Shamsul Kamal Ahmad Khalid

Anti-cropping digital image watermarking using Sudoku

Many digital image watermarking schemes have been developed to embed copyright information into an image. However, an attacker may reuse parts of a watermarked image by cropping out unwanted parts. Several techniques have been designed to overcome this attack but due to their limited redundancy approach, some section of the images can still be retrieved without detectable watermark. In this paper, a new watermarking scheme that is robust against severe cropping using Sudoku is proposed. It is based on Sudokus permutation property that allows evenly distributed copies of watermark pieces in all parts of the cover image. A valid Sudoku solution is used during the embedding as well as during the detection of the watermark. Using classic 9 × 9 Sudoku, the scheme demonstrated robustness of up to 94% of random cropping.

Automatic Generation of Assertions to Detect Potential Security Vulnerabilities in C Programs That Use Union and Pointer Types

Type unions, pointer variables and function pointers are a long standing source of subtle security bugs in C program code. Their use can lead to hard-to-diagnose crashes or exploitable vulnerabilities that allow an attacker to attain privileged access over classified data. This paper describes an automatable framework for detecting such weaknesses in C programs statically, where possible, and for generating assertions that will detect them dynamically, in other cases. Exclusively based on analysis of the source code, it identifies required assertions using a type inference system supported by a custom made symbol table. In our preliminary findings, our type system was able to infer the correct type of unions in different scopes, without manual code annotations or rewriting. Whenever an evaluation is not possible or is difficult to resolve, appropriate runtime assertions are formed and inserted into the source code. The approach is demonstrated via a prototype C analysis tool.

A customizable wireless food ordering system with realtime customer feedback

The existence of wireless technology and the emergence of mobile devices enable a simple yet powerful infrastructure for business application. Some early efforts have been made to utilize both technologies in food ordering system implementations. However, the food ordering systems that have been proposed earlier exhibit limitations, primarily in cost effectiveness, allowing customizations and supporting real-time feedback to customers. In this paper, we discuss the design and implementation of a customizable wireless food ordering system with real-time customer feedback for a restaurant (CWOS-RTF). The CWOS-RTF enables restaurant owners to setup the system in wireless environment and update menu presentations easily. Smart phone has been integrated in the CWOS-RTF implementation to facilitate real-time communication between restaurant owners and customers. A preliminary testing suggests that the CWOS-RTF has the potential to eliminate the limitations of existing food ordering systems.

Classification of JPEG Files by Using Extreme Learning Machine

Recovery of data files when their system information missing is a challenging research issue. The recovery process entails methods that analyze the structure and contents of each individual file clusters. A primary and important process of files’ recovery is determining the files’ types including JPEG, DOC or HTML. This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. The algorithm automatically classifies the files based on evaluation measures of three methods Entropy, Byte Frequency Distribution and Rate of Change. The ELM algorithm is applied to RABEI-2017 and DFRWS-2006 datasets. The experimental results show that the ELM algorithm is able to identify JPEG files of fragmented clusters with high accuracy rate. The classification accuracy of the RABEI-2017 dataset is 90.15% and the DFRWS-2006 is 93.46%. The DFRWS-2006 has more classes than the RABEI-2017 which improves the ELM classifier fitting.

An Improved Low Contrast Image in Normalization Process for Iris Recognition System

Iris recognition system is one of the most predominant methods used for personal identification in the modern days. Low quality iris image such as low contrast and poor illumination presents a setback for iris recognition as the acceptance or rejection rates of verified user depend solely on the image quality. This paper presents a new method for improving histogram equalization technique to obtained high contrast in normalization process thereby reducing False Rejection Rate (FRR) and False Acceptance Rate (FAR). The proposed technique is developed using C++ and tested using four datasets CASIA, UBIRIS, MMU and ICE 2005. The experimental results show that the proposed technique has an accuracy of 95%, as compared to the existing techniques: CLAHE, AHE, MAHE and HE which have an accuracy of a 93.0, 85.7, 92.8 and 90.71% respectively. Hence it can be concluded that the proposed technique is a better enhancement technique compared to the existing techniques for image enhancement.

A Systematic Redundancy Approach in Watermarking Using Sudoku

Digital watermarking is one of the most important techniques employed to protect digital contents. Copyright information embedded in the digital contents may become undetectable due to compression and additive noise attacks introduced into a watermarked image. A general strategy to overcome such attacks is to embed redundant watermarking to improve the survivability of the watermark. However, current approaches in redundant watermarking is generally not designed in a systematic way. In this paper, a systematic redundancy approach in watermarking using Sudoku is proposed. The approach is based on the property of Sudokus permutation that provide tightly related, redundant copies of watermark pieces discretely distributed to different hiding planes. Using the classic 9X9 Sudoku puzzle, the proposed approach has been implemented and tested with Gaussian, compression, poisson, speckle, low pass filter, high pass filter and contrast attacks using standard images. The result indicates sustained survivability of the watermark under common attacks.

Procedure automation with immediate user notification: A case study

There are various procedures in a university that can be automated with Information and Communication Technology (ICT) such as leave application, room reservation, facility booking and, laboratory or library material application. Adding such “inventory based systems” with an immediate feedback notification loop to the user will enhance the application process and increase user satisfaction. In this paper, we present automation of a stationary request procedure with Short Message Service (SMS) notification. As a case study, we designed and implemented the system at the Faculty of Computer Science and Information Technology (FCSIT), Universiti Tun Hussein Onn Malaysia. The descriptions of the system development process are presented. Essentially, the principle idea of the system can be used as a framework to effectively automate any university or business procedures that requires notification.