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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Babu R. Dawadi
Tribhuvan University
Computer Science & IT Engineering

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Enhancing IPv6 enabled IoT system security using addressless architecture Ashmita Tiwari; Chitran Pokhrel; Babu R. Dawadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 42, No 2: May 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v42.i2.pp469-484

Abstract

The growth and sensitivity of internet of things (IoT) deployments demand robust and efficient security mechanisms, especially at the addressing layer. Traditional IPv6 addressing is susceptible to scanning, spoofing, and tracking, especially in IPv6 over low-power wireless personal area networks (6LoWPAN) networks. This paper proposes a dynamic elliptic curve cryptography (ECC)-based IPv6 address generation mechanism for 6LoWPAN IoT networks. Encrypting Interface IDs (IIDs) while keeping the network prefix the same to improve security against scanning, inference, and correlation attacks. High entropy of 0.9836 and cryptanalysis confirm higher randomness and high resistance to wide vectors of attacks. Having computed an average delay of encryption as 2.5728 ms, the process ensures low latency and insignificant overhead. It is more secure and efficient than existing techniques and hence is ideal for real-time resource- constrained IoT applications.
A transfer learning-based approach for automatic monument detection Santosh Giri; Jebish Purbey; Sunil Adhikari; Paarit Pokharel; Babu R. Dawadi; Bipun Man Pati; Atsushi Ito; Sushant Chalise; Sanjivan Satyal
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i4.pp3326-3341

Abstract

Architectural heritage connects us to the cultural achievements of past civilizations. Patan Durbar Square in Nepal is home to many such structures, yet identifying them remains a challenge for tourists. This paper presents an automated monument recognition system built on the backbone of convolutional neural networks (CNNs). A dataset of 1832 images of 9 important monuments from Patan was created, and build a detection system with MobileNetV2, a light-weight CNN, to detect monuments in Patan Durbar Square with a near-perfect F1 score of 98.94%. The approach utilizes transfer learning to adapt the model to local architectural styles. A detailed ablation study is performed to determine the optimal network design and augmentation strategies. Class-wise performance is further analyzed to verify robustness against visual occlusion and similarity. Finally, the model is deployed as a mobile application using Flutter and the FastAPI framework. This work demonstrates the viability of lightweight CNNs for real-time cultural heritage preservation.
Co-Authors Ashmita Tiwari Atsushi Ito Bipun Man Pati Chitran Pokhrel Jebish Purbey Paarit Pokharel Sanjivan Satyal Santosh Giri Sunil Adhikari Sushant Chalise