Towards smart online dispute resolution for medical disputes
- Authors: Bellucci, Emilia , Stranieri, Andrew , Venkatraman, Sitalakshmi
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: Proceedings of the Australasian Computer Science Week Multiconference (ACSW 2020); Melbourne, Australia; 3rd-7th February 2020. p. 1-5
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- Description: With the advancements in technologies, digitization of health records in the healthcare industry is undertaking a rapid revolution. This is further fueled with the entrance of Internet of Things (IoT), where mobile health devices have resulted in an explosion of health data and increased accessibility via wireless communications and sensor networks. With the introduction of an Electronic Health Record (EHR) system as an important venture for the general health and wellbeing of a country's citizens, privacy issues and medical disputes are expected to rise. In addition to critical health information being documented and shared electronically, integrating data from diverse smart medical IoT devices are leading towards increasingly more complex disputes that require immense time and effort to resolve. Online dispute resolution (ODR) programs have been successfully applied to cost-effectively help disputants resolve commercial, insurance and other legal disputes, but as yet have not been applied to healthcare. This paper takes a modest step in this direction, firstly to identify the drivers of medical disputes that include patient empowerment and technology advancements and trends. Secondly, we explore dispute resolution models and identify the status and limitations of current ODR systems.
- Description: This work was funded by the University of Ballarat Deakin University Collaborative Fund. 160134
Towards understanding corporate dilemma about social responsibility
- Authors: Nayak, Ravi , Venkatraman, Sitalakshmi , Moyeen, Abdul
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at International Conference on Business Ethics and Corporate Responsibility, ICBECSR' 09, Karnataka, India : 3rd-5th December 2009 p. 387-396
- Full Text: false
- Description: This empirical research examines the relationship between corporate social performance outcome (CSPO) and corporate financial performance outcome (CFPO) in 85 Australian corporations as perceived by their managers. The correlation analysis of the data shows a positive, but low magnitude relationship between CSPO and CFPO. Based on our finding, we argue that the notion of enlightened self-interest is defunct and recommend stringent government policies and increased community pressure for making corporations more socially responsible.
- Description: 2003007367
Towards automatic image segmentation using optimised region growing technique
- Authors: Nicholson, Ann , Li, Xiaodong , Alazab, Mamoun , Islam, Mofakharul , Venkatraman, Sitalakshmi
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 22nd Australasian Joint Conference, AI 2009: Advances in Artificial Intelligence, Melbourne, Victoria : 1st-4th December 2009 Vol. 5866, p. 131-139
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- Description: Image analysis is being adopted extensively in many applications such as digital forensics, medical treatment, industrial inspection, etc. primarily for diagnostic purposes. Hence, there is a growing interest among researches in developing new segmentation techniques to aid the diagnosis process. Manual segmentation of images is labour intensive, extremely time consuming and prone to human errors and hence an automated real-time technique is warranted in such applications. There is no universally applicable automated segmentation technique that will work for all images as the image segmentation is quite complex and unique depending upon the domain application. Hence, to fill the gap, this paper presents an efficient segmentation algorithm that can segment a digital image of interest into a more meaningful arrangement of regions and objects. Our algorithm combines region growing approach with optimised elimination of false boundaries to arrive at more meaningful segments automatically. We demonstrate this using X-ray teeth images that were taken for real-life dental diagnosis.
- Description: 2003007514
A performance framework for corporate sustainability
- Authors: Venkatraman, Sitalakshmi , Nayak, Ravi
- Date: 2010
- Type: Text , Journal article
- Relation: International Journal of Business Innovation and Research Vol. 4, no. 5 (2010), p. 475-490
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- Description: Recent studies conducted worldwide on corporate sustainability indicate gaps in sustainability practice. Many organisations deal with their economic, social and environmental issues individually and have not explored their inter-connections. They are now required to rethink their business strategies for improving their contribution to both shareholders and society as a whole. This paper is a step further to address these gaps in sustainability practice. Through an empirical study conducted in 85 different Australia-based firms, we unearth the inter-relationships among environmental, social and economic considerations simultaneously and propose a performance framework for implementing corporate sustainability. The framework consciously interconnects the triple bottom line measures using our 'Triple-I' principles of innovation, integration and interdependence that we propose within the managerial thinking. We describe the implementation of this framework in the form of a step-wise roadmap, using the Plan-Do-Check-Act quality cycle. We believe that such a practical guideline would pave way for continuous improvements in corporate sustainability performances.
