Digital Commons Network^™

Machine Learning Techniques For Credit Card Fraud Detection, Hossam Eldin Mohammed Abd El-Hamid Ahmed Abdou, Wael Khalifa, Mohamed Ismail Roushdy, Abdel-Badeeh M. Salem

Future Computing and Informatics Journal

The term “fraud”, it always concerned about credit card fraud in our minds. And after the significant increase in the transactions of credit card, the fraud of credit card increased extremely in last years. So the fraud detection should include surveillance of the spending attitude for the person/customer to the determination, avoidance, and detection of unwanted behavior. Because the credit card is the most payment predominant way for the online and regular purchasing, the credit card fraud raises highly. The Fraud detection is not only concerned with capturing of the fraudulent practices, but also, discover it as fast as they …

Bleeding Out: The Case For Strengthening Healthcare Client Portal Data Privacy Regulations, Matthew D. Mccord

Minnesota Journal of Law, Science & Technology

No abstract provided.

Detection Of Fraud Risks In Retailing Sector Using Mlp And Svm Techniques, Davut Pehli̇vanli, Süleyman Eken, Ebu Beki̇r Ayan

Turkish Journal of Electrical Engineering and Computer Sciences

In today's business conditions, where business activities are spreading over a wide geographical area, fraud auditing processes have crucial importance especially for the retailing sector which has a high branch network. In the retailing sector, especially purchasing processes are subject to high fraud risks. This paper shows that it is possible to detect fraudulent processes by applying data mining techniques on operational data related to purchasing activities. Within this scope, in order to detect the fraudulent purchasing operations, support vector machine (SVM) models with different kernels and artificial neural networks methods have been used and successful results have been achieved. …

Scheduling In Mapreduce Clusters, Chen He

School of Computing: Dissertations, Theses, and Student Research

MapReduce is a framework proposed by Google for processing huge amounts of data in a distributed environment. The simplicity of the programming model and the fault-tolerance feature of the framework make it very popular in Big Data processing.

As MapReduce clusters get popular, their scheduling becomes increasingly important. On one hand, many MapReduce applications have high performance requirements, for example, on response time and/or throughput. On the other hand, with the increasing size of MapReduce clusters, the energy-efficient scheduling of MapReduce clusters becomes inevitable. These scheduling challenges, however, have not been systematically studied.

The objective of this dissertation is to …

Application Of Synthetic Informative Minority Over-Sampling (Simo) Algorithm Leveraging Support Vector Machine (Svm) On Small Datasets With Class Imbalance, Akshatha Fakkeriah Kallappanamatt

Dissertations

Developing predictive models for classification problems considering imbalanced datasets is one of the basic difficulties in data mining and decision-analytics. A classifier’s performance will decline dramatically when applied to an imbalanced dataset. Standard classifiers such as logistic regression, Support Vector Machine (SVM) are appropriate for balanced training sets whereas provides suboptimal classification results when used on unbalanced dataset. Performance metric with prediction accuracy encourages a bias towards the majority class, while the rare instances remain unknown though the model contributes a high overall precision. There are chances where minority instances might be treated as noise and vice versa. (Haixiang et …

Cyber Security Risks In Public High Schools, Ion Goran

Student Theses

Today, just like other organizations, schools are vulnerable to cyber-attacks. This vulnerability has vividly revealed itself in recent years, with the number of attacks on public schools increasing and taking ever-changing forms. Today, the student’s grades, disciplinary notes, learning diagnoses, phone numbers, addresses, and another identifying information is all at risk of being exposed. Moreover, poor network security poses a dire threat to parents of school children whose personal records contain sensitive or dangerous information. The practical implications of these attacks require intervention or remedy to increase cyber security. Cyberattacks may take place when storage facilities or infected devices are …

Can Phishing Education Enable Users To Recognize Phishing Attacks?, Hanaa Alghamdi

Dissertations

Phishing attacks have increased rapidly and caused many drastic damages and losses for internet users‟ .The purpose of this research is to investigate on effectiveness of phishing education and training to help users identify different forms of phishing threats. The study has been conducted through developing a phishing quiz mobile application which includes four kinds of phishing threats. It tested the ability of users to recognize spoofed emails, SMS phishing (SMshing), scam phone calls (Vishing), and phishing through social media networks. A comprehensive literature review was discussed to investigate on the research area, understand the research problem, support the proposed …

