Indian Daily Diet: Authenticity and Local Diversity
This literature review evaluates the authenticity and local authenticity of the Indian daily diet as it assesses the nature of Indian cuisine based on regional variations, culture, and cooking techniques. Defined as one of the most extensive and diverse cuisines in the world, India's food culture has been connected to geography, politics, history, religion, and socioeconomic conditions. This literature review brings together recent research on regional cuisine changes across India, comparisons and distinctions to cuisine around the world, and traditional cuisine retention to a conclusion that India's food culture is a reflection of life within the nation of India, where unity exists in diversity, but local variations reign true since people can embrace their regional identities while simultaneously sheltered under the Indian identity. Recent studies conclude that Indian food is more than food to eat since it serves a purpose for sociocultural identity, community integration, and traditional storage of information passed down from generation to generation.
Published by: Neil Ashok Nigam
Author: Neil Ashok Nigam
Paper ID: V11I3-1359
Paper Status: published
Published: June 19, 2025
What are the Practical Implications of Self-Defence Laws in India?
This paper explores the practical implications of self-defence laws in India, with a particular focus on their application to women’s safety. It begins by outlining the legal definition and categories of self-defence—physical, verbal, psychological, and cyber—and examines key provisions of the Indian Penal Code (Sections 96–106) that govern the right to private defence. Through a comparative analysis of landmark legal cases, the paper highlights the nuanced boundaries between justified and excessive force, especially in gendered contexts. It then shifts to a real-world application by examining the current landscape of personal safety devices for women in India, identifying gaps in accessibility and effectiveness. Based on this analysis, the paper proposes a multifunctional, low-cost wearable safety bracelet designed for Indian women across socio-economic backgrounds. Ultimately, the study underscores the limitations of legal protection in the absence of awareness and immediate aid, and argues for innovative, preventive approaches to complement existing legal rights.
Published by: Inayat Puri
Author: Inayat Puri
Paper ID: V11I3-1331
Paper Status: published
Published: June 19, 2025
FinTech Transformation and its Disruptive Impact on Traditional Financial Systems
The financial sector is undergoing a profound transformation driven by advancements in financial technology (FinTech). This study undertakes a comprehensive literature review to analyze the extent to which emerging technologies—such as artificial intelligence (AI), machine learning (ML), and big data analytics—are reshaping traditional banking and financial services. By examining key areas of disruption, including peer-to-peer lending, digital banking services, and mobile payment platforms, the research provides insights into the implications of FinTech innovations on legacy banking practices. Furthermore, the paper explores the strategic responses of traditional financial institutions, such as partnerships with FinTech firms and investments in digital transformation, alongside the critical regulatory challenges arising from these developments. The findings reveal a dual impact: FinTech has democratized access to financial services and enhanced operational efficiency, yet it has also introduced regulatory and cybersecurity complexities. The review concludes by emphasizing the importance of regulatory alignment, technological adaptation, and collaborative efforts for sustainable growth in the evolving financial ecosystem.
Published by: Aditya Prakash, Nikita Tanksali
Author: Aditya Prakash
Paper ID: V11I3-1356
Paper Status: published
Published: June 18, 2025
Corporate Security and Safety System
In today's commercial world, corporate security and safety are essential elements. Ensuring the safety of personnel, property, and infrastructure becomes critical as businesses expand and function in more complicated and frequently dangerous contexts. Conventional security solutions, such having employees on the scene and manually monitoring video systems, have limits in terms of their scope and efficacy, particularly when it comes to spotting dangers that change quickly, like fire or firearms. Intelligent surveillance systems that make use of cutting-edge technology like computer vision and machine learning are becoming more and more necessary to overcome these constraints. Significant gains in object detection and real-time monitoring capabilities have been made possible by the latest developments in deep learning. One such innovation is the YOLO (You Only Look Once) algorithm, which is renowned for its high-accuracy real-time object detection capabilities. Because of its single-shot detection technique, YOLO can quickly and effectively identify objects in photos or video streams, which makes it a great option for applications that demand quick decision-making and high processing efficiency. The creation of an automated corporate safety system that uses the YOLO algorithm to detect fire and weapons is the idea put forth in this paper. Organizations can enhance security and fire safety measures by automating the identification of weapons, knives, and fire-related threats in corporate environments by incorporating YOLO.
Published by: Thayalaraj K, Vijaya Lakshmi S, Ponneela Vignesh R
Author: Thayalaraj K
Paper ID: V11I3-1347
Paper Status: published
Published: June 14, 2025
Combining Machine Learning and Cryptography for Privacy-Focused Malicious URL Detection
Online safety is frequently and seriously at risk from malicious URLs and websites. Naturally, search engines are the cornerstone of information management. However, our users are now seriously at risk due to the widespread presence of bogus websites on search engines. The majority of methods used today to identify rogue websites focus on a specific attack. Online safety is frequently and seriously at risk from malicious URLs and websites. Naturally, search engines are the cornerstone of information management. However, our users are seriously at risk due to the rise of bogus websites on search engines. The majority of methods used today to identify rogue websites focus on a specific attack. However, a lot of websites remain unaffected by the widely accessible blacklist-based browser add-ons. Any data leaving the client side must be properly disguised, as the server cannot infer any meaningful information from the masked data. Here, the recommended initial Privacy-Preserving Safe Browsing (PPSB) service is given. Robust security assurances are given, which the existing SB services do not offer. The suggested method uses blacklist storage to identify malicious URL access. SVM classification was used to classify the user-provided input URL. SVM is a class of machine learning algorithms that reliably determines the safety or riskiness of a URL. Specifically, it retains the ability to identify malicious URLs while protecting the user's privacy, browsing history, and proprietary data of the blacklist provider (the list of dangerous URLs). This paper presented a technique that encrypts critical data to safeguard user privacy from outside analysts and service providers. Furthermore, completely supports the functions of chosen aggregates for analysing user behaviour online and guaranteeing differential privacy. The AES encryption method is used to protect user behaviour data online.
Published by: Sridevi S, Thayalaraj K
Author: Sridevi S
Paper ID: V11I3-1311
Paper Status: published
Published: June 14, 2025
Creating Tailored Detection and Prevention Mechanisms for Targeted Threats
In today’s fast-paced world of cybersecurity, standard detection and prevention methods often fall short when it comes to dealing with specific, targeted threats. To truly protect against sophisticated cyberattacks, organizations need to create solutions that are tailored to their unique risks and threat profiles. This means understanding the types of potential attackers, analyzing threats specific to their industry, and implementing detection and prevention strategies that fit the organization’s systems, data, and daily operations. By focusing on detecting targeted threats, using advanced analytics, and continuously improving defenses based on real-time intelligence, organizations can stay ahead of emerging risks. This proactive approach helps minimize vulnerabilities and strengthen overall security, ensuring the organization is always one step ahead of potential attackers.
Published by: Poongodi R K, Thirumoorthi C, Mohamed ibrahim H, Jaysankar P, Aldan Jeri M
Author: Poongodi R K
Paper ID: V11I1-1494
Paper Status: published
Published: June 11, 2025