- Description: 2003008239
Effective digital forensic analysis of the NTFS disk image
- Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul
- Date: 2009
- Type: Text , Journal article
- Relation: Ubiquitous Computing and Communication Journal Vol. 4, no. 3 (Special issue on ICIT 2009 Conference - Applied Computing) (2009), p. 551-558
- Full Text: false
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- Description: Forensic analysis of the Windows NT File System (NTFS) could provide useful information leading towards malware detection and presentation of digital evidence for the court of law. Since NTFS records every event of the system, forensic tools are required to process an enormous amount of information related to user / kernel environment, buffer overflows, trace conditions, network stack, etc. This has led to imperfect forensic tools that are practical for implementation and hence become popular, but are not comprehensive and effective. Many existing techniques have failed to identify malicious code in hidden data of the NTFS disk image. This research discusses the analysis technique we have adopted to successfully detect maliciousness in hidden data, by investigating the NTFS boot sector. We have conducted experimental studies with some of the existing popular forensics tools and have identified their limitations. Further, through our proposed three-stage forensic analysis process, our experimental investigation attempts to unearth the vulnerabilities of NTFS disk image and the weaknesses of the current forensic techniques.
- Description: 2003007525
A Grid-based neural network framework for multimodal biometrics
- Authors: Venkatraman, Sitalakshmi
- Date: 2010
- Type: Text , Journal article
- Relation: Proceedings of World Academy of Science, Engineering and Technology Vol. 72, no. (2010), p. 298-303
- Full Text: false
- Reviewed:
- Description: Recent scientific investigations indicate that multimodal biometrics overcome the technical limitations of unimodal biometrics, making them ideally suited for everyday life applications that require a reliable authentication system. However, for a successful adoption of multimodal biometrics, such systems would require large heterogeneous datasets with complex multimodal fusion and privacy schemes spanning various distributed environments. From experimental investigations of current multimodal systems, this paper reports the various issues related to speed, error-recovery and privacy that impede the diffusion of such systems in real-life. This calls for a robust mechanism that caters to the desired real-time performance, robust fusion schemes, interoperability and adaptable privacy policies. The main objective of this paper is to present a framework that addresses the abovementioned issues by leveraging on the heterogeneous resource sharing capacities of Grid services and the efficient machine learning capabilities of artificial neural networks (ANN). Hence, this paper proposes a Grid-based neural network framework for adopting multimodal biometrics with the view of overcoming the barriers of performance, privacy and risk issues that are associated with shared heterogeneous multimodal data centres. The framework combines the concept of Grid services for reliable brokering and privacy policy management of shared biometric resources along with a momentum back propagation ANN (MBPANN) model of machine learning for efficient multimodal fusion and authentication schemes. Real-life applications would be able to adopt the proposed framework to cater to the varying business requirements and user privacies for a successful diffusion of multimodal biometrics in various day-to-day transactions.
Virtual worlds: Not the final frontier for games-based nursing education
- Authors: Meredith, Grant , Achterbosch, Leigh , Turville, Kylie , Venkatraman, Sitalakshmi
- Date: 2012
- Type: Text , Conference paper
- Relation: ascilite 2012: Future challenges, sustainable futures p. 1-5
- Full Text: false
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- Description: Virtual worlds present frontiers of promise for the ever evolving venture of pedagogical development, trial and embracement. Of late there have been large pushes into these worlds in terms of health-based education for students and early practitioners. Virtual worlds seem to be the next logical jump into nursing education and can offer a range of simulation benefits. But these worlds do not appeal to all students, can be complex and expensive to develop and interact within. Other game-like avenues exist though and have not been explored thoroughly enough to date. Such genres like puzzles games, management style games and surprisingly first person shooters already have titles and game mechanics which have been somewhat adapted to nursing education but could easily be more thought out and developed to suit. This paper outlines the two major gaming audience types to be considered and then explores a range of options for nursing education beyond virtual worlds.
