The advancement of artificial intelligence (AI) demands significant data and computational
resources that have an adverse impact on the environment. To address this issue, a novel …

It is of great significance to compress neural network models so that they can be deployed
on resource-constrained embedded mobile devices. However, due to the lack of theoretical …

Network traffic anomaly detection is a critical issue in network security. Existing Abnormal
traffic detection methods rely on statistical-based or anomaly-based approaches, and these …

The universal adversarial trigger (UniTrigger) is an extremely destructive attack method,
posing significant threats particularly in the domain of text classification. However, our …

Text-to-image (TTI) models provide huge innovation ability for many industries, while the
content security triggered by them has also attracted wide attention. Considerable research has …

Retrieval-Augmented Generation (RAG) systems enhance Large Language Models (LLMs)
by integrating external knowledge bases. However, this integration introduces a new …

Abnormal traffic detection is a crucial topic in the field of network security. However, existing
methods face many challenges when processing complex high-dimensional traffic data. …

Tasks based on address text are commonly seen in real life, such as location-based services
based on geographic information systems, rapid localization and positioning systems for …

Extractive summarization and generative summarization are the two main ways to generate
summarization.However,previous work treats both of them as two independent subtasks.In …

This paper aims to analyze the security of RIP and IS-IS routing protocols and compare their
performance in the face of common routing attacks. First, this paper introduces the basic …