Authors - Aoudumber Londhe, Ravindra Apare, Parikshit Mahalle, Bhagwati Galande Abstract - Wireless communication technologies, particularly those based on IEEE 802.11, have significantly improved connectivity but remain highly vulnerable to Denial-of-Service (DoS) attacks. These attacks, which exploit protocol weaknesses and resource limitations, can severely disrupt network availability, particularly in mission-critical applications such as healthcare, financial services, and industrial control systems. In this research, we investigate various DoS attack techniques targeting IEEE 802.11 networks, including deauthentication flooding, disassociation attacks, authentication request flooding (AuthRF), association request flooding (AssRF), and cascading DoS attacks.To mitigate these threats, we analyze IEEE 802.11w, which provides management frame protection (MFP), and evaluate its effectiveness under different attack scenarios. The model integrates supervised learning for attack classification, unsupervised learning for detecting novel threats, and reinforcement learning for adaptive mitigation strategies. Additionally, the system incorporates IEEE 802.11w security enhancements and anomaly-based behavior analysis to strengthen network resilience. This study provides a comprehensive review of existing DoS attack mechanisms, explores recent mitigation techniques, and introduces an advanced IDS framework to safeguard IEEE 802.11 networks against sophisticated cyber threats. Finally, the analysis is organized through a survey that evaluates the articles based on publication year, research techniques, performance metrics, toolset and utilized database.
Thursday August 27, 2026 9:30am - 11:30am IST Virtual Room CGOA, India
Authors - Vedant Patel, Vidisha Pradhan, Akshita Kadam Abstract - Blockchain technology is transforming the education sector by offering decentralized, secure, and tamper-proof solutions to many of the inefficiencies in traditional educational systems. This paper explores the role of blockchain in lifelong learning, focusing on how it addresses key challenges such as learner autonomy, credential verification, and the creation of secure, decentralized education ecosystems. Through an examination of current developments and case studies—including Blockcerts, Sony Global Education, and Woolf University—the paper highlights blockchain’s applications in academic data storage, personalized learning pathways, and digital credentialing. Additionally, this study discusses the opportunities blockchain provides for improving transparency and trust in the verification of academic credentials across borders. While the technology presents promising solutions, significant challenges remain, including issues of interoperability, privacy, scalability, and legal frameworks. The paper concludes by outlining unanswered questions and future directions for research, emphasizing the need for standardization, privacy-preserving technologies, and scalable implementations to fully harness the potential of blockchain in lifelong learning.
Authors - Umesh Kumar Pandey, Mamta Santosh Nair, Shikha Gupta Abstract - Start-ups are buzzing word around the world. These start-ups need funding in their early stage with a high risk of failure and violation of the innovator's intellectual property. Any system's prime responsibility is to ensure the fund availability to the start-up and save the innovator's intellectual property since blockchain has become the chief technology in digital crypto-currencies. Bitcoin. Blockchain has become popular in finance, the health sector, social services and many more areas where transactions are recorded among the parties, known or unknown—the critical features of block Chainz. Decentralisation, distribution, immutability, transparency and audit-ability enrich the usability of this technology and increase the trust to use it. Therefore, a system is proposed here to manage start-ups utilising blockchain features. The proposed system ensures that parties to the contract have more confidence and feel safe to grow start-ups in the community and prevent unnecessary conflicts.
Authors - Smrity Dwivedi Abstract - This manuscript has oriented to new generation and new technology used for required resources and terms, which gives wide bandwidth for each and everyone’s perception. For this reason, microwave frequency area eight to 10 GHz has been explored for 5G and also 7 to 20 GHz is being explored for beyond 5G. This is why both possibilities were taken right here. First assessment among hexagonal and triangular structure complete floor were designed with CST microwave studio. Results obtained from those designs are -23.35dB for 7.77dBi benefit and -29.103dB for 7.85dBi gain for hexagonal and triangular systems respectively. For enhancing the advantage, a partial ground has been used for triangular structure and 10.5dBi has been completed at -38.65dB S11 and for 9.0988 GHz frequency. Bandwidth is increased from 0.29 GHz to 0.32 GHz. Everything is simulated and analysed by simulation software. Novelty is the simple structure gives beyond 5G applications.
Authors - A.Punidha, E.Arul, E.Yuvarani, S.Rajasakaran Abstract - Understanding how dark patterns influence user sentiment is crucial for developing ethical and user-friendly digital experiences. This study evaluates the performance of XGBoost and Random Forest in predicting sentiment (negative, neutral, or positive) based on user interactions. The models were assessed using accuracy, precision, recall, and F1-score, with results indicating that XGBoost outperforms Random Forest, achieving an accuracy of 88.4% compared to 85.9%. To enhance interpretability, SHAP (Shapley Additive Explanations) was used to break down model predictions and identify the most in-fluential features. The analysis revealed that "Number of Clicks" and "Time Spent on Page" were the strongest indicators of user sentiment, particularly in detecting frustration associated with dark patterns. The results provide valuable insights into how machine learning models interpret user engagement and emphasize the importance of transparent AI-driven sentiment analysis. By leveraging explainable AI techniques like SHAP, this research contributes to improving trust in sentiment classification models and guiding the development of more user-centric digital interfaces..
