The importance of mandatory data breach notification to identity crime
- Holm, Eric, Mackenzie, Geraldine
- Authors: Holm, Eric , Mackenzie, Geraldine
- Date: 2014
- Type: Text , Conference proceedings
- Full Text:
- Description: The relationship between data breaches and identity crime has been scarcely explored in current literature. However, there is an important relationship between the misuse of personal identification information and identity crime as the former is in many respects the catalyst for the latter. Data breaches are one of the ways in which this personal identification information is obtained by identity criminals, and thereby any response to data breaches is likely to impact the incidence of identity crime. Initiatives around data breach notification have become increasingly prevalent and are now seen in many State legislatures in the United States and overseas. The Australian Government is currently in the process of introducing mandatory data breach notification laws. This paper explores the introduction of mandatory data breach notification in Australia, and lessons learned from the experience in the US, particularly noting the link between data breaches and identity crime. The paper proposes that through the introduction of such laws, identity crimes are likely to be reduced.
- Authors: Holm, Eric , Mackenzie, Geraldine
- Date: 2014
- Type: Text , Conference proceedings
- Full Text:
- Description: The relationship between data breaches and identity crime has been scarcely explored in current literature. However, there is an important relationship between the misuse of personal identification information and identity crime as the former is in many respects the catalyst for the latter. Data breaches are one of the ways in which this personal identification information is obtained by identity criminals, and thereby any response to data breaches is likely to impact the incidence of identity crime. Initiatives around data breach notification have become increasingly prevalent and are now seen in many State legislatures in the United States and overseas. The Australian Government is currently in the process of introducing mandatory data breach notification laws. This paper explores the introduction of mandatory data breach notification in Australia, and lessons learned from the experience in the US, particularly noting the link between data breaches and identity crime. The paper proposes that through the introduction of such laws, identity crimes are likely to be reduced.
Identity crime : The challenges in the regulation of identity crime
- Authors: Holm, Eric
- Date: 2012
- Type: Text , Conference proceedings
- Full Text:
- Description: This paper discusses the unique challenges of regulating identity crime. Identity crime involves the use of personal identification information to perpetrate crimes of fraud. As such, the identity crime involves using personal and private information to perpetrate crime. This article considers the two significant issues that obstruct responses to this crime; firstly, the reporting of crime. Secondly the paper considers the issue of jurisdiction. Finally, the paper explores some responses to this crime. The paper then explores some of the current responses to identity crime. © 2012 IEEE.
- Authors: Holm, Eric
- Date: 2012
- Type: Text , Conference proceedings
- Full Text:
- Description: This paper discusses the unique challenges of regulating identity crime. Identity crime involves the use of personal identification information to perpetrate crimes of fraud. As such, the identity crime involves using personal and private information to perpetrate crime. This article considers the two significant issues that obstruct responses to this crime; firstly, the reporting of crime. Secondly the paper considers the issue of jurisdiction. Finally, the paper explores some responses to this crime. The paper then explores some of the current responses to identity crime. © 2012 IEEE.
Zero-day malware detection based on supervised learning algorithms of API call signatures
- Alazab, Mamoun, Venkatraman, Sitalakshmi, Watters, Paul, Alazab, Moutaz
- 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
- 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
The seven scam types: Mapping the terrain of cybercrime
- Stabek, Amber, Watters, Paul, Layton, Robert
- Authors: Stabek, Amber , Watters, Paul , Layton, Robert
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- 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.
- Authors: Stabek, Amber , Watters, Paul , Layton, Robert
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- 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.
Understanding victims of identity theft: Preliminary insights
- Turville, Kylie, Yearwood, John, Miller, Charlynn
- Authors: Turville, Kylie , Yearwood, John , Miller, Charlynn
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: Identity theft is not a new crime, however changes in society and the way that business is conducted have made it an easier, attractive and more lucrative crime. When a victim discovers the misuse of their identity they must then begin the process of recovery, including fixing any issues that may have been created by the misuse. For some victims this may only take a small amount of time and effort, however for others they may continue to experience issues for many years after the initial moment of discovery. To date, little research has been conducted within Australia or internationally regarding what a victim experiences as they work through the recovery process. This paper presents a summary of the identity theft domain with an emphasis on research conducted within Australia, and identifies a number of issues regarding research in this area. The paper also provides an overview of the research project currently being undertaken by the authors in obtaining an understanding of what victims of identity theft experience during the recovery process; particularly their experiences when dealing with organizations. Finally, it reports on some of the preliminary work that has already been conducted for the research project. © 2010 IEEE.
- Authors: Turville, Kylie , Yearwood, John , Miller, Charlynn
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: Identity theft is not a new crime, however changes in society and the way that business is conducted have made it an easier, attractive and more lucrative crime. When a victim discovers the misuse of their identity they must then begin the process of recovery, including fixing any issues that may have been created by the misuse. For some victims this may only take a small amount of time and effort, however for others they may continue to experience issues for many years after the initial moment of discovery. To date, little research has been conducted within Australia or internationally regarding what a victim experiences as they work through the recovery process. This paper presents a summary of the identity theft domain with an emphasis on research conducted within Australia, and identifies a number of issues regarding research in this area. The paper also provides an overview of the research project currently being undertaken by the authors in obtaining an understanding of what victims of identity theft experience during the recovery process; particularly their experiences when dealing with organizations. Finally, it reports on some of the preliminary work that has already been conducted for the research project. © 2010 IEEE.
Windows rootkits: Attacks and countermeasures
- Lobo, Desmond, Watters, Paul, Wu, Xin, Sun, Li
- Authors: Lobo, Desmond , Watters, Paul , Wu, Xin , Sun, Li
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: Windows XP is the dominant operating system in the world today and rootkits have been a major concern for XP users. This paper provides an in-depth analysis of the rootkits that target that operating system, while focusing on those that use various hooking techniques to hide malware on a machine. We identify some of the weaknesses in the Windows XP architecture that rootkits exploit and then evaluate some of the anti-rootkit security features that Microsoft has unveiled in Vista and 7. To reduce the number of rootkit infections in the future, we suggest that Microsoft should take full advantage of Intel's four distinct privilege levels. © 2010 IEEE.
- Authors: Lobo, Desmond , Watters, Paul , Wu, Xin , Sun, Li
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: Windows XP is the dominant operating system in the world today and rootkits have been a major concern for XP users. This paper provides an in-depth analysis of the rootkits that target that operating system, while focusing on those that use various hooking techniques to hide malware on a machine. We identify some of the weaknesses in the Windows XP architecture that rootkits exploit and then evaluate some of the anti-rootkit security features that Microsoft has unveiled in Vista and 7. To reduce the number of rootkit infections in the future, we suggest that Microsoft should take full advantage of Intel's four distinct privilege levels. © 2010 IEEE.
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