The International Journal of Scientific Research in Computing is a peer-reviewed journal dedicated to advancing state of the art research in computer science and related disciplines. Our mission is to promote excellence in scientific research and technological developments.
Editor-In-Chief: Dr. E. Chandra
Editor: Dr. D. Ramyachitra
Volume 7 | Issue 1 | January 2025
IJSRC, published by the Department of Computer Science, Bharathiar University is a peer-reviewed, open access journal dedicated to advancements in computing research and innovation. The mission of our journal is to promote the advancement in computing research and the applications by publishing the original contributions in artificial intelligence and machine learning, blockchain technology, digital forensics and ethical hacking, cloud computing and distributed systems, Internet of Things, digital twins, robotics and automation, digital image processing and remote sensing, data mining, computer networks and communication and emerging computational technologies.
Artificial Intelligence (AI) and Machine Learning (ML) are revolutionary technologies that enable machines to mimic human intelligence and learn from data. AI encompasses a broad range of applications, from speech recognition to decision-making systems, while ML focuses on developing algorithms that improve automatically through experience. There are three main types of ML: supervised, unsupervised, and reinforcement learning, each catering to different types of data-driven problems. Deep learning, a subset of ML, uses artificial neural networks to process complex patterns and make predictions. These technologies are widely used in industries like healthcare, finance, and automation, improving efficiency and accuracy in various tasks. AI-powered systems such as chatbots and virtual assistants enhance user experiences, while predictive analytics helps in areas like stock market forecasting and medical diagnosis.
Cybersecurity is the practice of protecting computer systems, networks, and data from cyber threats, attacks, and unauthorized access. It involves various security measures, including encryption, firewalls, antivirus software, and multi-factor authentication, to safeguard sensitive information. Cyber threats such as malware, phishing, ransomware, and hacking pose significant risks to individuals and organizations. Ethical hacking and penetration testing help identify vulnerabilities and strengthen security systems. With the rise of cloud computing and IoT, cybersecurity has become more critical in preventing data breaches and cybercrimes. Organizations implement security policies and frameworks like ISO 27001 and NIST to ensure data protection and compliance. Cybersecurity professionals work to detect, prevent, and respond to cyberattacks in real time. AI and machine learning are increasingly being used to enhance threat detection and automated response systems .
Data Science is a multidisciplinary field that uses statistics, programming, and machine learning to analyze and interpret complex data. It involves data collection, preprocessing, exploratory analysis, and predictive modeling to derive meaningful insights. Data Analytics, on the other hand, focuses on examining datasets to identify trends, correlations, and patterns, helping businesses make informed decisions. It includes descriptive, diagnostic, predictive, and prescriptive analytics. Data science emphasizes advanced algorithms and AI-driven predictions, while data analytics focuses on understanding historical data and improving decision-making. These fields are widely used in industries like healthcare, finance, marketing, and e-commerce for optimizing operations and customer experience. Ethical concerns like data privacy and bias remain, necessitating responsible data handling.They are expected to significantly influence the future of automation.