Applying genetic alogorithm for optimizing broadcasting process in ad-hoc network
- Authors: Elaiwat, Said , Alazab, Ammar , Venkatraman, Sitalakshmi , Alazab, Mamoun
- Date: 2011
- Type: Text , Journal article
- Relation: International Journal of Recent Trends in Engineering & Technology Vol. 4, no. 1 (2011), p. 68-72
- Full Text: false
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- Description: Optimizing broadcasting process in mobile ad hoc network (MANET) is considered as a main challenge due to many problems, such as Broadcast Storm problem and high complexity in finding the optimal tree resulting in an NP-hard problem. Straight forward techniques like simple flooding give rise to Broadcast Storm problem with a high probability. In this work, genetic algorithm (GA) that searches over a population that represents a distinguishable ‘structure’ is adopted innovatively to suit MANETs. The novelty of the GA technique adopted here to provide the means to tackle this MANET problem lies mainly on the proposed method of searching for a structure of a suitable spanning tree that can be optimized, in order to meet the performance indices related to the broadcasting problem. In other words, the proposed genetic model (GM) evolves with the structure of random trees (individuals) ‘genetically’ generated using rules that are devised specifically to capture MANET behaviour in order to arrive at a minimal spanning tree that satisfies certain fitness function. Also, the model has the ability to give different solutions depending on the main factors specified such as, ‘time’ (or speed) in certain situations and ‘reachability’ in certain others.
Mobile payment implementation: a reference framework
- Authors: Venkatraman, Sitalakshmi
- Date: 2008
- Type: Text , Journal article
- Relation: International Journal of Business Information Systems Vol. 3, no. 3 (2008), p. pg. 252-271
- Full Text: false
- Reviewed:
- Description: Over the last few years, there has been a growing prevalence of electronic commerce with most consumers and businesses preferring cashless mode of payments. The recent advancements in wireless data infrastructures have created a new channel for mobile payments. Not all mobile payment implementations, however, are successful from the business point of view as well as the consumer point of view, thereby decelerating the growth of m-business one of the main reasons being lack of suitable guidance or planning for a successful mobile payment adoption. This paper attempts to address this problem by proposing a reference framework or roadmap that adopts the Multicriteria Decision-Making (MCDM) model, incorporating both technical as well as business perspectives for mobile payment implementations. This is illustrated with a case study from the retail industry that adopts the framework for its mobile payment venture. The findings of the study are also discussed.
Towards understanding and improving E-government strategies in Jordan
- Authors: Alkhaleefah, Mohammad , Alkhawaldeh, Mahmoud , Venkatraman, Sitalakshmi , Alazab, Mamoun
- Date: 2010
- Type: Text , Conference paper
- Relation: Paper presented at (ICCBS 2010) International Conference on e-Commerce, e-Business and e-Service Vol. 66, p. 1871-1877
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- Description: Electronic government or e-government initiatives in Jordan are facing major challenges that hinder the country's expected economic and social transformation. The aims of this paper are two-fold, firstly to provide an insight into the understanding of these challenges, and secondly to propose an insight into the understanding of these challenges, and secondly to propose a four-step improvement plan for a successful implementation of Jordan's e-government project. The proposed pragmatic method, strategies and action plan are envisaged to improve Jordan's potential in developing the capability, resources, law and infrastructure for enhancing the e-service delivery to citizens and businesses. Such a method of developing an improvement plan that uniquely aligns with Jordan's e-government strategic pillars would result in the fruitful realization of their e-government vision as a major contributor towards economic and social development. The proposed improvement plan could be adopted by other similar developing countries for successfully implementing their e-government projects as well.
Stochastic model based approach for biometric identification
- Authors: Islam, Mofakharul , Venkatraman, Sitalakshmi , Alazab, Mamoun
- Date: 2010
- Type: Text , Conference proceedings
- Full Text: false
- Description: In this paper, we present a new stochastic model based approach for enhanced image segmentation in biometric identification systems. Biometric features such as fingerprint, face, iris, hand geometry and more recently dental features are being used for human identification. Image analysis of each of these biometric features has various challenges to overcome. To address such contemporary problems of image segmentation, we provide a novel approach based on maximum a posteriori (MAP) fitting Gaussian mixture model using Expectation-Minimization (EM) algorithm within the Bayesian framework. Our new algorithm captures the pixel intensity by the likelihood term in Bayesian Networks, and a priori biasing term of the spatial location information with the help of Markov Random Fields (MRF) model. We have employed a novel approach of using Daubechies wavelet transform for texture feature extraction that uses MRF model and a robust technique of determining the number of pixel classes based on Cluster Ensembles for a reliable segmentation of dental X-ray images. We present how our approach could be applied in dental biometrics to achieve very fast and reliable human identification. Experiments show that our new unsupervised image segmentation technique provides accurate feature extraction and teeth segmentation for effective biometric identification.
