A study of application level information from the volatile memory of Windows computer systems

The purpose of this research work was to investigate into the seven most commonly used applications in order to uncover information that may have been hidden from forensic investigators by extracting the application level information from volatile memory of a Windows system and performing analysis of that volatile memory. The aim of this research was to formulate how the extracted application level information can be reconstructed to describe what user activities had taken place on the application under investigation. After reviewing the relevant literature on volatile memory analysis and forensically relevant data from Windows applications, this thesis confines its research to a study of the application level information and the volatile memory analysis of Windows applications. Quantitative and qualitative results were produced in this study. The quantitative assessment consists of four metrics and that were used to investigate the quantity of user input on the applications while the qualitative measures were formulated to infer what the user is doing on the application, what they have been doing and what they are using the applications for. The reconstruction of user input activities was carried out by using some commonly used English words to search for user input and pattern matching techniques for when the user input is known in the investigation. The analysis of user input was discussed based on four scenarios developed for this research. The result shows that different amounts of user input can be recovered from various applications. The result in scenario 1, indicates that user input can be recovered easily from Word, PowerPoint, Outlook Email and Internet Explorer 7.0 and that little user input can be found on Excel, MS Access and Adobe Reader 8.0. In scenario 2, a significant amount of user input was recovered in the memory allocated to all the applications except MS Access where little user input was found. In scenario3, only Outlook Email and Internet Explorer 7.0 resulted in a large amount of user input being recovered. The rest of the applications retain little user input in memory. In scenario 4, a greatly reduced amount of information was found for all the applications. But some user input was found from Outlook Email and Internet Explorer 7.0 which shows that user input can be retained for some time in the memory. After the analysis of user input, the importance of volatile memory of the application level information was discussed. A procedure has been formulised for the extraction and analysis of application level information and these have been discussed with respect to their use in the court of law based on the five Daubert tests of scientific method of gathering digital evidence. As presented, three out of the Daubert tests have been completed while the two others forms the unique contribution of the research project to digital forensic community. The author recommends that the research theory of application level information should be extended to other operating systems using the scenarios formulated in this research project.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

On the Investigation of Social Network Analysis for E-Commerce Transaction in South-West Region of Nigeria

An investigative survey of the application of Social Network Analysis on e-commerce is presented and methods to improve e-commerce activity in this region is reported. The research reviewed relevant papers by survey based on the existing research work in the field of e-commerce, using social network analysis. This research presents an investigation on the application of social network analysis on e-commerce, with a case study of the user’s perception in the South West Region of Nigeria. An investigation that was carried out revealed the different research works of others and the research was built upon by the metric presented. This approach was applied to influence the importance of Social Network Analysis in e-commerce. The data collected and the methods used by researcher proved the usefulness of the measures used in Social Network Analysis of e-Commerce. This research shows that the importance and potential of Social Network Analysis on e-commerce, is particularly, based on how Social Network Analysis has been used to improve e-commerce recommender systems which can give users a better shopping experience in Nigeria. Using Social Network Analysis for E-commerce in South west Nigeria to improve e- commerce activities

Optimizing the performance of the advanced encryption standard techniques for secured data transmission

Information security has emerged as a critical concern in data communications. The use of cryptographic methods is one approach for ensuring data security. A cryptography implementation often consists of complex algorithms that are used to secure the data. Several security techniques, including the Data Encryption Standard (DES), Triple Data Encryption Standard (3DES), Twofish, Rivest-Shamir-Adleman (RSA), Elliptic curve cryptography, and many others, have been created and are used in the data encryption process. However, the Advanced Encryption Standard (Rijndael) has received a lot of attention recently due to its effectiveness and level of security. To increase the scope of AES's numerous uses, it is crucial to develop high-performance AES. To enhance the processing time of AES methods, the research provided solution performance of the AES algorithm. This includes additional layers of encoding, decoding, shrinking and expansion techniques of the analysis that was performed. Data findings are produced for further actions based on the outcome

Implementation of the Enhanced Fingerprint Authentication in the ATM System Using ATmega128 with GSM Feedback Mechanism

ATM was introduced to boost the cashless policy in Nigeria. Current trend of Cybercrime facilitate the need for an enhanced fingerprint application on ATM machine with GSM Feedback mechanism. The mechanism enable unassigned fingerprint authentication of customers with quick code and secret code. The project enhances the security authentication of customers using ATM. A core controller using fingerprint recognition system of ATmega128 in-system programmable flash is explored. An SM630 fingerprint module is used to capture fingerprints with DSP processor and optical sensor for verification, using AT command of GSM module for feedback text messaging (i.e. sending of Quick and Secret-Codes respectively). Upon system testing of capable reduction of ATM fraud using C program, the new method of authentication is presented

Fraud mitigation in attendance monitoring systems using dynamic QR code, geofencing and IMEI technologies

Attendance monitoring is a vital activity in several organizations. Due to its importance, many attendance monitoring systems have been developed to automate this process. Despite several advancements in automated attendance management solutions, attendance fraud remains an issue as some end users can manipulate known vulnerabilities, such as proxy attendance, buddy-punching, early departure, and so on. In this paper, a fraud-resistant attendance management solution is developed by harnessing technologies such as geofencing, dynamic QR code and IMEI Checking. The proposed solution is comprised of a single-page web application where QR code can be enabled for attendance registration, and a mobile application, where endusers can scan generated QR code to register their attendance. Attendance cheating via QR code sharing is prevented by encoding the polygonal coordinates of the event venue in the QR code to determine if the user is within the venue. The proposed system solves the problem of proxy attendance by registering and verifying the end user’s device IMEI number. Results obtained from testing indicate that attempts at committing a variety of attendance frauds are effectively mitigated

REALTIME FRAUD DETECTION IN THE BANKING SECTOR USING DATA MINING TECHNIQUES/ALGORITHM

Abstract—The banking sector is a very important sector in our present day generation where almost every human has to deal with the bank either physically or online. In dealing with the banks, the customers and the banks face the chances of been trapped by fraudsters. Examples of fraud include insurance fraud, credit card fraud, accounting fraud, etc. Detection of fraudulent activity is thus critical to control these costs. This paper hereby addresses bank fraud detection via the use of data-mining techniques; association, clustering, forecasting, and classification to analyze the customer data in order to identify the patterns that can lead to frauds. Upon identification of the patterns, adding a higher level of verification/authentication to banking processes can be added Keywords: Data mining techniques, banking sector, fraud, and authentication