The recent advancements in the field of artificial intelligence and cybersecurity have seen significant innovations, particularly in the integration of large language models (LLMs) with blockchain technology and the development of advanced phishing detection systems. The field is moving towards more intelligent and automated solutions that enhance both security and efficiency. LLMs are being leveraged to detect and mitigate vulnerabilities in smart contracts, improve phishing detection through ensemble strategies, and even automate the detection of financial misinformation. Notably, the use of multimodal agents for phishing detection has shown promising results in terms of both accuracy and cost reduction. Additionally, there is a growing focus on making security warnings more accessible, particularly for visually impaired users, through innovative aural warning systems. These developments collectively point towards a future where AI-driven solutions are not only more robust but also more inclusive and cost-effective.
AI-Driven Security Innovations in Blockchain and Cybersecurity
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SmartLLMSentry: A Comprehensive LLM Based Smart Contract Vulnerability Detection Framework
To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models
An AI-Driven Data Mesh Architecture Enhancing Decision-Making in Infrastructure Construction and Public Procurement
SeQwen at the Financial Misinformation Detection Challenge Task: Sequential Learning for Claim Verification and Explanation Generation in Financial Domains
Evaluating Large Language Models' Capability to Launch Fully Automated Spear Phishing Campaigns: Validated on Human Subjects
Exposing LLM Vulnerabilities: Adversarial Scam Detection and Performance
"Oh, sh*t! I actually opened the document!": An Empirical Study of the Experiences with Suspicious Emails in Virtual Reality Headsets
Connecting Large Language Models with Blockchain: Advancing the Evolution of Smart Contracts from Automation to Intelligence
Large Multimodal Agents for Accurate Phishing Detection with Enhanced Token Optimization and Cost Reduction
(Blind) Users Really Do Heed Aural Telephone Scam Warnings