Shahrin Sahib

An Introduction to Image Steganography Techniques

Steganography is a form of security technique through obscurity, the science and art of hiding the existence of a message between sender and intended recipient. Steganography has been used to hide secret messages in various types of files, including digital images, audio and video. The three most important parameters for audio steganography are imperceptibility, payload, and robustness. Different applications have different requirements of the steganography technique used. This paper intends to give an overview of image steganography, its uses and techniques.

Analysis of Features Selection and Machine Learning Classifier in Android Malware Detection

The proliferation of Android-based mobile devices and mobile applications in the market has triggered the malware author to make the mobile devices as the next profitable target. With user are now able to use mobile devices for various purposes such as web browsing, ubiquitous services, online banking, social networking, MMS and etc, more credential information is expose to exploitation. Applying a similar security solution that work in Desktop environment to mobile devices may not be proper as mobile devices have a limited storage, memory, CPU and power consumption. Hence, there is a need to develop a mobile malware detection that can provide an effective solution to defence the mobile user from any malicious threat and at the same time address the limitation of mobile devices environment. Prior to this matter, this research focused on evaluating the best features selection to be used in the best machine-learning classifiers. To find the best combination of both features selection and classifier, five sets of different feature selection are applies to five different machine learning classifiers. The classifier outcome is evaluated using the True Positive Rate (TPR), False Positive Rate (FPR), and Accuracy. The best combination of both features selection and classifier can be used to reduce features selection and at the same time able to classify the infected android application accurately.

Image Super-Resolution via Discrete Tchebichef Moment

Super-resolution is a set of methods of increasing or doubling image resolution. Super-resolution algorithms can be divided into frequency or space domain. In this paper, a simple technique shall be applied in both space and frequency domain of an image. This transform integrates a simplified mathematical framework technique using matrices, as well as a block-wise reconstruction technique. Tchebichef moment has been chosen here since it performs better than the popular Discrete Cosine Transform.

Image watermarking using psychovisual threshold over the edge

Currently the digital multimedia data can easily be copied. Digital image watermarking is an alternative approach to authentication and copyright protection of digital image content. An alternative embedding watermark based on human eye properties can be used to effectively hide the watermark image. This paper introduces the embedding watermark scheme along the edge based on the concept of psychovisual threshold. This paper will investigate the sensitivity of minor changes in DCT coefficients against JPEG quantization tables. Based on the concept of psychovisual threshold, there are still deep holes in JPEG quantization values to embed a watermark. This paper locates and utilizes them to embed a watermark. The proposed scheme has been tested against various non-malicious attacks. The experiment results show the watermark is robust against JPEG image compression, noise attacks and low pass filtering.

Image Projection over the Edge

Image projection is usually associated with image enlargement projected on screen or large display devices. The objective of this paper is to achieve sharper image projection and thinner transition over the edge. Tchebichef moment has been chosen here since it performs better than the popular Discrete Cosine Transform. This transform integrates a simplified mathematical framework technique using matrices, as well as a block-wise reconstruction technique. The result shows Tchebichef moment gives better image projection over the edge on graphical and real images.

Psychovisual model on discrete orthonormal transform

Discrete Orthonormal Transform has been a basis for digital image processing. The lesser coefficients of a Discrete Orthonormal Transform to reconstruct an image is the more compact support the Discrete Orthonormal Transform provides to an image. Tchebychev Moment Transform has been shown to provide a more compact support to an image than the popular Discrete Cosine Transform. This paper will investigate the contribution of each coefficient of the Discrete Orthonormal Transform to the image reconstruction. The error threshold in image reconstruction will be the primitive of Psychovisual Model to an image. An experimental result shall show that the Psychovisual Model will provide a statistically efficient error threshold for image reconstruction.

Perception on Cyber Terrorism: A Focus Group Discussion Approach

Focus group discussion is an exploratory research technique used to collect data through group interaction. This technique provides the opportunity to observe interaction among participants on a topic under this study. This paper contributes to an understanding on the cyber terrorism conceptual framework through the analysis of focus group discussion. The proposed cyber terrorism conceptual framework which was obtained during the qualitative study by the authors has been used as a basis for discussion in the focus group discussion. Thirty (30) participants took part in the focus group discussion. The overall results suggest that the proposed cyber terrorism framework is acceptable by the participants. The present study supports our initial research that the cyber terrorism conceptual framework constitutes the following components: target, motivation, tools of attack, domain, methods of attack and impact.

Understanding cyber terrorism: The grounded theory method applied

Grounded theory method is gaining importance as a method for theory building about a particular phenomenon. One of the most important benefits is the ability to derive theory from and within the context of data collected. In this research, the authors analyzed the data by using a grounded theory method, in which the cyber terrorism framework is drawn. This paper proposes a conceptual framework describing the components of cyber terrorism from six perspectives: Target, motivation, tools of attack, domain, method of action, and impact. The framework provides a baseline when establishing and defining the concept of cyber terrorism. The finding of this work contributes as strategic input to the policy and decision makers in formulating and developing better policy and strategy to counter cyber terrorism.

Traceability in digital forensic investigation process

Digital forensic is part of forensic science that implicitly covers crime that is related to computer technology. In a cyber crime, digital evidence investigation requires a special procedures and techniques in order to be used and be accepted in court of law. Generally, the goals of these special processes are to identify the origin of the incident reported as well as maintaining the chain of custody so that the legal process can take its option. Subsequently, the traceability process has become a key or an important element of the digital investigation process, as it is capable to map the events of an incident from difference sources in obtaining evidence of an incident to be used for other auxiliary investigation aspects. Hence, this paper introduces a trace map model to illustrate the relationship in the digital forensic investigation process by adapting and integrating the traceability features. The objective of this integration is to provide the capability of trace and map the evidence to the sources and shows the link between the evidence, the entities and the sources involved in the process, particularly in the collection phase of digital forensic investigation framework. Additionally, the proposed model is expected to help the forensic investigator in obtaining accurate and complete evidence that can be further used in a court of law.

CNC PCB drilling machine using Novel Natural Approach to Euclidean TSP

Nowadays, many industries use the Computerized Numerical Control (CNC) for Printed Circuit Board (PCB) drilling machines in industrial operations. It takes a long time to find optimal tour for large number of nodes (up to thousands). To achieve more effective results, optimization systems approach is required to be equipped in drilling machine. Euclidean Traveling Salesman Problem (TSP) is one of optimization method that gives fast near optimal solution for the drilling machine movement using novel friendly techniques. This paper describes the development of that CNC PCB drilling machine with novel approach to Euclidean TSP. This design can be widely applied to various CNC PCB drilling machines in small and medium scale manufacturing industries.