Daily Archives: November 10, 2025

Authors: Aakanksha Raghunath Chaudhari, Sharmistha Sujit Sarkar

Abstract: With the rapid growth of digital communication and online services, network security has become a primary concern for organizations and individuals. Traditional intrusion detection systems (IDS) rely heavily on predefined signatures, making them ineffective against zero-day attacks and unknown threats. To overcome these limitations, AI-based anomaly detection systems have emerged as a powerful approach for identifying unusual patterns in network traffic that may indicate malicious activity. This research introduces NetGuard, an intelligent system that leverages machine learning and deep learning techniques to detect anomalies in network traffic. The system provides real-time threat detection, reduces false alarms, and enhances network resilience against evolving cyber threats.

DOI: https://doi.org/10.5281/zenodo.17570618

 

Published by: vikaspatanker

Authors: Aryan Bhatt, Aryan Verma

Abstract: Artificial Intelligence (AI) methods, specifically Large Language Models (LLMs), are increasingly being employed by developers and students to produce source code. Though helpful, such AI-produced code is problematic in terms of plagiarism, originality, and academic honesty. Hence, differentiating between code written by humans and code generated by AI has become vital for the prevention of plagiarism. This article provides an empirical evaluation of current AI detection tools to determine how well they can detect AI-generated code in educational and coding environments. The findings indicate that most of the tools are ineffective and not generalizable enough to be useful for detecting plagiarism. In order to deal with this problem, we suggest a number of solutions, such as fine-tuning LLMs and machine learning-based classification based on static code metrics and code embeddings obtained from Abstract Syntax Trees (AST). Our top-performing model outperforms current detectors (e.g., GPTSniffer) and gets an F1 score of 82.55. In addition to that, we carry out an ablation study to study the contribution of different source code features to detection accuracy.

DOI:

 

Published by: vikaspatanker

Authors: Morziul Haque, 2Mohammed Shaik Fahad, Ansh Goyal, Bhagyashree .N. Singh, Priyanka Sahu, Dr. Basavaraj Neelur, Deepak Kumar Punna, Lavanya Dahiya

Abstract: In 1977, NASA launched two identical spacecrafts known as Voyager 1 and 2, which is the most important ambassador of mankind to the universe. Voyager as a project which was originally intended to be a planetary exploration mission, transformed into a historic project which incorporated both scientific, engineering and humanistic goals. Throughout a period of close to five decades, the Voyagers have unrelentingly provided deliveries in terms of firsts in regard to the outer planets, the heliosphere and the interstellar medium. They are nowadays the well-known stepping-stones of human inquisitiveness and venture beyond the solar frontier. The theory discussed in this paper is a literature review about the current scholarly debate around the issue of the scientific success, the engineering strength, and cultural meaning of the Voyager mission in terms of the 21st century digital era. It also calls attention to modern reinterpretations of Voyager data with these aspects may involve the use of artificial intelligence (AI) and astrophysical modeling, as well as the continued debate surrounding the following, interstellar communication and preservation. Through the lens of both the empirical heritage and with an emphasis on the philosophical influence of the Voyager program, this review explores the mission against the background of 21st century space exploration and human self-understanding.

DOI: https://doi.org/10.5281/zenodo.17568692

 

Published by: vikaspatanker