LEMMA: Towards LVLM-Enhanced Multimodal Misinformation Detection with External Knowledge Augmentation

The rise of multimodal misinformation on social platforms poses significant challenges for individuals and societies. Its increased credibility and broader impact compared to textual misinformation make detection complex, requiring robust reasoning across diverse media types and profound knowledge for accurate verification. The emergence of Large Vision Language Model (LVLM) offers a potential solution to this problem. Leveraging their proficiency in processing visual and textual information, LVLM demonstrates promising capabilities in recognizing complex information and exhibiting strong reasoning skills. In this paper, we first investigate the potential of LVLM on multimodal misinformation detection. We find that even though LVLM has a superior performance compared to LLMs, its profound reasoning may present limited power with a lack of evidence. Based on these observations, we propose LEMMA: LVLM-Enhanced Multimodal Misinformation Detection with External Knowledge Augmentation. LEMMA leverages LVLM intuition and reasoning capabilities while augmenting them with external knowledge to enhance the accuracy of misinformation detection. Our method improves the accuracy over the top baseline LVLM by 7% and 13% on Twitter and Fakeddit datasets respectively.

Research on Virus Cyberattack-Defense Based on Electromagnetic Radiation

Information technology and telecommunications have rapidly permeated various domains, resulting in a significant influx of data traversing the networks between computers. Consequently, research of cyberattacks in computer systems has become crucial for many organizations. Accordingly, recent cybersecurity incidents have underscored the rapidly evolving nature of future threats and attack methods, particularly those involving computer viruses wireless injection. This paper aims to study and demonstrate the feasibility of remote computer virus radiation injection. To achieve this objective, digital signal processing (DSP) plays a vital role. By studying the principles and models of radiation attacks and computer virus propagation, the modulation of the binary data stream of the simulated virus into a terahertz radar carrier signal by Phase-Shift Keying (PSK) is simulated, enabling the implementation of an attack through the "field to line" coupling of electromagnetic signals. Finally, the defense and countermeasures based on signal recognition are discussed for such attacks. Additionally, an idea of establishing a virus library for cyberattack signals and employing artificial intelligence (AI) algorithms for automated intrusion detection is proposed as a means to achieve cybersecurity situation awareness.