Six sigma approach to improve quality in e-services: An empirical study in Jordan
- Authors: Alhyari, Salah , Alazab, Moutaz , Venkatraman, Sitalakshmi , Alazab, Mamoun , Alazab, Ammar
- Date: 2012
- Type: Text , Journal article
- Relation: International Journal of Electronic Government Research Vol. 8, no. 2 (April, 2012), p. 57-74
- Full Text: false
- Reviewed:
- Description: This paper investigates the application of the Six Sigma approach to improve quality in electronic services (e-services) as more countries are adopting e-services as a means of providing services to their people through the Web. This paper presents a case study about the use of Six Sigma model to measure customer satisfaction and quality levels achieved in e-services that were recently launched by public sector organisations in a developing country, such as Jordan. An empirical study consisting of 280 customers of Jordan's e-services is conducted and problems are identified through the DMAIC phases of Six Sigma. The service quality levels are measured and analysed using six main criteria: Website Design, Reliability, Responsiveness, Personalization, Information Quality, and System Quality. The study indicates a 74% customer satisfaction with a Six Sigma level of 2.12 has enabled the Greater Amman Municipality to identify the usability issues associated with their e-services offered by public sector organisations. The aim of the paper is not only to implement Six Sigma as a measurement-based strategy for improving e-customer service in a newly launched e-service programme, but also widen its scope in investigating other service dimensions and perform comparative studies in other developing countries.
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
- Reviewed:
- 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.
Self-learning framework for intrusion detection
- Authors: Venkatraman, Sitalakshmi
- Date: 2010
- Type: Text , Conference proceedings
- Full Text: false
- Description: Present intrusion detections systems (IDS) in both network (NIDS) and host (HIDS) lack the ability to sense signs of intrusions at early stages of attacks, much before any damage occurs. They are unable to cope with new attacking strategies as they predominantly rely on matching patterns of known behaviour (Known signatures). In addition, they are unable to take automatic action in the event of multiple intrusions as they typically resort to manual or semi-manual identification mechanism that are either network-based or host-based separately, rather than collectively. Hence, there is no need for more research to focus on i) automatically identifying new possible intrusions through self-learning methods in order to address zero-day attacks and ii) integrating observed anomalies from NIDS as well as HIDS. With these two objectives, this paper presents a framework that postulates a self-learning monitoring mechanism with the aid of agents to integrate existing knowledge with new observed behaviour patterns gathered from network and host collectively. It also illustrates the working of an agent-based self-learning mechanism in detecting intrusions effectively.
Does the business size matter on corporate sustainable performance? The Australian business case
- Authors: Nayak, Ravi , Venkatraman, Sitalakshmi
- Date: 2011
- Type: Text , Journal article
- Relation: World Review of Entrepreneurship, Management and Sustainable Development Vol. 7, no. 3 (2011), p. 281-301
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- Description: While a growing majority of research studies have concentrated on triple bottom line public reporting in large organisations, the review of past research suggests there seems to be limited support and importance given to small and medium sized businesses. This paper attempts to examine whether business size matters when it comes to corporate sustainability. To achieve this, we have conducted an empirical study to investigate sustainable business practices in small, medium and large organisations. With a sample of 80 different Australia-based firms, we have examined various parameters attributing to corporate sustainability and have arrived at three kinds of performance outcomes (factors) that concur with triple bottom line principles, which we term as: 1) corporate environmental performance outcome (CEPO); 2) corporate social performance outcome (CSPO); 3) corporate financial performance outcome (CFPO). The results of the ANOVA analysis of these factors against business size have been discussed and the significantly higher CEPO in large size businesses than in small or medium size businesses have been explored. This paper also unearths the implications of these results on corporate sustainability and recommends possible improvements to increase the focus around environmental sustainability.
