Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 71 tok/s
Gemini 2.5 Pro 52 tok/s Pro
GPT-5 Medium 18 tok/s Pro
GPT-5 High 15 tok/s Pro
GPT-4o 101 tok/s Pro
Kimi K2 196 tok/s Pro
GPT OSS 120B 467 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Risks & Benefits of LLMs & GenAI for Platform Integrity, Healthcare Diagnostics, Cybersecurity, Privacy & AI Safety: A Comprehensive Survey, Roadmap & Implementation Blueprint (2506.12088v1)

Published 10 Jun 2025 in cs.CR and cs.CY

Abstract: LLMs and generative AI (GenAI) systems such as ChatGPT, Claude, Gemini, LLaMA, and Copilot, developed by OpenAI, Anthropic, Google, Meta, and Microsoft are reshaping digital platforms and app ecosystems while introducing key challenges in cybersecurity, privacy, and platform integrity. Our analysis shows alarming trends: LLM-assisted malware is projected to rise from 2% in 2021 to 50% by 2025; AI-generated Google reviews grew from 1.2% in 2021 to 12.21% in 2023, with an expected 30% by 2025; AI scam reports surged 456%; and misinformation sites increased over 1500%, with a 50-60% increase in deepfakes in 2024. Concurrently, as LLMs have facilitated code development, mobile app submissions grew from 1.8 million in 2020 to 3.0 million in 2024, with 3.6 million expected by 2025. To address AI threats, platforms from app stores like Google Play and Apple to developer hubs like GitHub Copilot, and social platforms like TikTok and Facebook, to marketplaces like Amazon are deploying AI and LLM-based defenses. This highlights the dual nature of these technologies as both the source of new threats and the essential tool for their mitigation. Integrating LLMs into clinical diagnostics also raises concerns about accuracy, bias, and safety, needing strong governance. Drawing on a comprehensive analysis of 455 references, this paper presents a survey of LLM and GenAI risks. We propose a strategic roadmap and operational blueprint integrating policy auditing (CCPA, GDPR), fraud detection, and compliance automation, and an advanced LLM-DA stack with modular components including multi LLM routing, agentic memory, and governance layers to enhance platform integrity. We also provide actionable insights, cross-functional best practices, and real-world case studies. These contributions offer paths to scalable trust, safety, and responsible innovation across digital platforms.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.

Authors (1)

X Twitter Logo Streamline Icon: https://streamlinehq.com