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Showing posts with label Google Gemini AI. Show all posts

Google Messages' Gemini Update: What You Need To Know

 



Google's latest update to its Messages app, dubbed Gemini, has ignited discussions surrounding user privacy. Gemini introduces AI chatbots into the messaging ecosystem, but it also brings forth a critical warning regarding data security. Unlike conventional end-to-end encrypted messaging services, conversations within Gemini lack this crucial layer of protection, leaving them potentially vulnerable to access by Google and potential exposure of sensitive information.

This privacy gap has raised eyebrows among users, with some expressing concern over the implications of sharing personal data within Gemini chats. Others argue that this aligns with Google's data-driven business model, which leverages user data to enhance its AI models and services. However, the absence of end-to-end encryption means that users may inadvertently expose confidential information to third parties.

Google has been forthcoming about the security implications of Gemini, explicitly stating that chats within the feature are not end-to-end encrypted. Additionally, Google collects various data points from these conversations, including usage information, location data, and user feedback, to improve its products and services. Despite assurances of privacy protection measures, users are cautioned against sharing sensitive information through Gemini chats.

The crux of the issue lies in the disparity between users' perceptions of AI chatbots as private entities and the reality of these conversations being accessible to Google and potentially reviewed by human moderators for training purposes. Despite Google's reassurances, users are urged to exercise caution and refrain from sharing sensitive information through Gemini chats.

While Gemini's current availability is limited to adult beta testers, Google has hinted at its broader rollout in the near future, extending its reach beyond English-speaking users to include French-speaking individuals in Canada as well. This expansion signifies a pivotal moment in messaging technology, promising enhanced communication experiences for a wider audience. However, as users eagerly anticipate the platform's expansion, it becomes increasingly crucial for them to proactively manage their privacy settings. By taking the time to review and adjust their preferences, users can ensure a more secure messaging environment tailored to their individual needs and concerns. This proactive approach empowers users to navigate digital communication with confidence and peace of mind.

All in all, the introduction of Gemini in Google Messages underscores the importance of user privacy in the digital age. While technological advancements offer convenience, they also necessitate heightened awareness to safeguard personal information from potential breaches.




Private AI Chatbot Not Safe From Hackers With Encryption


AI helpers have assimilated into our daily lives in over a year and gained access to our most private information and worries. 

Sensitive information, such as personal health questions and professional consultations, is entrusted to these digital companions. While providers utilize encryption to protect user interactions, new research raises questions about how secure AI assistants may be.

Understanding the attack on AI Assistant Responses

According to a study, an attack that can predict AI assistant reactions with startling accuracy has been discovered. 

This method uses big language models to refine results and takes advantage of a side channel present in most major AI assistants, except for Google Gemini.

According to Offensive AI Research Lab, a passive adversary can identify the precise subject of more than half of all recorded responses by intercepting data packets sent back and forth between the user and the AI assistant.

Recognizing Token Privacy

This attack is centered around a side channel that is integrated within the tokens that AI assistants use. 

Real-time response transmission is facilitated via tokens, which are encoded-word representations. But the tokens are delivered one after the other, exposing a flaw known as the "token-length sequence." By using this route, attackers can infer response content and jeopardize user privacy.

The Token Inference Assault: Deciphering Cryptographic Reactions

Researchers use a token inference attack to refine intercepted data by using LLMs to convert token sequences into comprehensible language. 

Yisroel Mirsky, the director of the Offensive AI Research Lab at Ben-Gurion University in Israel, stated in an email that "private chats sent from ChatGPT and other services can currently be read by anybody."

By using publicly accessible conversation data to train LLMs, researchers can decrypt responses with remarkably high accuracy. This technique leverages the predictability of AI assistant replies to enable contextual decryption of encrypted content, similar to a known plaintext attack.

An AI Chatbot's Anatomy: Understanding of Tokenization

AI chatbots use tokens as the basic building blocks for text processing, which direct the creation and interpretation of conversation. 

To learn patterns and probabilities, LLMs examine large datasets of tokenized text during training. According to Ars Technica, tokens enable real-time communication between users and AI helpers, allowing users to customize their responses depending on environmental cues.

Current Vulnerabilities and Countermeasures

An important vulnerability is the real-time token transmission, which allows attackers to deduce response content based on packet length. 

Sequential delivery reveals answer data, while batch transmission hides individual token lengths. Reevaluating token transmission mechanisms is necessary to mitigate this risk and reduce susceptibility to passive adversaries.

Protecting the Privacy of Data in AI Interactions

Protecting user privacy is still critical as AI helpers develop. Reducing security threats requires implementing strong encryption techniques and improving token delivery mechanisms. 

By fixing flaws and improving data security protocols, providers can maintain users' faith and trust in AI technologies.

Safeguarding AI's Future

A new age of human-computer interaction is dawning with the introduction of AI helpers. But innovation also means accountability. 

Providers need to give data security and privacy top priority as vulnerabilities are found by researchers. Hackers are out there; the next thing we know, they're giving other businesses access to our private chats.