Authors - Vedansh Verdia, Upesh Patel, Trushit Upadhyaya Abstract - In this paper, we take a look into the world of communication protocols from the ones we've relied on for years like the Ethernet, to newer technologies made just for the Internet of Things (IoT), and even those that are just starting to emerge. As our need for faster, more reliable, secure, and energy-efficient communication keeps growing, these protocols have continued to evolve. We look at how they work, what they're built on, and how well they perform in real-world situations. Along the way, we break down their strengths, their drawbacks, and where they’re best used. Our review spans a broad spectrum—from classic wired systems to wireless options like Wi-Fi and cellular networks, as well as industrial communication setups and cutting-edge technologies like Time-Sensitive Networking. We break down how these protocols compare in terms of speed, ease of implementation, and security, helping readers understand which ones are best suited for different needs and situations. Finally, we talk about the big questions researchers are still trying to answer, and where things might be headed especially when it comes to making systems smarter, more unified, and ready for future challenges like quantum-safe communication. This paper is meant to be a helpful guide for anyone researchers, engineers, or tech enthusiasts—trying to make sense of today’s complex communication landscape.
Authors - Vikas Sihag, Kanika Panwar Abstract - Predictive analytics is reshaping crime mapping and policing by leveraging tools like GIS, machine learning, and big data. This paper reviews current techniques and real-world applications, highlighting their potential to identify crime hotspots and inform proactive strategies. It also examines key challenges, including biased data, ethical concerns, and privacy risks. Through case studies analysis and literature review, the research outlines the limitations of existing systems. The study stresses the importance of fairness, transparency, and accountability. Furthermore, the paper presents a current state of challenges and solutions advocated in research, thus supporting responsible and effective crime prevention practices.
Authors - Moses Moyo, Hanifa Abdullah Abstract - This scoping review was conducted to have an overview of how Artificial Intelligence (AI) influenced cybersecurity posture in South African small and medium enterprises (SMES) utilizing cloud computing technologies. The study extract 57 articles from six electronic databases. After rigorous screen, only eighteen studies were eligible for analysis. Of the eighteen remaining studies, eight were empirical and ten desktops. A qualitative thematic approach was used to extract relevant data from the study to understand the current state of cyberse-curity in SMEs. The study found that South African SMEs were using AI but did not harness opportunities it can offer in cybersecurity. The level of cybersecurity among the SMEs was very low due to lack of proper knowledge about threats that AI technologies could bring about if used by criminals. The study concluded SMEs were poorly prepared for AI use in general and in cybersecurity. The study was limited due to lack of literature related to the research questions. Therefore, it is recommended that a longitudinal empirical study be conducted with South African SMEs to have deeper understanding standing of how the adoption of AI is influencing their cybersecurity posture.
Authors - Aswathi Mary Varghese, Jisha K Abstract - Digital public infrastructure (DPI) denotes foundational digital systems that serve as essential enablers for delivering digital services at scale across society. It has emerged as a key enabler of innovation in developing countries by reducing systemic entry barriers and fostering an inclusive digital ecosystem. DPI serves as a vital connective tissue within the digital ecosystem. Bridging the gap between physical infrastructure—such as internet connectivity, devices, data centers, and the cloud—and a diverse landscape of applications, DPI empowers societies to deploy innovative solutions across sectors like e-commerce, social protection, re-mote education, and telehealth. Real-world illustrations abound: India’s Aadhaar system has revolutionized digital identification, Brazil’s Pix has made fast, real-time payments accessible nationwide, and Australia’s Consumer Data Right is pioneering user-centric data sharing. By enabling dynamic, cross-sectoral innovation, DPI stands as the engine powering the next generation of digital transformation. This paper analyses the evolution and impact of India Stack, focusing on how its layers enable innovation across sectors such as fintech, health, and e-commerce. By mapping the structural features of India Stack against the outcomes in financial inclusion, digital health, and market decentralization, the paper offers a conceptual framework to assess the role of public policy in driving innovation. The findings indicate that when government platforms are built as public goods with interoperable standards and strong institution-al backing, they can create an enabling environment for grassroots and enterprise-level innovation. The India Stack model, while context-specific, holds valuable lessons for other nations seeking to integrate public policy with digital transformation goals.
Authors - Mohammed Hashim Kalam, Guhanathan Poravi Abstract - Time-series data has been increasingly utilized in critical domains making it vulnerable to stealthy adversarial attacks. Explainable AI (XAI) has made major enhancements to model transparency specifically in non-sequential domains (Image, NLP and tabular) but is less researched in time series data due to complexity of temporal dependency in sequential data. This paper systematically reviews around 60 studies published up to June 2025, examining XAI-based approaches for time series, as well as recent XAI extensions tailored for time series data. Various attack types are discussed in terms of their effectiveness, and the performance of recent detection frameworks against these attacks is analyzed, with particular focus on XAI-integrated systems, including SHAP, LIME, LRP, and formal verifications. Despite their usage, most XAI-enhanced approaches, especially those relying on SHAP, face challenges in efficiency and risk explanation instability under noise, with limited evaluation against subtle partial adversarial attacks. While LRP offers computational efficiency vital for high stakes domain real-time detection, its architectural dependency restricts its adaptability across diverse models. This review highlights major unsolved limitations and concludes with prioritizing the need for efficient, robust, temporally aware, and architecture-agnostic frameworks, possibly extending LRP, tailored specifically for time series data.
