Internet of Drones (IoD) has become increasingly important to support collaborative Unmanned Aerial Vehicles (UAV) services such as logistics, surveillance, and disaster recovery. Yet, current authentication mechanisms for IoD are typically based on static credential models and do not support revocation in real-time, thereby exposing such environments to insider threats, and unauthorized access. In response, in this paper, propose Revocable Lightweight Authentication Protocol (RLAP), a scalable and decentralized authentication which introduces trusted units to identify fellow drones using ephemeral elliptic curve keys and pseudo identifiers. RLAP leverages a Bloom filter based revocation strategy for constant detection of compromised nodes without requiring centralized storage or synchronized clocks. Our protocol has low computational and communication overhead and can achieve stateless mutual authentication. Analysis against the security requirements shows RLAP is secure against impersonation, replay, and verifier compromise, and the experimental results reveal the computational cost of RLAP is reduced by 57% and message size is decreased by more than 60% in comparison to the existing schemes. RLAP is well-suited to safe and adaptive communication on large-scale, resource limited UAV swarms.
Hussein Ali Ghadhban Salman, Najem Aldeen Abdullah Al Hajij, Ola J. Saleh et al.· 2026 6th International Confe...· 0 citations
Cross-functional teams are a central organizational model in contemporary software engineering fueled by practices such as Agile development, DevOps and Continuous Integration/Continuous Deployment (CI/CD). Although widely adopted, there is limited empirical support for the effectiveness of these practices in cross-functional teams. This paper presents evidence based software engineering for improving the performance of cross-functional teams. We propose a structured optimization framework which connects modern software engineering principles to measurable performance incentives. The framework is empirically validated on data from real cross-functional software teams, including delivery, quality and collaboration metrics. We show empirical evidence that we have increased deployment frequency, reduced time to release cycle, decreased defect density, improved recovery efficiency, and enhanced collaboration across teams through data-driven optimization. The results reveal that systematic and sustainable performance improvements are achieved through data driven decision making. The contributions of this paper move along the evidence-based software engineering and propose a theoretical and empirically grounded support for optimizing cross-functional software teams.
M. Qasim, Ali Zamil Sharhan Al-Maliki, Murtadha Al-Maliki et al.· 2026 6th International Confe...· 0 citations
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