Smarter IoT Security: Classifying Encrypted Traffic with AI
![A diffusion-based system extracts multi-level features from traffic imagery by progressively introducing noise, then leveraging a U-Net architecture to denoise and identify optimal feature layers-a process refined through [latex]K[/latex]-means clustering for efficient fine-tuning-and ultimately fusing adjacent network layer features to represent both detailed and abstract traffic patterns.](https://arxiv.org/html/2512.21144v1/x2.png)
A new approach leverages the power of diffusion models and large language models to accurately identify network traffic even within the limitations of resource-constrained IoT devices.
![A diffusion-based system extracts multi-level features from traffic imagery by progressively introducing noise, then leveraging a U-Net architecture to denoise and identify optimal feature layers-a process refined through [latex]K[/latex]-means clustering for efficient fine-tuning-and ultimately fusing adjacent network layer features to represent both detailed and abstract traffic patterns.](https://arxiv.org/html/2512.21144v1/x2.png)
A new approach leverages the power of diffusion models and large language models to accurately identify network traffic even within the limitations of resource-constrained IoT devices.

With all the potential to be a great follow-up to the already strong TRON: Legacy, TRON: Ares unfortunately stumbled. The biggest issue? The absence of TRON himself. While he wasn’t the central figure after the first movie, he still played a significant part in Legacy. Now, with TRON: Ares underperforming in theaters, it’s obvious that including the character the series is named after might have made a real difference.
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The villains in Avatar: The Way of Water were compelling and complex, especially Colonel Miles Quaritch and Varang. However, I’m really interested to find out more about the major villain hinted at in Avatar 4 and 5.

A fascinating detail about Walter White’s transformation was his tendency to adopt the mannerisms of those he killed. It’s unclear if this was intentional, a subconscious process, or simply a coincidence, but it’s a striking pattern. Looking back at the series, this subtle habit reveals a lot about his character and adds layers to his motivations, allowing for multiple interpretations of his actions.

Despite the overall somber tone of the mining sequences, nothing could have truly prepared viewers for a particularly heartbreaking moment. Several well-loved Dwarf characters from The Hobbit meet tragic ends, appearing as corpses in a scene that remains deeply disturbing for many fans.

A new analysis reveals the Lightning Network maintains surprising resilience over time, even as it becomes increasingly fragmented and concentrated in its structure.

This is positive for the gaming world, but to truly understand where games are headed, it’s helpful to remember their history. In 2026, popular titles like Firewatch and Overwatch will mark their ten-year anniversaries, having first launched in 2016.
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![A reinforcement learning system leverages an LSTM-modeled magnetic catheter-where state is defined by tip position [latex]X_{t},Y_{t}[/latex] and goal [latex]X_{g},Y_{g}[/latex]-to train an agent, employing either a Deep Q-Network or TD3, to select angular increments [latex]\Delta\theta_{1},\,\Delta\theta_{3}[/latex]-with [latex]\Delta\theta_{2}=\Delta\theta_{1}[/latex] due to coupling-and optimize a reward function balancing goal proximity with control effort, effectively establishing closed-loop control of the catheter’s tip.](https://arxiv.org/html/2512.21063v1/Overview2.png)
Researchers are leveraging the power of artificial intelligence to achieve unprecedented precision in navigating magnetically steered catheters within the body.