- Description: 2003008915
An optimal transportation routing approach using GIS-based dynamic traffic flows
- Authors: Alazab, Ammar , Venkatraman, Sitalakshmi , Abawajy, Jemal , Alazab, Mamoun
- Date: 2010
- Type: Text , Conference proceedings
- Full Text: false
- Description: This paper examines the value of real-time traffic information gathered through Geographic Information Systems for achieving an optimal vehicle routing within a dynamically stochastic transportation network. We present a systematic approach in determining the dynamically varying parameters and implementation attributes that were used for the development of a Web-based transportation routing application integrated with real-time GIS services. We propose and implement an optimal routing algorithm by modifying Dijkstra’s algorithm in order to incorporate stochastically changing traffic flows. We describe the significant features of our Web application in making use of the real-time dynamic traffic flow information from GIS services towards achieving total costs savings and vehicle usage reduction. These features help users and vehicle drivers in improving their service levels and productivity as the Web application enables them to interactively find the optimal path and in identifying destinations effectively.
Malware detection based on structural and behavioural features of API calls
- Authors: Alazab, Mamoun , Layton, Robert , Venkatraman, Sitalakshmi , Watters, Paul
- Date: 2010
- Type: Text , Conference proceedings
- Full Text: false
- Description: In this paper, we propose a five-step approach to detect obfuscated malware by investigating the structural and behavioural features of API calls. We have developed a fully automated system to disassemble and extract API call features effectively from executables. Using n-gram statistical analysis of binary content, we are able to classify if an executable file is malicious or benign. Our experimental results with a dataset of 242 malwares and 72 benign files have shown a promising accuracy of 96.5% for the unigram model. We also provide a preliminary analysis by our approach using support vector machine (SVM) and by varying n-values from 1 to 5, we have analysed the performance that include accuracy, false positives and false negatives. By applying SVM, we propose to train the classifier and derive an optimum n-gram model for detecting both known and unknown malware efficiently.
Cloud computing: A research roadmap in coalescence with software engineering
- Authors: Venkatraman, Sitalakshmi , Wadhwa, Bimlesh
- Date: 2012
- Type: Text , Journal article
- Relation: Software Engineering Vol. 2, no. 2 (2012), p. 7-17
- Full Text: false
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Malicious code detection using penalized splines on OPcode frequency
- Authors: Alazab, Mamoun , Al Kadiri, Mohammad , Venkatraman, Sitalakshmi , Al-Nemrat, Ameer
- Date: 2012
- Type: Text , Conference proceedings
- Full Text: false
- Description: Recently, malicious software are gaining exponential growth due to the innumerable obfuscations of extended x86 IA-32 (OPcodes) that are being employed to evade from traditional detection methods. In this paper, we design a novel distinguisher to separate malware from benign that combines Multivariate Logistic Regression model using kernel HS in Penalized Splines along with OPcode frequency feature selection technique for efficiently detecting obfuscated malware. The main advantage of our penalized splines based feature selection technique is its performance capability achieved through the efficient filtering and identification of the most important OPcodes used in the obfuscation of malware. This is demonstrated through our successful implementation and experimental results of our proposed model on large malware datasets. The presented approach is effective at identifying previously examined malware and non-malware to assist in reverse engineering. © 2012 IEEE.
- Description: 2003011056
Analysis of firewall log-based detection scenarios for evidence in digital forensics
- Authors: Mukhtar, Rubiu , Al-Nemrat, Ameer , Alazab, Mamoun , Venkatraman, Sitalakshmi , Jahankhani, Hamid
- Date: 2012
- Type: Text , Journal article
- Relation: International Journal of Electronic Security and Digital Forensics Vol. 4, no. 4 (2012), p. 261-279
- Full Text: false
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- Description: With the recent escalating rise in cybercrime, firewall logs have attained much research focus in assessing their capability to serve as excellent evidence in digital forensics. Even though the main aim of firewalls is to screen or filter part or all network traffic, firewall logs could provide rich traffic information that could be used as evidence to prove or disprove the occurrence of online attack events for legal purposes. Since courts have a definition of what could be presented to it as evidence, this research investigates on the determinants for the acceptability of firewall logs as suitable evidence. Two commonly used determinants are tested using three different firewall-protected network scenarios. These determinants are: 1 admissibility that requires the evidence to satisfy certain legal requirements stipulated by the courts 2 weight that represents the sufficiency and extent to which the evidence convinces the establishment of cybercrime attack. Copyright © 2012 Inderscience Enterprises Ltd.
- Description: 2003010400