Aidan Mooney

Noisy Optical Detection of Chaos-Based Watermarks

In this paper we investigate the limits on optical detection of noisy watermarks that use a chaotic function, the logistic difference equation, in the watermark generation scheme. By varying the function seed, different chaotic sequences exhibiting lowpass and highpass characteristics, can be obtained for the same function, offering an added security advantage over watermarks generated using pseudorandom sequences. Watermark Detection is the process of determining whether an image is watermarked with a certain watermark. In this paper, we model and investigate an optical correlator suitable for watermark detection for certain classes of high-pass or low-pass watermarks. Once in the public domain a watermarked image may be subjected to noise and other attacks, deliberate and unintentional. Additionally,an optical correlator system will also be subject to shot noise. The effects of shot noise on optically transmitted watermarks are modeled in this paper and we examine how the watermark detection scheme performs in such situations. We quantify the degree of noise that may be present in the watermark detection scheme in order to obtain reliable detection or rejection of a watermark using an optical-correlator.

Chaos Based Digital Watermarking

Digital watermarking is a technique first described in 1979 which aims to embed extra pieces of information into some cover work for protection. This information is known as a digital watermark and its presence shouldn’t affect the overall quality of the cover work. To date the majority of digital watermarking techniques employ watermarks generated by iterating pseudorandom number generators. These watermarks have been shown to possess white spectrums and have good robustness to common watermark attacks. Watermarks generated using chaotic functions have received increasing interest recently. Numerous chaotic functions have been studied for this process and the generated watermark sequences can be easily controlled in order to create a sequence with particular spectral properties, e.g. lowpass sequence. This chapter will present the field of chaotic digital watermarking and examine three chaotic functions used in chaos based watermarking and show the advantages of using these over the more common pseudorandom ones.

The impact of the theoretical properties of the logistic function on the generation of optically detectable watermarks

A digital watermark is a visible, or preferably invisible, identification code that is permanently embedded in digital media, to prove owner authentication and provide protection for security or defence documents. In this paper, we present an approach for the generation of watermarks using a logistic chaotic function. Using this function, in conjunction with seed management, it is possible to generate chaotic sequences that may be used to create highpass or lowpass digital watermarks. A slight change in the initial conditions will quickly lead to a significant change in the subsequent states of the system, and thus will generate substantially different watermarks. This technique has been shown to offer an added security advantage over the more traditionally generated watermarks created from pseudorandom sequences, in that only the function seed needs to be stored. We have previously presented a study where an optical correlator was suitable for the detection of chaotically generated watermarks. We have also studied the impact of shot noise present in an optical detector for watermarks generated using the logistic function. The logistic function presented in this paper is ill-defined for certain seed values and has not been fully investigated for the purpose of watermark generation. We consider the impact of the theoretical properties of the logistic function on watermark generation and their highpass and lowpass properties, which when embedded in digital media, are suitable for optical detection.

Visual and textual programming languages: a systematic review of the literature

It is well documented and has been the topic of much research as well that Computer Science courses tend to have higher than average drop-out rates at third level, particularly so, for students advancing from first year to second year. This is a problem that needs to be addressed not only with urgency but also with caution. The required number of Computer Science graduates is growing every year, but the number of graduates is not meeting this demand, and one way that this problem can be alleviated is to encourage students, at an early age, towards studying Computer Science courses. This paper presents a systematic literature review that examines the role of visual and textual programming languages when learning to program, particularly as a First Programming Language. The approach is systematic in that a structured search of electronic resources has been conducted, and the results are presented and quantitatively analysed. This study will provide insight into whether or not the current approaches to teaching young learners programming are viable, and examines what we can do to increase the interest and retention of these students as they progress through their education.

Generation and detection of watermarks derived from chaotic functions

A digital watermark is a visible, or preferably invisible, identification code that is permanently embedded in digital media, to prove owner authentication thereby providing a level of document protection. In this paper, we review several approaches for the generation of watermarks using chaotic functions, and in particular, the logistic chaotic function. Using this function, in conjunction with seed management, it is possible to generate chaotic sequences that may be used to create highpass or lowpass digital watermarks. A slight change in the initial conditions will quickly lead to a significant change in the subsequent states of the system, and thus will generate substantially different watermarks. This technique has been shown to offer an added security advantage over the more traditionally generated watermarks created from pseudorandom sequences, in that only the function seed needs to be stored. It also has the advantage that, through examination of the theoretical properties of the function, it is possible to choose seeds that lead to robust, lowpass watermarks. We review various detection techniques including correlation and statistical methods, and present an analysis of the impact of noise present in a model optical detector. The logistic function presented in this paper is ill defined for certain seed values and has not been fully investigated for the purpose of watermark generation. We consider the impact of the theoretical properties of the logistic function for several chaos-based watermark generation techniques, in particular, their highpass and lowpass properties, which when embedded in digital media, are suitable for correlation and statistical based detection methods.