By synergizing external knowledge with generative capabilities, RAG is emerging as an important approach for enhancing the professionalism and reliability of Large Language Models (LLMs). However, due to the difficulty of fully ensuring the reliability of external knowledge sources, RAG systems are vulnerable to data poisoning attacks. Existing poisoning attacks are typically designed for a single specific query, exhibiting limited generalization capability. In addition, existing methods craft poisoned texts with low retrieval probability, leading to limited attack effectiveness. What is more, they also suffer from inefficiency in poisoned text construction. In this paper, we propose AutoTPA, a novel RAG poisoning attack, which targets all user queries containing the specific trigger. AutoTPA integrates dynamic query clustering, efficient and minimal candidate token set construction, as well as heuristic token evaluation algorithm, enabling automated and efficient construction of effective poisoned texts. All the attacker has to do is to determine the trigger to attack. Extensive experimental results demonstrate that AutoTPA achieves an attack success rate up to 95.5 % in less time while using only a token set sized at about 3.5 % of the original vocabulary. It significantly outperforms existing methods, showing clear advantages in both efficiency and effectiveness.

Neuroscience research indicates that the interaction among different functional regions of the brain plays a crucial role in driving various cognitive tasks. Existing studies have primarily focused on constructing either local or global functional connectivity maps within the brain, often lacking an adaptive approach to fuse functional brain regions and explore latent relationships between localization during different cognitive tasks. This paper introduces a novel approach called the Local-Ascending-Global Learning Strategy (LAG) to uncover higher-level latent topological patterns among functional brain regions. The strategy initiates from the local connectivity of individual brain functional regions and develops a K-Level Self-Adaptive Ascending Network (SALK) to dynamically capture strong connectivity patterns among brain regions during different cognitive tasks. Through the step-by-step fusion of brain regions, this approach captures higher-level latent patterns, shedding light on the progressively adaptive fusion of various brain functional regions under different cognitive tasks. Notably, this study represents the first exploration of higher-level latent patterns through progressively adaptive fusion of diverse brain functional regions under different cognitive tasks. The proposed LAG strategy is validated using datasets related to fatigue (SEED-VIG), emotion (SEED-IV), and motor imagery (BCI_C_IV_2a). The results demonstrate the generalizability of LAG, achieving satisfactory outcomes in independent-subject experiments across all three datasets. This suggests that LAG effectively characterizes higher-level latent patterns associated with different cognitive tasks, presenting a novel approach to understanding brain patterns in varying cognitive contexts.

Abstract Cooperative communication can improve the performance of communication system under multi‐path fading conditions by relaying. If there is an eavesdropper in communication system, the secrecy capacity of the system will decrease. Sending artificial noise can enhance the secrecy capacity of communication system. A novel scheme combining relay selection with artificial noise for amplify‐and‐forward cooperative communication system in the presence of an eavesdropper is designed, which seeks the relay with the highest signal‐to‐noise ratio. The location of optimal relay node is found out in this scheme by the relay selection scheme based on distance. However, there is not always a relay node at the optimal location. If there is no relay at the optimal location, then the suboptimal relay node can be found out by drawing circles centered on the optimal location. After that, the optimal relay forwards the signals and sends the artificial noise in the null space of the legitimate channel to confuse the eavesdropper. A close‐form expression for maximizing the secrecy capacity is derived, and it is used as the objective function to select the optimal or suboptimal relay node. The algorithm complexity of the relay selection scheme based on distance is lower than that of the relay selection scheme based on instantaneous channel states. Moreover, it can achieve higher secrecy capacity compared with the scheme without artificial noise. Simulations are conducted to validate the theoretical analyses, and the results demonstrate the validity and reliable security of the scheme. Copyright © 2016 John Wiley & Sons, Ltd.

With the advancement and deployment of leading-edge telecommunication technologies for sensing and collecting traffic related information, the vehicular ad-hoc networks (VANETs) have emerged as a new application scenario that is envisioned to revolutionize the human driving experiences and traffic flow control systems. To avoid any possible malicious attack and resource abuse, employing lightweight cryptosystems is widely recognized as one of the most effective approaches for the VANETs to achieve confidentiality, integrity and authentication. As a typical substitution-permutation network lightweight cryptosystem, LED supports 64-bit and 128-bit secret keys, which are flexible to provide security for the RFID and other highly-constrained devices in the VANETs. Since its introduction, some research of fault analysis has been devoted to attacking the last three rounds of LED. It is an open problem to know whether provoking faults at a former round of LED allows recovering the secret key. In this paper, we give an answer to this problem by showing a novel impossible differential fault analysis on one round earlier of all LED keysize variants. Mathematical analysis and simulating experiments show that the attack could recover the 64-bit and 128-bit secret keys of LED by introducing 48 faults and 96 faults in average, respectively. The result in this study describes that LED is vulnerable to a half byte impossible differential fault analysis. It will be beneficial to the analysis of the same type of other iterated lightweight cryptosystems in the VANETs.