VOLUME 15, ISSUE 9, SEPTEMBER 2026

Abstract: The field of computing has rapidly evolved from the 1960s into distinct disciplines: Computer Science, Information and Communication Technology. While this diversity enriches the profession, it has also created a problem. The overlapping competencies and blurred boundaries make it difficult for learners to choose appropriate pathways, trainers to impart discipline-specific skills, and employers to interpret graduate profiles. This leads to mismatched expectations, skill gaps, and inefficiencies in the workforce, thus weakening the ability of computing education to meet organizational and societal demands. This study clarifies the uniqueness of each computing discipline, highlighting their philosophies, competencies, and graduate profiles. The study employed a desktop research method, drawing on secondary data from academic publications, professional guidelines, and industry reports. Sources were selected based on credibility, relevance, and recognition by established bodies. The analysis involved systematically reviewing literature to identify recurring themes, disciplinary distinctions, and competency frameworks. Sources were cross-checked for were synthesized by comparing perspectives across disciplines, highlighting overlaps, and distinguishing unique competencies. This triangulated approach ensured that conclusions were both academically robust and practically relevant. By distinguishing these pathways, the study ensures that learners acquire targeted skills aligned with career aspirations, trainers deliver curricula that reflect discipline-specific competencies, and employers can interpret graduate profiles accurately to reduce skill mismatches. Ultimately, society benefits from graduates whose competencies are tailored to solving real-world problems through computing technologies. This study contributes to bridging the gap between education and practice by offering clarity on computing disciplines. It empowers learners to make informed choices, trainers to design effective programs, employers to align talent with organizational needs, and policymakers to strengthen curricula that support national and global development. In doing so, the paper positions computing education as a driver of innovation, efficiency, and societal progress.

Keywords: computing disciplines, computing curriculum pathways, unique competencies, graduate profiles, digital transformation, ICT

Abstract: Phishing URL detection has advanced considerably through machine learning and deep learning, with recent published systems reporting accuracy figures that frequently exceed 95%. However, a close reading of this literature shows that high accuracy is often achieved using large feature sets, deep sequence architectures, or ensembles comprising a dozen or more classifiers — approaches that are difficult to justify on resource-constrained platforms such as browser extensions, mobile applications, or edge gateways, where real-time response and a small memory footprint matter as much as raw detection accuracy. This paper reviews six recent studies on machine-learning-based phishing URL detection, comparing their algorithms, feature counts, and reported accuracy, and identifies a consistent gap: none of the reviewed works measure deployment cost — inference latency, model size, or throughput under concurrent load — alongside their accuracy claims. Building on this analysis, the paper proposes a tentative methodology for a lightweight, scalable, real-time phishing-detection framework that restricts features to those computable from the URL string alone, benchmarks compact classical classifiers against the heavier baselines identified in the review, and treats latency, model size, and throughput as first-class evaluation metrics rather than afterthoughts. The proposed direction is intended to narrow the gap between laboratory-grade accuracy and field-deployable, real-time phishing protection.

Abstract: Now day’s security is an important aspect of life. We require security in every part of communication to transmit our information safely. Here our main aim is to secure the important information hidden in the images, while communicating we are hiding watermark inside the image by using RSA algorithm. To obtain very high image quality we use Fractal color image watermarking. Firstly we encrypt the watermark using RSA and then this encrypted watermark is used to hide inside the image using Fractal color image watermarking. To achieve watermarking we convert RGB into space. Also we are trying to achieve better parameters like PSNR (power signal to noise ratio), BER (Bit error rate) and MSE (Mean square Error).

Keywords: DCT, DWT, HVS, CIE, SCDFT etc