Section RQ1: How to construct cybersecurity-oriented domain LLMs? summarizes existing LLMs for cybersecurity. Section RQ2: What are the potential applications of LLMs in cybersecurity? details how LLMs can be a
We provide ablation of the effect of blurring in Table 2 which reveals that blurring may indeed be important for our method when applied to images, but importantly also shows that our gain in performance does not only come from blurring because blurring without our algorithm actually hurts ...
Fourth, we demonstrate PAWS's potential effectiveness when applied to patrols in QENP, where PAWS will be deployed. 69 被引用 · 1 笔记 引用 To conserve and protect: examining law enforcement ranger culture and operations in Queen Elizabeth National Park, Uganda William D. Moreto Jan 2013 ...
I expect that any AI applied to checking software for defensive purposes will at best be an excuse to run some “tool” against the software, so anyone responsible can then say “I checked it for problems: The tool said it was OK!” With that excuse they achieve CYA, whether the “tool...
Transfer learning improves the transferability of models between different domains, i.e., a well-trained model can achieve good accuracy when applied to other testing domains. Recently, since adversarial learning, such as generative adversarial networks (GANs), has shown promising results in image ...
A 14-keypoint HRNet-W32 model [22] that was trained on the AI Challenger dataset [28] is then applied to obtain the user’s keypoint pose. In many situations, the model can reliably infer joint positions even for body parts that are largely occluded by each other or the table. For a...
Facial recognition is an artificial intelligence-based technology that, like many other forms of artificial intelligence, suffers from an accuracy deficit.
They review the need for advanced AI-based systems to address these challenges, proposing the use of generative adversarial networks (GANs) and decentralized LLMs for automated adversarial attacks and defenses. This paper also analyzes future trends in cybersecurity, such as intent-based networking ...
On the other hand, once the traffic sensing is done with good design and quality, it is then necessary to focus on designing models to extract useful information for your tasks. Machine learning has been widely applied for a variety of traffic pattern learning tasks, such as driver and ...
This encouraged researchers to make the effort to automatically extract knowledge from visible light images moving, this way, systems complexity from the hardware to the software side. Image processing began then to be applied to the eye image [53] and, since then, a plethora of new methods ...