IoT applications are increasingly common, yet they often rely on expensive, externally managed authentication services. This paper introduces a novel, self-contained authentication method for IoT applications which leverages fog computing principles to lower operational costs and infrastructure complexity. The proposed system, fogauth, combines device serial numbers with cryptographically generated UUIDs to establish secure identification without third-party services. A static cloud-side architecture coupled with a lightweight, locally hosted API enables secure authentication through object-storage operations. Performance testing demonstrates comparable security performance to commercial cloud-based authentication while reducing long-term operational costs and maintaining latency at below 2 minutes in production conditions. fogauth provides a scalable and economically viable alternative for companies seeking to reduce cloud dependency and minimize long-term costs associated with IoT application security. To support reproducibility, a complete open-source implementation and validation dataset are provided, allowing independent replication and extension of the system.

This paper proposes a parameter free dynamics framework that provides a full explanation for observed stellar movement within galaxies. It follows a didactic pattern starting with observations at small scale and moves upwards into galactic rotation speeds. A comparison with Classic Newtonian Dynamics serves to establish its status as a generalisation of Newton's theories. A simple falsifiability experiment is proposed for testing by the scientific community. Finally, some questions are posed for further discussion.

This paper presents the first large scale validation of the Enhanced Newtonian Dynamics framework to the Spitzer Photometry and Accurate Rotation Curves (SPARC) dataset. Unlike traditional models that rely on adjustable free parameters or dark matter halos, END derives gravitational attraction solely from the local density distribution and geometric shape of the galaxy. To accommodate the complexity of real-world data, we developed a hybrid optimisation strategy combining gradient descent with an interval search algorithm. This method enables the robust fitting of multi-component models, where galaxies are decomposed into overlapping oblate spheroids to capture intricate density profiles. After applying strict accuracy filters to the SPARC catalog, we demonstrate that END successfully reproduces the rotation curves of 39 disk galaxies across varying morphological types. Our results confirm that a parameter-free, density-driven approach is sufficient to model galactic dynamics without invoking non-baryonic matter.

The study of galactic dynamics remains fragmented across three competing paradigms—Dark Matter ($\Lambda CDM$), Modified Newtonian Dynamics (MOND), and Yukawa-type modifications. This work relies on Enhanced Newtonian Dynamics (END), a parameter-free gravitational framework that derives rotational velocities exclusively from observable baryonic mass distributions and geometric configurations. Applying END to 39 high-quality galaxies from the SPARC database via a three-oblate spheroid composite model (core, bulge, and disc), we achieve mean velocity errors below 3% for 71.79% of the sample, with a median ${\chi }^2=1.77$. The fundamental END relation, $M{T}^2=\kappa V$ (where $\kappa \approx 1.4121\times {10}^{11}{\displaystyle \frac{\mathrm{kg}}{{\mathrm{m}}^3}}{\mathrm{s}}^2$), successfully reproduces observed rotation curves without invoking non-baryonic dark matter haloes or modified gravity interpolation functions. Notable exceptions (e.g., IC2574, ${\chi }^2=51.56$) arise from geometric mismatches between the assumed exponential decay profiles and the actual density structures of dwarf irregular systems. Classical Newtonian Dynamics, applied to identical mass distributions, accounts for only 20% of observed velocities, suggesting the “missing mass” problem reflects limitations in how gravitational law relates enclosed mass to orbital motion rather than unseen matter. END’s zero-parameter architecture renders it strictly falsifiable, offering a parsimonious alternative to parameter-heavy competing models while requiring future iterations to incorporate adaptive geometric baselines for morphologically diverse galaxies.