Threat Scoring Model Basis Hybrid Attack Emulation
In today's world, as the globe moves towards the Metaverse, all commercial and business transactions are digitalised, and digital transformation is the new need of the hour owing to COVID and other environmental and health problems. On the one hand, digitalisation is transforming the world; on the other, with an expanding attack surface and a variety of attacker modus operandi, it is critical and long overdue to develop a threat classification model that can provide clear insight into adversaries through their appropriate classification and threat scoring. The research aims to emulate “Threat Scoring based on the Hybrid Attack Model”, which consists of Red Teaming, Attack vectors and Threat Hunting models. The model will be simulated to understand the threat landscape for potential trigger points in the network and operation by initiating a wide range of attacks at various levels with respect to security posture. Hypothesis of results based on attack vectors will be mapped with Threat Intel received from various open Threat Scoring models based on analysis of adversities. The threat modelling process will be based on the MITRE & ATTACK Framework, with discovered threats further classified according to MITRE Tactics, Techniques and Procedures.
Published by: Mukul Kulshrestha, Satish Salunkhe, Dr Vaishali Khairnar
Author: Mukul Kulshrestha
Paper ID: V11I1-1390
Paper Status: published
Published: February 27, 2025
A Review of Artificial Intelligence in Diabetic Retinopathy Detection
Diabetic retinopathy (DR) alongside diabetes is rising among the population twenty-first century and is one of the leading sight threatening cause worldwide. With early treatment in the initial stage possible, detecting the problem before it worsens is important. Different methods of eye evaluation for the changes in retina are mainly hospital based and not accessible to rural remote areas. AI methods can aid the process and provide warnings beforehand in places with inaccessible or poor health facilities. In this review, we discuss four applications - IDx- DR, Eye Art, RetinaLyze, and Bosch DR Algorithm - that are in use in real-world or under study for screening retinopathy.
Published by: Aryan Raj Pradhan
Author: Aryan Raj Pradhan
Paper ID: V11I1-1382
Paper Status: published
Published: February 27, 2025
Enhancing Solar PV Plant Performance with Digital Twins: Leveraging Data Science and AI for Real-Time Analysis.
As solar power continues to be a crucial element of the global shift towards renewable energy, improving the performance of solar power plants becomes important. Various sensors installed on solar panels, inverters, and other equipment produce data, which is then integrated to create a virtual model, the digital twin, that reflects the solar power plant’s operational behavior. For precise representation and control, the system dynamically models the actions of the plant by integrating MATLAB-simulink simulations. Furthermore, fault detection is achieved using Neural Networks, Adaboost, Naïve Bayes, and Decision Trees. This unification of AI-based Digital Twins with energy generation prediction and forecasting, fault detection, and corrective maintenance technologies amplifies solar power plants' operational efficiency, reliability, and sustainability.
Published by: Tanmay Mane, Arpita Kulkarni, Anurhuta Kulkarni, Omkar Shrotri, Dr. Sinu Nambiar, Prof. Sonali Potadar
Author: Tanmay Mane
Paper ID: V11I1-1394
Paper Status: published
Published: February 27, 2025
Gig Labor Market Dynamics – A Case Study on Challenges of Gig Economy in Tamil Nadu
The gig economy is a marketplace where individuals take temporary/contingent jobs at organisations or work as freelancers. It is a booming sector but has remained an unregulated space on a larger scale. Given the nature of their role, they do not maintain a stable relationship with their clients and management and are always open to risk. With the rise of internet users and city growth via investment and urbanisation, Gig workers and their services have become a crucial part of our rapid lives. With the amount of effort, risks, and complexities the Gig workers face in their day-to-day operations, their plight must be considered. In this study, we are focused on understanding and highlighting the challenges of Gig workers. We are trying to work towards addressing an enduring version of the Gig economy, which can help its participant maintain a primary source of income from their gigs. It requires the digital infrastructure, standardized policies, legislations, and corporate work structure to be improved to create space and viability for this growing sector. The research will collect data on real-time Gig workers by understanding their experiences, challenges, social-security requirements, and technological assistance in operations. It is necessary to build on the available secondary data by identifying the areas for improvement in this sector. The study is looking for a scope for improvement in the current framework to result in an environment where the gig economy can thrive and become a perennial source of employment.
Published by: Shikhar Sinha, Rashi K
Author: Shikhar Sinha
Paper ID: V11I1-1392
Paper Status: published
Published: February 27, 2025
Noise Pollution and its Impact on the Environment
The fact we live in advanced and industrialized societies, or progress and industrialization, although these advances have led to the well-being of human beings, they have also caused a series of problems, such as water, air, and soil pollution. We can also say that the pollution of air, soil, and water has a direct or indirect adverse effect on humans or other creatures, which means that if the air, soil, or water is polluted, it will cause various diseases, but if the air If the water and soil are smooth and in their natural state, the damage that is caused by the effect of so much pollution on the creatures will never be faced. Here we are discussing a part of air pollution which is noise pollution, which governments noticed in the past, but with the development of industry and the creation of efficient means of social life, this issue has attracted a lot of attention from governments. And the governments have tried nationally and internationally to limit this phenomenon. In this research, we were reminded about pollution, air pollution and noise pollution, noise pollution, problems and diseases that arise from noise pollution, and the purpose of this research is to provide better conditions for life and evaluate noise pollution, as well as the national rules and The international convention that was created by governments or international organizations to prevent noise pollution, noise pollution that has direct and indirect effects on the environment and human health should be taken into consideration. As a result, noise pollution is considered a serious problem for humanity and other species of this land, even though governments and international organizations have worked to regulate this phenomenon to some extent, they have created rules and principles, but until these principles and rules are not implemented seriously, creating rules will be a waste of time.
Published by: Masouda Ahmadabadi
Author: Masouda Ahmadabadi
Paper ID: V11I1-1404
Paper Status: published
Published: February 27, 2025
Review, Tutorials and Introduction to Cloud Platforms for Agentic GenAI: A Comparative Studies
This paper presents a comparative analysis of leading cloud platforms for Generative AI applications. We evaluate performance, scalability, cost, and ecosystem support for AI workloads. The rapid evolution of generative artificial intelligence (AI) has significantly increased the demand for scalable and robust cloud infrastructure. This paper presents a comparative analysis of major cloud platforms, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), focusing on their capabilities to support generative AI applications. We examine key aspects such as infrastructure scalability, cost efficiency, and the availability of specialized AI services. Furthermore, we discuss the importance of well-architected frameworks and best practices for deploying scalable AI solutions. The paper also explores the strategic collaborations and advancements in supercomputing infrastructure that are driving the future of generative AI. Generative AI (GenAI) is rapidly transforming various industries, demanding scalable and cost-effective infrastructure. Cloud platforms like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI) are vying to provide the necessary tools and services. This literature review examines recent publications and articles discussing the capabilities, architectures, and cost considerations of these platforms in the context of GenAI application development and deployment. We categorize these resources based on their focus: (1) comparative analyses of cloud platforms, (2) GenAI infrastructure and application development, (3) Retrieval-Augmented Generation (RAG) solutions, and (4) scalability and cost optimization strategies. This review aims to provide a comprehensive overview of the current state of GenAI in the cloud, highlighting the strengths and weaknesses of each platform and identifying key trends and challenges.
Published by: Satyadhar Joshi
Author: Satyadhar Joshi
Paper ID: V11I1-1395
Paper Status: published
Published: February 25, 2025