A Reduced Labeled Samples (Rls) Framework For Classification Of Imbalanced Concept-Drifting Streaming Data., Elaheh Arabmakki

Electronic Theses and Dissertations

Stream processing frameworks are designed to process the streaming data that arrives in time. An example of such data is stream of emails that a user receives every day. Most of the real world data streams are also imbalanced as is in the stream of emails, which contains few spam emails compared to a lot of legitimate emails. The classification of the imbalanced data stream is challenging due to the several reasons: First of all, data streams are huge and they can not be stored in the memory for one time processing. Second, if the data is imbalanced, the accuracy …

Paper Session Ii: Computer Forensics Field Triage Process Model, Marcus K. Rogers, James Goldman, Rick Mislan, Timothy Wedge, Steve Debrota

Annual ADFSL Conference on Digital Forensics, Security and Law

With the proliferation of digital based evidence, the need for the timely identification, analysis and interpretation of digital evidence is becoming more crucial. In many investigations critical information is required while at the scene or within a short period of time - measured in hours as opposed to days. The traditional cyber forensics approach of seizing a system(s)/media, transporting it to the lab, making a forensic image(s), and then searching the entire system for potential evidence, is no longer appropriate in some circumstances. In cases such as child abductions, pedophiles, missing or exploited persons, time is of the essence. In …

Designing A Data Warehouse For Cyber Crimes, Il-Yeol Song, John D. Maguire, Ki Jung Lee, Namyoun Choi, Xiaohua Hu, Peter Chen

Annual ADFSL Conference on Digital Forensics, Security and Law

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on …

The Proceedings Of 14th Australian Digital Forensics Conference, 5-6 December 2016, Edith Cowan University, Perth, Australia, Craig Valli

Australian Digital Forensics Conference

Conference Foreword

This is the fifth year that the Australian Digital Forensics Conference has been held under the banner of the Security Research Institute, which is in part due to the success of the security conference program at ECU. As with previous years, the conference continues to see a quality papers with a number from local and international authors. 11 papers were submitted and following a double blind peer review process, 8 were accepted for final presentation and publication. Conferences such as these are simply not possible without willing volunteers who follow through with the commitment they have initially made, …

The Role Of Cryptography In Security For Electronic Commerce, Ann Murphy, David Murphy

The ITB Journal

Many businesses and consumers are wary of conducting business over the Internet due to a perceived lack of security. Electronic business is subject to a variety of threats such as unauthorised access, misappropriation, alteration and destruction of both data and systems. This paper explores the major security concerns of businesses and users and describes the cryptographic techniques used to reduce such risks.

Multi-Stakeholder Case Prioritization In Digital Investigations, Joshua I. James

Journal of Digital Forensics, Security and Law

This work examines the problem of case prioritization in digital investigations for better utilization of limited criminal investigation resources. Current methods of case prioritization, as well as observed prioritization methods used in digital forensic investigation laboratories are examined. After, a multi-stakeholder approach to case prioritization is given that may help reduce reputational risk to digital forensic laboratories while improving resource allocation. A survey is given that shows differing opinions of investigation priority between Law Enforcement and the public that is used in the development of a prioritization model. Finally, an example case is given to demonstrate the practicality of the …

Rank Based Anomaly Detection Algorithms, Huaming Huang

Electrical Engineering and Computer Science - Dissertations

Anomaly or outlier detection problems are of considerable importance, arising frequently in diverse real-world applications such as finance and cyber-security. Several algorithms have been formulated for such problems, usually based on formulating a problem-dependent heuristic or distance metric. This dissertation proposes anomaly detection algorithms that exploit the notion of ``rank," expressing relative outlierness of different points in the relevant space, and exploiting asymmetry in nearest neighbor relations between points: a data point is ``more anomalous" if it is not the nearest neighbor of its nearest neighbors. Although rank is computed using distance, it is a more robust and higher level …

