A Customizable Decision-Tree Driven Toolkit for Ethical Network Security Testing
Developing an Avatar Generator and Secure Storage using AI
An Analysis of the Harassment and Bullying of Adolescents on Social Media in Madras University, Chennai
Secure File Sharing System Using Advanced Cryptography”
The Future of Fiat Currencies: Insights from Cryptocurrency Adoption
Enhancing Cyber Security in Health Care Industry by using ISO 27001 Accreditation
Survey on the Role of Artificial Intelligence in Cyber Security
An Extensive Overview on Dark Web
A Study of Cybercrime and Cybersecurity
A Growth of Artificial Intelligence in Crime Detection usages in Law Enforcement
Exploring Natural Language Processing Chatbots and Phishing Website Detection: A Literature Perspective
Digital Arrest in India: Driven Cybersecurity for National Digital Security
An Analysis of the Harassment and Bullying of Adolescents on Social Media in Madras University, Chennai
A Dual-Layer Approach for Image and Data Encryption using Logistic Map using Python
An Extensive Overview on Dark Web
Network security testing is a crucial component of modern cybersecurity practices, enabling organizations to identify and address vulnerabilities before they are exploited. Existing penetration testing frameworks, such as Kali Linux, Metasploit, and Burp Suite, provide powerful tools but typically overwhelm beginners, lack contextual prioritization of vulnerabilities, and fail to adapt to localized environments. To address these challenges, a customizable decision-tree- driven toolkit for ethical network security testing is presented. This toolkit integrates reconnaissance, vulnerability scanning, and controlled exploitation with a decision-tree–based prioritization model. The decision tree evaluates vulnerabilities based on factors such as severity scores, exploit availability, and service criticality, thereby guiding ethical hackers to focus on the most critical risks first. The system also includes ethical safeguards such as activity logging, user confirmation before sensitive tests, and restrictions to controlled virtual environments, ensuring responsible use. Unlike existing frameworks, this approach offers both usability and intelligence, making it particularly valuable in developing contexts where cybersecurity expertise and resources are limited. Results from controlled testing environments demonstrate improvements in accuracy, prioritization efficiency, and reduced false positives. This work contributes a practical, ethical, and intelligent toolkit that advances the practice of network security testing and provides a foundation for further research in AI-assisted ethical hacking.
Integration of artificial intelligence (AI) in digital identity creation has also introduced sophisticated avatar creation and safe storage. This paper presents a new AI-based system for creating personalized avatars with safe storage. The system, in the proposed scenario, utilizes deep learning methods like Generative Adversarial Networks (GANs) and Neural Style Transfer (NST) to create high-quality avatars from user data in terms of face information and body pose based on pose estimation pipelines like OpenPose and MediaPipe. This paper illuminates the uses of AI-empowered avatar generation in gaming, virtual reality, augmented reality, and online secure identity. Utilizing deep learning, encryption, and blockchain technology together, the suggested system provides naturalistic avatar generation and advanced data protection, privacy, and user control. Experimental results indicate the efficacy and scalability of the system with a suggestion for use in mass usage by multiple industries. Future research can then be directed towards enhancing avatar realism, computationally optimizing, and further developing the support for real-time rendering of avatars from dynamic scenes.
This study presented a novel empirical analysis of the harassment and bullying of adolescents on social media, focusing on students at Madras University, Chennai. While cyberbullying was a growing global concern, this research added value by contextualizing the issue within the Indian educational and cultural environment, where limited data currently existed. The study employed a mixed-method approach, integrating qualitative data from interviews and focus group discussions with quantitative analysis using Likert-scale questionnaires administered to 30 adolescents aged 12 to 18. Statistical tools such as chi-square and ANOVA were used to assess the relationships between exposure to cyberbullying and various psychological and academic outcomes. The findings revealed a significant correlation between cyberbullying and increased emotional distress, reduced academic performance, and absenteeism. Notably, the research highlighted institutional gaps such as lack of digital literacy and inadequate school interventions. The study suggested the implementation of structured digital literacy campaigns, school-based mental health services, and peer-led advocacy programs. Future research should expand sample sizes and include longitudinal designs to assess the long-term impact of cyberbullying on adolescent development and educational attainment.
Using post-quantum encryption, asymmetric and symmetric cryptography, and digital signatures, this study offers a sophisticated cryptographic file-sharing system that guarantees data integrity, confidentiality, and authenticity. Elliptic Curve Digital Signature Algorithm (ECDSA) for authentication, Advanced Encryption Standard (AES) for file encryption, and Kyber for key generation and exchange are all integrated into the suggested system. Furthermore, three-factor authentication (3FA) including password, OTP verification and face recognization is used to improve system security during login. The solution is suitable for both personal and business file- sharing applications since experimental results demonstrate how well it reduces security flaws while preserving performance.
In an era where the global financial system stands at a critical juncture, marked by the rapid rise of cryptocurrencies, this paper explores their implications for the traditional dominance of fiat currencies. Utilizing a distinctive approach that diverges from traditional literature reviews and conventional research methodologies, it focuses on case studies and direct observations to gather insights into the evolving interplay between these two monetary paradigms. It critically examines how the swift adoption of decentralized digital currencies is reshaping perceptions of value, trust, and control within global finance. By analysing contemporary developments, it investigates crucial issues such as market volatility, regulatory responses, and the growing significance of central bank digital currencies (CBDCs) as a new hybrid financial model. Additionally, it investigates whether cryptocurrencies represent a systemic threat to established fiat regimes or serve instead as a catalyst for financial innovation and inclusion. Through this comparative analysis, it posits that, despite their ideological and structural disparities, fiat currencies and cryptocurrencies are not inherently destined for mutual exclusivity. Rather, the future of money appears to be characterized by a coexistence model, shaped by regional realities, technological advancements, and the evolution of policy frameworks. By taking this innovative approach, this study enriches the broader discourse on the transformation of monetary systems in the digital age, providing essential insights that reflect the complexities and potential pathways of future financial landscapes.
