Below is a list of my published research papers in the fields of Cryptography, AI, and Data Science.
Lightweight cryptography is an emerging field in the field of research, which endorses algorithms which are best suited for constrained environment. Design metrics like Gate Equivalence (GE), Memory Requirement, Power Consumption, and Throughput play a vital role in the applications like IoT. This paper presents the 6LoWPAN Protocol Stack which is a popular standard of communication for constrained devices
Reference: Khairnar, S., Bansod, G., Dahiphale, V. (2019). Advances in Intelligent Systems and Computing, Springer. DOI | [PDF]
The growth in IoT devices means an ongoing risk of data vulnerability. The transition from centralized ecosystems to decentralized ecosystems is of paramount importance due to security, privacy, and data use concerns. Since the majority of IoT devices will be used by consumers in peer-to-peer applications, a centralized approach raises many issues of trust related to privacy, control, and censorship. Identity and access management lies at the heart of any user-facing system. Blockchain technologies can be leveraged to augment user authority, transparency, and decentralization.
Recommender systems play a crucial role in enhancing user experience and engagement on e-commerce plat-forms by suggesting relevant products based on user behavior. In the context of Amazon’s extensive catalog of over 8,000 magazines spanning more than twenty-five categories, providing personalized magazine subscription recommendations poses a significant challenge. This study addresses the problem of identifying potential future associations between magazine reviewers and products using a graph-based approach.
Reference: Khairnar, S., Bodra, D. (2025). IJACSA 16(7). DOI | [PDF]
The proliferation of resource-constrained devices in the Internet of Things (IoT) has intensified the need for cryptographic algo- rithms that are both secure and efficient. Traditional cryptographic schemes such as AES and RSA, while robust, are often unsuit- able for embedded and low-power devices due to computational and memory demands. This paper presents a comprehensive re- view of lightweight cryptography (LWC), focusing on algorith- mic taxonomy, comparative hardware performance, standardiza- tion initiatives by NIST, and evolving attack countermeasures.
Reference: Khairnar, S., Bodra, D. (2025). IJCA 187(37). DOI | [PDF]
The rise of distributed applications and cloud computing has created a demand for scalable, high-performance key-value storage systems. This paper presents a performance evaluation of three prominent NoSQL key-value stores: Redis, Aerospike, and Dragonfly, using the Yahoo! Cloud Serving Benchmark (YCSB) framework. We conducted extensive experiments across three distinct workload patterns (read-heavy, write-heavy), and balanced while systematically varying client concurrency from 1 to 32 clients. Our evaluation methodology captures both latency, throughput, and memory characteristics under realistic operational conditions, providing insights into the performance trade-offs and scalability behaviour of each system.
Reference: Bodra, D., Khairnar, S. (2025). JORIT 4(2). DOI | [PDF]
Flight delays pose significant challenges to passengers and aviation stakeholders alike, causing not only inconvenience but also substantial economic losses. In this study, we present a machine learning-based approach to predict air traffic delays using real-world flight, airline, and airport datasets. We evaluate multiple regression models including Linear Regression, Lasso, Ridge, Decision Tree, and Random Forest through cross validation, achieving high predictive accuracy, particularly when departure delay is used as a feature.
Reference: Khairnar, S., Bodra, D. (2025). IJBAS 14(4). DOI | [PDF]
The proliferation of Internet of Things (IoT) devices in smart home environments has introduced significant security challenges, particularly for resource-constrained devices operating under strict power and computational limitations. This paper presents NexCrypt, a novel symmetric cryptographic algorithm specifically designed for low-power smart home IoT devices. This solution addresses the critical need for lightweight yet secure encryption that maintains acceptable performance levels while minimizing energy consumption. Through comprehensive analysis, this paper demonstrate that NexCrypt achieves a 34% reduction in gate equivalence (GE) compared to existing lightweight ciphers, requires only 1.2KB of memory, and consumes 23% less power while maintaining throughput rates of 156 Mbps.
Reference: Khairnar, S. (2019). IJERIA 12(1). [PDF]
Cloud computing has emerged as a transformative technology paradigm that fundamentally alters how organizations deploy, manage, and scale their IT infrastructure. This research paper presents a comprehensive analysis of cloud computing adoption patterns, performance metrics, and security challenges in enterprise environments through 2019. Using a mixed-methods approach combining quantitative surveys of 500 enterprise IT decision-makers and qualitative interviews with 25 cloud architects, this study examines the factors driving cloud adoption, performance benchmarks across different service models, and persistent security concerns.
Reference: Khairnar, S. (2018). IJMSEA 12(3). [PDF]
For a full list, visit my Google Scholar profile.