Rashidah Funke Olanrewaju

Digital audio watermarking; techniques and applications

Counterfeiting and piracy of intellectual properties are often pointed to as an indispensable problems across the globe, though more intense in some region than others. Currently over millions of digital audio files like digital songs are copied illegally during file-sharing over the networks, costing loss of revenue to the music and broadcasting industries. Right owners such artists, composers, and producers have been searching for ways to protect their creations, discoveries and inventions. These challenges prompted significant research in Digital Watermarking (DW) to develop efficient methods to protect copyright and authentication messages in digital audio in order to prevent forgery and impersonation. This paper brings to view techniques and applications of digital audio watermarking signals. Requirements and Methods of audio watermark were indentified and classified accordingly. A new intelligent audio watermarking technique in a combine domain is proposed to complement the current methods. It is expected that this paper will serve as a launch pad for researchers interested in audio watermarking.

State-of-the-art digital watermarking attacks

Digital watermarking is a huge research area which is progressively growing. It covers theoretical studies, novel techniques, attacks and performance analysis. An embedded watermark may unintentionally or inadvertently be impaired by such processing. Other types of processing may be applied with the explicit goal of hindering watermark reception. In watermarking terminology, an “attack” is any processing that may impair detection of the watermark or communication of the information conveyed by the watermark. Broadly it can be classified as Intentional Attacks and Non-Intentional Attacks. The processed watermarked data is then called “attacked data”. An important aspect of any Watermarking scheme is its robustness against attacks. The notion of robustness is intuitively clear: A watermark is robust if it cannot be impaired without also rendering the attacked data useless. Watermark impairment can be measured by criteria such as miss probability, probability of bit error, or channel capacity. For multimedia, the usefulness of the attacked data can be gauged by considering its perceptual quality or distortion. Hence, robustness can be evaluated by simultaneously considering watermark impairment and the distortion of the attacked data. An attack succeeds in defeating a watermarking scheme if it impairs the watermark beyond acceptable limits while maintaining the perceptual quality of the attacked data. In this paper, JPEG compression (quality 50 and 75), noise (Gaussian noise), distortion (blurring) and contrast enhancement (histogram equalization and intensity adjustment) are testified. Results shown that embedding gain and DWT decomposition subbands were among the contribute against attacks performed.

An Empirical Study of the Evolution of PHP MVC Framework

Commercial, social and educational importance of web technology has tremendously increased research activities in web programming/scripting. Several methods for writing PHP codes such as Object Oriented Programming (OOP), Procedural PHP coding and Model View Controller (MVC) pattern have been proposed. Model View Controller (MVC) which is one of the most powerful method for developing PHP application has many variant such Laravel, Symfony, CodeIgniter, CakePHP etc. However, selection of best MVC framework among the variants is of concern to the programmers as well as project managers, especially when managing big applications. Hence, performance evaluation criterions are required. This paper discusses the MVC based most famous PHP frameworks, evaluate their performance and it was found that Laravel outperforms other MVC framework, hence Laravel is proposed as the most suitable PHP framework for future web technology.

Big Data Analysis Solutions Using MapReduce Framework

Recently, data that generated from variety of sources with massive volumes, high rates, and different data structure, data with these characteristics is called Big Data. Big Data processing and analyzing is a challenge for the current systems because they were designed without Big Data requirements in mind and most of them were built on centralized architecture, which is not suitable for Big Data processing because it results on high processing cost and low processing performance and quality. MapReduce framework was built as a parallel distributed programming model to process such large-scale datasets effectively and efficiently. This paper presents six successful Big Data software analysis solutions implemented on MapReduce framework, describing their datasets structures and how they were implemented, so that it can guide and help other researchers in their own Big Data solutions.

Watermarking in Safe Region of frequency domain using complex-valued Neural Network

It has been discovered by computational experiments that Complex Back-Propagation (CBP) algorithm is well suited for learning complex pattern [1], and it has been reported that this ability can successfully be applied in image processing with complex values. In this paper, a watermarking scheme based on Complex-Valued Neural Network, CVNN trained by CBP in transform domain is proposed. Fast Fourier Transform, FFT is used to obtain the complex values (real and imaginary part) of the host image. The complex values form the input data of CVNN. Neural networks performs best on detection, mapping, classification, learning and adaption. These features are employed to simulate the Safe Region (SR) to embed the watermark, thus, watermark are appropriately mapped to the safe region of selected coefficients. The implementation results have shown that this watermarking algorithm has high level of imperceptibility.