Automating Vendor Fraud Detection In Enterprise Systems, Kishore Singh, Peter Best, Joseph Mula

Journal of Digital Forensics, Security and Law

Fraud is a multi-billion dollar industry that continues to grow annually. Many organizations are poorly prepared to prevent and detect fraud. Fraud detection strategies are intended to quickly and efficiently identify fraudulent activities that circumvent preventative measures. In this paper, we adopt a DesignScience methodological framework to develop a model for detection of vendor fraud based on analysis of patterns or signatures identified in enterprise system audit trails. The concept is demonstrated by developing prototype software. Verification of the prototype is achieved by performing a series of experiments. Validation is achieved by independent reviews from auditing practitioners. Key findings of …

On The Development Of A Digital Forensics Curriculum, Manghui Tu, Dianxiang Xu, Samsuddin Wira, Cristian Balan, Kyle Cronin

Journal of Digital Forensics, Security and Law

Computer Crime and computer related incidents continue their prevalence and frequency, resulting in losses approaching billions of dollars. To fight against these crimes and frauds, it is urgent to develop digital forensics education programs to train a suitable workforce that can effectively investigate computer crimes and incidents. There is presently no standard to guide the design of digital forensics curriculum for an academic program. In this research, previous work on digital forensics curriculum design and existing education programs are thoroughly investigated. Both digital forensics educators and practitioners were surveyed and results were analyzed to determine the industry and law enforcement …

Developing A Forensic Continuous Audit Model, Grover S. Kearns, Katherine J. Barker, Stephen P. Danese

Journal of Digital Forensics, Security and Law

Despite increased attention to internal controls and risk assessment, traditional audit approaches do not seem to be highly effective in uncovering the majority of frauds. Less than 20 percent of all occupational frauds are uncovered by auditors. Forensic accounting has recognized the need for automated approaches to fraud analysis yet research has not examined the benefits of forensic continuous auditing as a method to detect and deter corporate fraud. The purpose of this paper is to show how such an approach is possible. A model is presented that supports the acceptance of forensic continuous auditing by auditors and management as …

Defining A Forensic Audit, G. S. Smith, D. L. Crumbley

Journal of Digital Forensics, Security and Law

Disclosures about new financial frauds and scandals are continually appearing in the press. As a consequence, the accounting profession's traditional methods of monitoring corporate financial activities are under intense scrutiny. At the same time, there is recognition that principles-based GAAP from the International Accounting Standards Board will become the recognized standard in the U.S. The authors argue that these two factors will change the practices used to fight corporate malfeasance as investigators adapt the techniques of accounting into a forensic audit engagement model.

Self-Reported Cyber Crime: An Analysis On The Effects Of Anonymity And Pre-Employment Integrity, Ibrahim Baggili, Marcus Rogers

Electrical & Computer Engineering and Computer Science Faculty Publications

A key issue facing today’s society is the increase in cyber crimes. Cyber crimes pose threats to nations, organizations and individuals across the globe. Much of the research in cyber crime has risen from computer science-centric programs, and little experimental research has been performed on the psychology of cyber crime. This has caused a knowledge gap in the study of cyber crime. To this end, this research focuses on understanding psychological concepts related to cyber crime. Through an experimental design, participants were randomly assigned to three groups with varying degrees of anonymity. After each treatment, participants were asked to self-report …

Continuous Fraud Detection In Enterprise Systems Through Audit Trail Analysis, Peter J. Best, Pall Rikhardsson, Mark Toleman

Journal of Digital Forensics, Security and Law

Enterprise systems, real time recording and real time reporting pose new and significant challenges to the accounting and auditing professions. This includes developing methods and tools for continuous assurance and fraud detection. In this paper we propose a methodology for continuous fraud detection that exploits security audit logs, changes in master records and accounting audit trails in enterprise systems. The steps in this process are: (1) threat monitoringsurveillance of security audit logs for ‘red flags’, (2) automated extraction and analysis of data from audit trails, and (3) using forensic investigation techniques to determine whether a fraud has actually occurred. We …

Data Mining Techniques For Fraud Detection, Rekha Bhowmik

Annual ADFSL Conference on Digital Forensics, Security and Law

The paper presents application of data mining techniques to fraud analysis. We present some classification and prediction data mining techniques which we consider important to handle fraud detection. There exist a number of data mining algorithms and we present statistics-based algorithm, decision tree-based algorithm and rule-based algorithm. We present Bayesian classification model to detect fraud in automobile insurance. Naïve Bayesian visualization is selected to analyze and interpret the classifier predictions. We illustrate how ROC curves can be deployed for model assessment in order to provide a more intuitive analysis of the models.