Authors - Shalini Singh, Amala Siby Abstract - In the last twenty years, efforts have been made to address how financial literacy and inclusion can empower rural women entrepreneurs. However, one essential factor tends to be left behind—the contribution of incubation centers to enabling these women to succeed. This research examines the academic landscape in closer detail through a bibliometric analysis of 2,012 peer-reviewed articles between 2005 and mid-2025 based on the Scopus database. Using tools such as Biblioshiny and VOSviewer, we delve into how the discourse on financial capability, women entrepreneurship, and economic empowerment has progressed throughout time. The research indicates a meteoric increase in interest following 2020, fueled primarily by vulnerabilities uncovered with the COVID-19 pandemic. Despite expansion, however, something is certain: there remains relatively little research linking incubation assistance to rural women directly or financial literacy programs. Our analyses of keywords and co-authorships indicate a splintered discipline with ample space for richer, more holistic research. This article not only charts what is known but also reveals what is lacking, presenting new directions for researchers and policymakers dedicated to building stronger safety nets for rural women entrepreneurs.
Authors - Manupriya P, Rajeshwari.Mattimani, Haripriya G, Hema B, Saroja.V.Siddamal, Vijay H M, Suhas Shirol, Ganga I Abstract - At present, encryption is key to safeguard confidential information from unauthorized access. It means using special algorithms and encryption keys to change readable data into unreadable data. AES is symmetric encryption algorithm adopted by the U.S.Government as a replacement of DES algorithm. AES supports 3-key sizes: 128 bit, 192 bit and 256 bit, with AES -128 being the most commonly used due to its balance of security and performance. Because it is fast and simple, symmetric key encryption which uses a single key for both encryption and decryption, is used in many cases. Advanced Encryption Standard (AES) is a symmetric block cipher that is used extensively in the encryption of electronic data. Out of its various implementations, AES-128 is the most commonly used, with a 128-bit key size and encrypting 128-bit-sized blocks of data and to get 128-bit cipher text. The encryption process goes through 10 rounds of processes like SubBytes, ShiftRows, MixColumns, and AddRoundKey, which are computed to have high confusion and diffusion properties. AES-128 is optimally balanced in terms of security, efficiency, and performance and thus finding use in hardware and software in various industries. Due to its strength and immunity against known attacks on electronic data, passwords etc. AES-128 has been the standard for encrypting data in commercial and government systems worldwide. AES algorithm has many applications such as online banking, ATM machines and military and government communication.
Authors - Anirban Chowdhury, Parul Sachdeva Abstract - This study explores the product-market response to breastfeeding equipment by leveraging user data analytics to evaluate consumer behavior, preferences, and satisfaction. As maternal health awareness grows and parenting practices evolve, breastfeeding products have seen significant innovation in design, functionality, and accessibility. However, market success relies not only on product features but also on understanding real-world user experience and response. The research employs a quantitative method, from user ratings sales metrics to get insights from data collected from amazon.in. Findings reveal key determinants influencing user acceptance, including ergonomic design, portability, ease of use, and aesthetics. The study also identifies gaps between user expectations and product performance that affect repeat purchases despite of product brand. By contextualizing user experience data within broader market trends, the research highlights the role of user-centered design and feedback loops in enhancing product relevance and competitiveness. The outcomes of this study can inform product developers, marketers, and health professionals in creating more effective, user-aligned breastfeeding solutions that support ma- ternal well-being and infant health outcomes.
Authors - I Gusti Ketut Agung Ulupui, Gentiga Muhammad Zairin, Septi Nurmalita, Hera Khairunnia, Dwi Kismayanti Respati, Eka Septariana Puspa Abstract - This study examines the relationship between voluntary risk disclosure and Environmental, Social, and Governance (ESG) performance among Indonesian publicly listed companies. While ESG metrics have become central to investment evaluations, the influence of narrative risk reporting on ESG scores remains unclear, particularly in emerging markets where such disclosures are not standardized. Utilizing content analysis of 2022 annual reports and ESG ratings provided by Sustainalytics through the Indonesia Stock Exchange, this study investigates whether risk disclosure serves as a credible signal of corporate sustainability. The findings reveal that risk disclosure does not significantly influence ESG performance, suggesting that investors and ESG rating agencies may discount voluntary disclosures when they lack precision or strategic alignment. In contrast, firm-specific characteristics, namely profitability (ROA), leverage, and firm size—are positively associated with ESG scores. These results indicate that internal financial and structural factors may offer more reliable indicators of ESG commitment than unregulated disclosure narratives. The study contributes to the ESG literature by questioning the signaling power of voluntary disclosures and highlights the need for stronger disclosure standards in emerging markets to enhance ESG credibility and comparability.
Authors - Devanjan Khuntia, Anirban Chowdhury, Subhra Chakraborty Abstract - Cybercrime poses a significant threat to India’s business environment, disrupting economic ecosystems, revenue growth, innovation, and employee well-being. As digital adoption accelerates, sectors like banking, e-commerce, and manufacturing face escalating vulnerabilities. This study analyses cyber crime’s multifaceted impact, revealing projected losses of ₹20,000 crore in 2025, with banking (₹8,200 crore) and retail (₹5,800 crore) hardest hit. Beyond financial damage, attacks erode trust, delay deliveries (30% of manufacturers), and slow AI/cloud adoption (40%). Intellectual property theft affects 22% of firms, while SMEs struggle with weak defences (73% prioritize cybersecurity). Employees face data breaches (32% via PUPs) and stress (45%). The paper advocates for stronger policies (e.g., enhancing I4C), AI-driven security, and workforce training to build resilience. A holistic approach—combining regulation, public-private collaboration, and awareness—is critical to safeguarding India’s digital economy.
