Secure and Selective Geographic Opportunistic Routing Against DoS Attacks

Abstract

WSNs serve as fundamental components for IoT applications to develop smart homes systems alongside traffic monitoring and control of smart grids and environment surveillance capabilities. Security and reliability of data delivery represents a primary requirement in these networks. Network security becomes achievable through the introduction of Secure and Selective Geographic Opportunistic Routing (SelGOR) protocol. The SelGOR security approach utilizes authentication selection with geographic opportunistic routing to create an attack defense against Denial-of-Service (DoS) incidents. The protocol develops a trust model from Statistical State Information (SSI) systems to maximize operational data productivity. SelGOR protects data integrity with automatic intruder detection through an encryption mechanism based on entropy which enables both strong authenticity and low calculations cost. By implementing a distributed verification system one can detect attackers more rapidly and simultaneously prevent duplicate data by using smart routing decision-making.The routing system of SelGOR adds trust capabilities to Mobile Ad Hoc Networks (MANETs) through its trust-based mechanism. The protocol uses node reputation and monitoring results to make route decisions so it chooses routes from trusted sources. Through its combination of geographic opportunistic routing with entropy-driven encryption and statistical trust models and cooperative attacker verification SelGOR delivers complete protection to WSNs against attacks and simultaneous enhancement of energy efficiency along with throughput and end-to-end performance. The system functions well for secure huge-scale IoT smart infrastructure applications through its detection methods.

Introduction

Wireless Sensor Networks (WSNs) in IoT environments are vulnerable to Denial of Service (DoS) attacks due to limited resources and open access. Integrating Selective Authentication with Geographic Opportunistic Routing (GOR) enhances security by authenticating about one-third of nodes, reducing network overhead while maintaining efficient, reliable communication. This approach is effective across various IoT domains such as smart cities, healthcare, agriculture, industry, military, and disaster response, protecting against DoS attacks and conserving energy.

Several intrusion detection systems combining rule-based filtering with machine learning (Decision Tree, SVM, LSTM with fuzzy logic) improve DoS detection accuracy and speed. Additionally, studies on Mobile WSNs (M-WSNs) highlight coverage optimization and node failure recovery through adaptive algorithms balancing mobility, coverage, and connectivity.

The Secure and Selective Authentication Geographic Opportunistic Routing (SSAGOR) protocol authenticates nodes before network access, enabling stable, energy-efficient multipath routing that prolongs network lifetime and ensures reliable data transmission. The routing method dynamically selects nodes based on energy levels and node density, employing cooperative verification to block unauthorized access and maintain network integrity.

Simulation results using NS-2 confirm the Dominant Optimization System (DOS) algorithm's effectiveness in minimizing energy consumption, reducing packet loss, and sustaining high packet delivery ratios under various mobility and traffic conditions. The system extends network operational time by optimizing energy use and routing decisions, showing promising applicability for secure, scalable IoT-based WSNs.

Conclusion

WSNs in IoT operations face DoS attack vulnerability because they have restricted capabilities and open accessibility. Approximately one-third of node authentication in Geographic Opportunistic Routing (GOR) helps maintain secure communication without adding excess overhead to the network. The approach enhances marketplace safety and maintains optimal data transfer operations in IoT-based WSNs.[1], [2], [3]. IOT enhances Wireless Sensor Network (WSN) data collection ability while making both networks more susceptible to Denial of Service attacks.

References

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Copyright

Copyright © 2025 M.V.H. Bhasakara Murthy, Doki Harikrishna, Majji Prasanth Reddy, Battala Purna Chandra, Nabelli Bhargavi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.