Adopting Secure Software Development Practices to Improve Financial Transactions in the Banking Sector
Secure software development practices are believed to be the banking sector's backbone of financial transaction security. This research examines the issues of adoption, effectiveness, and challenges of secure software practices, focusing on their implications for transaction security, customer trust, and regulatory compliance. The data from structured surveys and machine learning analysis using the Random Forest algorithm provided actionable insights. The results reflected that secure coding standards and threat modeling were at the top and had brought the vulnerabilities down a lot, raising the security of financial transactions a notch. Security testing and continuous integration had an important role but were less influential. Organizations adopting these practices extensively reported increased operational efficiency, reduced data breaches, and higher levels of customer trust. However, high costs of implementation, lack of skilled personnel, and integration complexities with legacy systems remain a challenge. Indeed, the performance of the machine learning model was very strong, with 90.7% accuracy, 91.6% precision, and 90.7% recall; thus affirming its strength in prediction. The importance of features further emphasized secure coding and threat modeling. This research has identified that strategic investments in employee training, modern security tools, and infrastructure upgrades are needed to address the implementation challenges. The agenda of future research integrates blockchain and AI with secure practices for enhanced security. The general contribution of the study is that secure software development practices have the potential to transform the security of financial transactions, build customer trust, and facilitate regulatory compliance in the banking industry.
Published by: Rianat Abbas, Rasheed Afolabi, Ifeoma Eleweke, Adetomiwa Adesokan, Ahmed Akinsola, Laticbe Elijah
Author: Rianat Abbas
Paper ID: V11I1-1304
Paper Status: published
Published: February 4, 2025
Tangent Bundles Related to Various Properties of Differential Geometry
The objective of the present article is to investigate the lifts of a Fλ(2ν + 3, 2) -structure and determine its integrability requirements and partial integrability on the tangent bundle. Finally, the third tangent bundle T3M is examined in order to study the extension of a Fλ(2ν+3, 2) -structure.
Published by: Anowar Hussain Sadiyal
Author: Anowar Hussain Sadiyal
Paper ID: V11I1-1210
Paper Status: published
Published: February 3, 2025
Do Early Medications in Cases of ADHD Help Children to Cope with Behavioural Issues?
Diagnoses of Attention Deficit Hyperactivity disease (ADHD), a common neurodevelopmental disease, have increased globally, especially since the 1980s. Until the late 20th century, ADHD was not as often diagnosed in other parts of the world as it is in Western nations like the United States. This study examines how the prevalence of ADHD diagnoses and medication use is rising across a range of demographics, with a particularly noticeable increase seen between 2005 and 2012. The study lists the main causes of ADHD, which include environmental variables, brain damage, prenatal substance exposure, and genetic factors. Although environmental variables including low birth weight and exposure to pollutants certainly play a part, genetics is the primary determinant, with heritability estimates ranging from 70 to 90%. Individuals of all ages are impacted by the wide-ranging effects of ADHD. Among these are increased chances of comorbid ailments like anxiety, depression, sleep disorders, and behavioral problems. Stimulants and other medications are frequently used to treat ADHD, but they can have negative side effects including appetite suppression, sleeplessness, and more severe mental health issues. The fact that people with ADHD are more likely to commit crimes further emphasizes the disorder's wider social and economic effects. ADHD is managed differently over the world; for example, Australia and India have established protocols for diagnosis and therapy. Although pharmacological therapies are frequently employed, non-pharmacological methods including behavioral therapy and cognitive training are becoming more popular due to worries about their long-term effectiveness and potential negative consequences. This essay promotes a comprehensive, tailored strategy for treating ADHD, stressing the significance of addressing the disorder's influencing hereditary and environmental components. This study adds to the continuing discussion about the diagnosis and treatment of ADHD by emphasizing the value of all-encompassing care plans that weigh the advantages and disadvantages of pharmaceutical treatments against non-pharmacological alternatives.
