling the profiteers and consumers of child exploitation material
- Authors: Watters, Paul , Lueg, Christopher , Spiranovic, Caroline , Prichard, Jeremy
- Date: 2013
- Type: Text , Journal article
- Relation: First Monday Vol. 18, no. 2 (2013), p.
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- Description: Recent research has indicated that cybercrime thrives when a corrupt social, economic, and political environment emerges such that law enforcement impact is minimised and key elements of crime prevention are absent. In this paper, using a snowball methodology we analyse patterns of ownership of "child model" sites which generate profits from advertising and/or subscriptions. While the material may not be traditional "pornography" in content, it is arguably exploitative. An open question is how the material compares to "beauty pageant" and other highly stylised mainstream photography that depicts children in adult situations, and whether access to all such material should be restricted.
- Description: 2003010829
Child face detection using age specific luminance invariant geometric descriptor
- Authors: Islam, Mofakharul , Watters, Paul , Yearwood, John
- Date: 2011
- Type: Text , Conference proceedings
- Full Text: false
- Description: While considerable research have been conducted on age-wise age estimation using skin detection most often with other visual cues, relatively little research has looked closely at the subject. In this paper, we present a new framework for interpreting facial image patterns that can be employed in categorical age estimation. The aim is to propose a novel approach to investigate and implement a child face detection technique that is able to estimate age categorically adult or child based on a new hybrid feature descriptor. The novel hybrid feature descriptor LIGD (the luminance invariant geometric descriptor) is composed of some low and high level features, which are found to be effective in characterizing the local appearance. In local appearance estimation, chromaticity, texture, and positional information of few facial visual cues can be employed simultaneously. Compared to the results published in a recent work, our proposed approach yields the highest precision and recall, and overall accuracy in recognition. © 2011 IEEE.
A new stochastic model based approach for object identification and segmentation in textured color image
- Authors: Islam, Mofakharul , Watters, Paul
- Date: 2010
- Type: Text , Book chapter
- Relation: Technological Developments in Networking, Education and Automation p. 309-314
- Full Text: false
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- Description: We investigate and propose a novel stochastic model based approach to implement a robust unsupervised color image content understanding technique that segments a color textured image into its constituent parts automatically and meaningfully. The aim of this work is to detection and identification of different objects in a color image using image segmentation. Image segments or objects are produced using precise color information, texture information and neighborhood relationships among neighboring image pixels. As a whole, in this particular work, the problem we want to investigate is to implement a robust Maximum a posteriori (MAP) based unsupervised color textured image segmentation approach using Cluster Ensembles, MRF model and Daubechies wavelet transform for identification and segmentation of image contents or objects. In addition,Cluster Ensemble has been utilizedfor introducing a robust technique for finding the number of components in an image automatically. The experimental results reveal that the proposed model is able to find the accurate number of objects or components in a color image and can produce more accurate and faithful segmentation of different meaningful objects from relatively complex background. Finally, we have compared our results with another similar existing segmentation approach.
Authorship analysis of aliases: Does topic influence accuracy?
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. Online first, no. (2013), p.
- Full Text:
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- Description: Aliases play an important role in online environments by facilitating anonymity, but also can be used to hide the identity of cybercriminals. Previous studies have investigated this alias matching problem in an attempt to identify whether two aliases are shared by an author, which can assist with identifying users. Those studies create their training data by randomly splitting the documents associated with an alias into two sub-aliases. Models have been built that can regularly achieve over 90% accuracy for recovering the linkage between these ‘random sub-aliases’. In this paper, random sub-alias generation is shown to enable these high accuracies, and thus does not adequately model the real-world problem. In contrast, creating sub-aliases using topic-based splitting drastically reduces the accuracy of all authorship methods tested. We then present a methodology that can be performed on non-topic controlled datasets, to produce topic-based sub-aliases that are more difficult to match. Finally, we present an experimental comparison between many authorship methods to see which methods better match aliases under these conditions, finding that local n-gram methods perform better than others.
A methodology for analyzing the credential marketplace
- Authors: Watters, Paul , McCombie, Stephen
- Date: 2011
- Type: Text , Journal article
- Relation: Journal of Money Laundering Control Vol. 14, no. 1 (2011), p. 32-43
- Full Text: false
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- Description: Purpose – Cybercrime has rapidly developed in recent years thanks in part to online markets for tools and credentials. Credential trading operates along the lines of a wholesale distribution model, where compromised credentials are bundled together for sale to end-users. Thus, the criminals who specialize in obtaining credentials (through phishing, dumpster diving, etc.) are typically not the same as the end-users. This research aims to propose an initial methodology for further understanding of how credentials are traded in online marketplaces (such as internet relay chat (IRC) channels), such as typical amounts charged per credential, and with a view to preliminary profiling, especially based on language identification. Design/methodology/approach – This research proposes an initial methodology for further understanding of how credentials are traded in online marketplaces (such as IRC channels), such as typical amounts charged per credential, and with a view to preliminary profiling, especially based on language identification. Initial results from a small sample of credential chatroom data is analysed using the technique. Findings – The paper identified five key term categories from the subset of the 100 most frequent terms (bank/payment provider names, supported trading actions, non-cash commodities for trading, targeted countries and times), and demonstrated how actors and processes could be extracted to identify common business processes in credential trading. In turn, these elements could potentially be used to track the specific trading activities of individuals or groups. The hope in the long-term is that we may be able to cross-reference named entities in the credential trading world (or a pattern of activity) and cross-reference this with known credential theft attacks, such as phishing. Originality/value – This is the first study to propose a methodology to systematically analyse credential trading on the internet. Acknowledgements: This work was supported in part by the Australian Federal Police, Westpac Banking Corporation, IBM, the State Government of Victoria and the University of Ballarat.
- Description: 2003011113