Keywords: Data Mining, Decision Tree, Bayesian Network, ROC …

Data Mining Techniques In Fraud Detection, Rekha Bhowmik

Journal of Digital Forensics, Security and Law

The paper presents application of data mining techniques to fraud analysis. We present some classification and prediction data mining techniques which we consider important to handle fraud detection. There exist a number of data mining algorithms and we present statistics-based algorithm, decision treebased algorithm and rule-based algorithm. We present Bayesian classification model to detect fraud in automobile insurance. Naïve Bayesian visualization is selected to analyze and interpret the classifier predictions. We illustrate how ROC curves can be deployed for model assessment in order to provide a more intuitive analysis of the models.

Paper Session Iv: Development And Delivery Of Coursework - The Legal/Regulatory/Policy Environment Of Cyberforensics, John W. Bagby, John C. Ruhnka

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper describes a cyber-forensics course that integrates important public policy and legal issues as well as relevant forensic techniques. Cyber-forensics refers to the amalgam of multi-disciplinary activities involved in the identification, gathering, handling, custody, use and security of electronic files and records, involving expertise from the forensic domain, and which produces evidence useful in the proof of facts for both commercial and legal activities. The legal and regulatory environment in which electronic discovery takes place is of critical importance to cyber-forensics experts because the legal process imposes both constraints and opportunities for the effective use of evidence gathered through …

Designing A Data Warehouse For Cyber Crimes, Il-Yeol Song, John D. Maguire, Ki Jung Lee, Namyoun Choi, Xiaohua Hu, Peter Chen

Journal of Digital Forensics, Security and Law

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on …

A Curriculum For Teaching Information Technology Investigative Techniques For Auditors, Grover S. Kearns

Journal of Digital Forensics, Security and Law

Recent prosecutions of highly publicized white-collar crimes combined with public outrage have resulted in heightened regulation of financial reporting and greater emphasis on systems of internal control. Because both white-collar and cybercrimes are usually perpetrated through computers, internal and external auditors’ knowledge of information technology (IT) is now more vital than ever. However, preserving digital evidence and investigative techniques, which can be essential to fraud examinations, are not skills frequently taught in accounting programs and instruction in the use of computer assisted auditing tools and techniques – applications that might uncover fraudulent activity – is limited. Only a few university-level …

Development And Delivery Of Coursework: The Legal/Regulatory/Policy Environment Of Cyberforensics, John W. Bagby, John C. Ruhnka

Journal of Digital Forensics, Security and Law

This paper describes a cyber-forensics course that integrates important public policy and legal issues as well as relevant forensic techniques. Cyber-forensics refers to the amalgam of multi-disciplinary activities involved in the identification, gathering, handling, custody, use and security of electronic files and records, involving expertise from the forensic domain, and which produces evidence useful in the proof of facts for both commercial and legal activities. The legal and regulatory environment in which electronic discovery takes place is of critical importance to cyber-forensics experts because the legal process imposes both constraints and opportunities for the effective use of evidence gathered through …

Computer Forensics Field Triage Process Model, Marcus K. Rogers, James Goldman, Rick Mislan, Timothy Wedge, Steve Debrota

Journal of Digital Forensics, Security and Law

With the proliferation of digital based evidence, the need for the timely identification, analysis and interpretation of digital evidence is becoming more crucial. In many investigations critical information is required while at the scene or within a short period of time - measured in hours as opposed to days. The traditional cyber forensics approach of seizing a system(s)/media, transporting it to the lab, making a forensic image(s), and then searching the entire system for potential evidence, is no longer appropriate in some circumstances. In cases such as child abductions, pedophiles, missing or exploited persons, time is of the essence. In …