Preventing Cyber Attacks using Artificial Intelligence
Exploring Advantages and Challenges of Chatbot Integration in Human-Robot Interaction
Counterfeit Currency Detection using Machine Learning
Artificial Intelligence use in Lung Cancer Screening to Improve Patient Recovery
An Analysis of Various Crypto Coins and their Suitability for Real-Time Applications
Design and Evaluation of Parallel Processing Techniques for 3D Liver Segmentation and Volume Rendering
Ensuring Software Quality in Engineering Environments
New 3D Face Matching Technique for an Automatic 3D Model Based Face Recognition System
Algorithmic Cost Modeling: Statistical Software Engineering Approach
Prevention of DDoS and SQL Injection Attack By Prepared Statement and IP Blocking
A Web Vulnerability Scanner (WVS) is a software tool that assesses the security of web applications by conducting automated penetration tests. It speeds up the process, reduces costs, and eliminates the need for specialized testing engineers. This study evaluates the vulnerability detection capabilities of six WVSs, three commercial scanners, and three open-source scanners. The goal is to identify and mitigate potential security risks before they are exploited by malicious users. The study employed two well-known vulnerable web applications and four relevant metrics, such as detection rate of accuracy, recall, precision, and the ability to detect different vulnerabilities using the Open Web Application Security Project (OWASP) as a reference.
An Intrusion Detection System (IDS) monitors network traffic for suspicious activity and alerts when such an activity is discovered. In this study, the NSL-KDD cup 99 dataset was used to evaluate anomaly detection from intruders. Intrusion Detection System, Distributed Denial of Service (DDoS), Deep Belief Network (DBN), Random Forest, Naïve Bayes, Security Attack, Machine Learning. Pre-processing and normalization processes were performed on the dataset with inadequate, noisy, or duplicate data. A hybrid K-means clustering algorithm is used to combine clusters, which are classified using Deep Belief Networks (DBNs), Random Forest and Naïve Bayes. The study analyzed the dataset based on accuracy, precision, F-score, and false alarm rate, among which the DBN showed better performance than the other two ML algorithms.
Traditional methods of managing residential societies have several limitations, such as a lack of transparency and inefficient communication. This study proposes a web application that can address these limitations by automating tasks, such as improving communication and enhancing transparency. It offers features such as maintenance of payment scheduler, record maintenance dues, complaint management, communication management, notice systems, visitor notifications, and security management. The user interface of the application shows great potential for streamlining society management and fostering efficient communication.
Outcome-Based Education (OBE) is a student-centric approach to education that focuses on the outcomes of student learning. This paper discusses the pedagogy followed for the skill-oriented course Web Application Development using Full Stack Module-1. It emphasizes the front-end design of web applications using HyperText Markup Language (HTML), Cascading Style Sheets (CSS), JavaScript, and jQuery. The criteria for analysis and evaluation were based on the rubrics defined in the course structure according to OBE. The results show that there is an improvement in the students skills from the perspective of industry expectations in terms of communication, presentation, and report writing skills. The findings of this paper it is clear that OBE can be an effective approach to teaching and learning skills-oriented courses. The results also suggest that OBE can help students develop the skills that are necessary to succeed in the workforce.
Computer viruses are malicious computer programs that can affect the working of a computer system, thus affecting important data and files. This study provides an overview of the history of computer viruses, their evolution, and the ways in which they spread and infect systems. It discusses the various security vulnerabilities that viruses exploit, such as software bugs and human errors, and the damage they can cause, such as data loss, system crashes, and identity theft. The study also analyzes various preventive measures that can be taken to minimize the risk of virus infection, such as software updates, firewalls, and anti-virus software. It also discusses the importance of user education and awareness for preventing virus attacks.