CDR analysis using Big Data technology

Call Detail Records (CDR) is a valuable source of information; it opens new opportunities for telecom industry and maximize its revenues as well as it helps the community to raise its standard of living in many different ways. However, we need to analyze CDRs in order to extract its big value. But CDRs has a huge volume, variety of data and high data rate, while current telecom systems are designed without these issues in mind. CDRs can be seen as Big Data source, and hence, it is applicable to use Big Data technologies (storage, processing and analysis) in CDR analytics. There are considerable research efforts to address the CDR analysis challenges. This paper presents the use of Big Data technology in CDR analysis by giving some CDR analytics based application examples, highlighting their architecture, the utilized Big Data tools and techniques, and the CDR use case scenarios.

A Secure Authentication Scheme for Bluetooth Connection

Recently, Bluetooth technology is widely used by organizations and individuals to provide wireless personal area network (WPAN) because the radio frequency (RF) waves can easily penetrate obstacles and can propagate without direct line-of-sight (LoS). However, there are serious security challenges associated with wireless communication systems since they are easier to eavesdrop, disrupt and jam than the wired systems. Bluetooth technology uses either legacy pairing or secure and simple pairing (SSP), however both are vulnerable to attacks such as eavesdropping and man-in-the-middle (MITM) attacks. Therefore, this paper has proposed a secure protocol that uses a double encryption to identify the slave. The implementation of this proposal is based on the Arduino Integrated Development Environment (IDE) as software and a Bluetooth (BT) Shield connected to an Arduino Uno R3 boards as hardware. The result was verified on a Graphical User Interface (GUI) built in Microsoft Visual Studio 2010. It has shown that the proposed scheme works perfectly and the protocol thwarts the passive and active eavesdropping which exist during SSP. These attacks are defeated by avoiding the exchange of passwords and public keys in plain text. Therefore, this protocol is expected to be implemented by the Bluetooth Specification Interest Group (SIG) to enhance the security in Bluetooth connection.

Robust Image Watermarking Scheme by Discrete Wavelet Transform

This paper proposes a robust digital image watermarking techniques by using discrete wavelet transform. The watermark is embedded in 2-level diagonal coefficient to achieve high performance in term of imperceptibility. The watermark is embedded by selecting a seed that generating pseudorandom noise sequence. Then the Watermark is extracted back by using the same pseudorandom noise sequence seed in the embedding. The experimental results show that the proposed algorithm provides good level of imperceptibility. Moreover, the watermarked image is robust against several attacks.

Mobile Heart Rate Detection System (MoHeRDS) for Early Warning of Potentially-Fatal Heart Diseases

Most health institutes and common hospitals use a continuous cardiac monitoring machine that is immobile, big and heavy, costly and is not equipped with an option to send warnings if there is an alarming change in the patients heart rate. Thus, the purpose of this research is to design and develop a device prototype that detects alarming changes of a persons heart rate and sends a warning immediately via Short Message Service (SMS) to receivers such as doctors, family members, a person in charge, or monitoring system application. The objective is achieved by developing a program for Arduino microcontroller that enables a pulse sensor module to detect alarming changes of a users heart rate through photoplethysmography technique and utilizes a GSM Shield module to act as an SMS interface between the device prototype and receivers. The relevancy of Mobile Heart Rate Detection System (MoHeRDS) device is investigated through a survey that has resulted in positive responses from 70 respondents mainly from the health sector where 100% of them agree that MoHeRDS is relevant and some deem it very relevant to be one of the helping factors for early warning of Potentially-Fatal Heart Diseases (such as heart attacks, heart failures, etc.). Furthermore, MoHeRDS is palm-sized, portable and has a reasonable low cost. Thus, with the implementation of MoHeRDS in the health sectors, individuals with risk of potentially-fatal heart diseases can get immediate treatment hence reducing their death statistics.

RFDA: Reliable framework for data administration based on split-merge policy

Emerging technologies in cloud environment have not only increased its use but also posed some severe issues. These issues can cause considerable harm not only to data storage but also to the large amount of data in distributed file structure which are being used in collaborative sharing. The data sharing technique in the cloud is prone to many flaws and is easily attacked. The conventional cryptographic mechanism is not robust enough to provide a secure authentication. In this paper, we overcome this issue with our proposed Reliable Framework for Data Administration (RFDA) using split-merge policy, developed to enhance data security. The proposed RFDA performs splitting of data in a unique manner using 128 AES encryption key. Different slots of the encrypted key are placed in different places of rack servers of different cloud zones. The effectiveness and efficiency of the proposed system are analyzed using comparative analysis from which it is seen that the proposed system has outperformed the existing and conventional security standard.