Published by: Falakh Jahid
Author: Falakh Jahid
Paper ID: V11I1-1278
Paper Status: published
Published: February 2, 2025
The Current State of Research into the Efficiency of Distributed Machine Learning Algorithms for Cloud-Based Big Data Analysis
Today, data has become a driving force in nearly every business sector, and cloud computing, alongside artificial intelligence (AI), serves as a critical enabler that enhances business operations and performance. This research focuses on optimizing distributed machine learning (DML) algorithms within cloud environments to efficiently handle and process large datasets. The paper introduces a methodology for improving the performance of DML algorithms by utilizing the computational power and storage capacity of cloud platforms, coupled with parallel processing techniques. The experimental results demonstrate that the proposed approach reduces processing time by 40% and improves model accuracy by 15%, making it highly suitable for big data environments.
Published by: Shubham Malhotra
Author: Shubham Malhotra
Paper ID: V11I1-1269
Paper Status: published
Published: February 2, 2025
The Role of AI Tools like Chatgpt and Copilot in Revolutionizing Software Development and User Experiences
Artificial Intelligence (AI) has now entered organizations as a key driver of change in software engineering and UX design through such tools as the ChatGPT, and CoPilot among others. AI tools give developers incredible efficiency to improve their productivity, automate processes, and offer unique and better user experiences. This paper aims to evaluate the effects of hyping software developments with AI tools such as ChatGPT and CoPilot, the part they play in enhancing users’ experiences, and the complications involved. Some research findings present how these technologies affect Software Engineering practices regarding the future and theoretical questions that come with the gains of these innovations. AI tools are creating new frontiers when applying software engineering techniques. They act as enablers of increased productivity and creativity since they sift through dull, repetitive tasks, allow work in progress to occur in parallel, and provide a framework for development processes that were once limited to the realm of experts. Furthermore, they liberate developers to focus on dreaming and problem-solving as they code while promoting structures that take care of repetitive code writing, generating idiosyncratic documentation in real-time, and providing solutions. However, this transformation is accompanied by obstacles such as; AI call-for-duty dilemmas, issues of data privacy, developers’ overdependence, and skill degradation. This paper aims to explore their use to critically evaluate their usability to redefine paradigms in software development and user experience design. It also brings to the fore the importance of creating ethical guiding principles as well as very sound frameworks for the implementation of AI solutions. Lastly, tools such as ChatGPT and CoPilot represent a clear example of the transition to AI-enabled engineering, as distinct from AI-driven engineering, which marks a new age where the symbiosis of human creativity and artificial brainpower delivers results that have not been seen before.
Published by: Radhakrishnan Arikrishna Perumal
Author: Radhakrishnan Arikrishna Perumal
Paper ID: V11I1-1213
Paper Status: published
Published: February 2, 2025
Nerve Sensitivity Identification by Explainable AI for Diabetic Patients’ Nerve Stress Point: A New Approach
Diabetic neuropathy, a common complication of diabetes, leads to impaired nerve sensitivity, particularly in the feet, resulting in an increased risk of foot ulcers, infections, and amputations. Current diagnostic techniques, often subjective and reliant on invasive procedures, fail to offer early detection of nerve damage, limiting timely interventions. This project leverages Explainable Artificial Intelligence (XAI) to create a diagnostic system aimed at identifying, categorizing, and analyzing foot dynamics and nerve sensitivity in diabetic patients. By utilizing XAI, the proposed system enhances interpretability, offering clinicians a transparent and reliable tool for early diagnosis and personalized treatment. Our solution focuses on capturing foot immersion and image data to assess nerve sensitivity, utilizing a four-point structural analysis to map foot dynamics and detect abnormalities. The system will also address the challenge of false diagnoses by distinguishing diabetic nerve damage from other nerve-related conditions using heat and frequency verification at the foot's nerve endings. The goal is to provide an objective, accurate, and interpretable diagnostic tool that empowers healthcare providers to improve patient outcomes by enabling timely interventions in diabetic neuropathy cases. The use of XAI ensures that the AI models are interpretable and transparent, allowing clinicians to understand the underlying factors influencing the diagnosis. This transparency is critical for clinical adoption, as it builds trust in AI-driven diagnostic systems. By integrating XAI into diabetic neuropathy diagnostics, this project seeks to revolutionize diabetic foot care, enabling more accurate and timely detection of nerve damage, reducing the risk of severe complications, and ultimately improving the quality of life for diabetic patients.
Published by: Chaitanya Jain, Aniruddha Bhaumik, Harsh Bhanushali
Author: Chaitanya Jain
Paper ID: V11I1-1211
Paper Status: published
Published: January 31, 2025