Thursday August 27, 2026 9:30am - 11:30am IST Virtual Room CGOA, India
Authors - J. Jeslin Shanthamalar, Prateesh Kumar S, Abishin J, Sindhu Chandra Sekharan, Malar Selvi G Abstract - There is a growing necessity for noninvasive and sophisticated diagnostic capabilities with the ability to very early prediction of skin conditions from the patient. Timely diagnosis is a powerful influence on patient care out comes, access to dermatologists is not, especially in rural. We propose an AI and deep learning model for improving classification of skin diseases in a highly accurate advantageous manner. This model, which follows the architecture of Convolutional Neural Network, trained on a multi-class skin disease images dataset where every image has a label per lesion. Through hyperparameter fine- tuning, the model is optimized to achieve performance from metrics that include accuracy and trade-off accuracy vs. precision/recall. With user-friendly access in mind, the model runs into the app (web or mobile) that supports a friendly diagnostic user interface. Advanced security floor work is taken within designed to reduce the effect of adversarial attacks. Multimodal processing (text, image and speech inputs) improves classification substantially resulting in accurate and robust diagnosis. The platform has been built based on healthcare professionals and patients' input to provide a easy-to-use diagnostic tool. Research to edit the ai applications in dermatology through fewer dataset bias, more human like NLP explainable models, as well as ongoing work for improved security. In the end, this system is what makes skin disease detection accessible and fast via AI- determined aids an inclusivity in healthcare.
Authors - Aravind A R, Archa A S, Gouri S Krishna Abstract - With India rapidly embracing digital transformation, initiatives like UMANG by the government are the means to achieve online public services. Although UMANG offers over 1,750 services of many departments, it has some critical accessibility concerns, particularly for differently-abled citizens. In this study, we evaluate the UMANG website for WCAG 2.2 compliance using a two-stage method: automated checking using AccessibilityChecker.org and user review analysis using Appbot. Findings identify prominent issues of poor ARIA labeling, flawed heading order, inadequate color contrast, and improper focus order as hindrances for assistive technology users. Sentiment analysis also indicates frustration with usability, login failure, and performance. For the improvement of accessibility, the present study has some suggestions that make UMANG equivalent to international standards. By making inclusive design central to e-governance, India can enjoy equal access to fundamental digital services, creating an inclusive digital space.
Authors - Thisura S. Wijesekera, Dinuka R. Wijendra Abstract - Kubernetes has become the leading container orchestration platform due to its powerful scalability features, enabling dynamic resource management and efficient workload handling in cloud-native environments. This review examines Kubernetes scaling mechanisms at both the application and cluster levels, focusing on Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA), and event-driven scaling with KEDA for adaptive application scaling. At the cluster level, Cluster Autoscaler (CA), Karpenter, Cluster Proportional Autoscaler (CPA), and Cluster Proportional Vertical Autoscaler (CPVA) optimize node provisioning and resource allocation. Despite these advancements, challenges persist, including reactive scaling delays, resource fragmentation, inconsistent scaling decisions across multiple autoscalers, and security vulnerabilities like Economic Denial of Sustainability (EDoS) attacks. To address these issues, emerging trends in AI-driven observability, predictive analytics, and unified autoscaling frameworks offer proactive scaling, anomaly detection, and self-healing capabilities. This review synthesizes academic research and industry practices to highlight the current state, challenges, and future directions of Kubernetes scalability, emphasizing the need for intelligent, adaptive, and secure scaling solutions.
Authors - Suruchi Pandey, Hemlata Gaikwad, Yograj Ingale, Neha Sharma Abstract - This article looks at how organisational culture, resource allocation, and decision-making procedures reflect sustainable leadership principles in different settings. A comparative investigation shows that military commanders place a higher priority on mission success and national security than do business executives, who place more emphasis on profitability and shareholder value. Nonetheless, there are similarities between the two fields, including the value of making moral decisions, flexibility in the face of change, and an emphasis on long-term goals. The role of innovation in sustainable leadership is also examined in this article, with particular attention paid to how strategy development and technology support organisational resilience. Additionally, it looks at how sustainable leadership affects worker engagement, emphasising how crucial it is to develop a feeling of dedication and purpose. This article seeks to provide a more comprehensive knowledge of successful leadership techniques by exploring the subtleties of sustainable leadership in business and defence environments. Regardless of the particular difficulties they encounter, executives looking to im-prove the sustainability and resilience of their organisations may gain a great deal of insight from identifying the parallels and variations across these industries.
Authors - G. Ram Sundar, Sindhu Chandra Sekharan, Taruni Mamidipaka, Yoga Sreedhar Reddy Kakanuru, Priyadharshini M Abstract - The traditional sarees in India represent a rich history both culturally and artistically, as their patterns are created from regional influences along with modern fashion. Making sarees requires detailed skill, and traditional techniques are highly laborious and time-consuming. In this research, we have developed Vastra Kalpana, an AI-driven saree design generator that uses generative deep learning models to automate textile pattern creation. Users can now provide voice commands, and they are converted to text prompts by our integrated OpenAI Whisper speech-to-text software, which are then transformed into structured textual descriptions. These descriptions serve as instructions for the Stable Diffusion's high-resolution saree design generator. Our research results suggest that this automated saree design generator is both solution oriented and efficient, proving the generative techniques offer a novel approach for saree design while tackling the challenges of overreliance on handmade designs. This research mainly contributes to the field of fashion design and establishes a framework for future advancements in automated textile pattern generation.
