Zero-Trust Agentic Federated Learning for Secure IIoT Defense Systems

Recent attacks on critical infrastructure, including the 2021 Oldsmar water treatment breach and 2023 Danish energy sector compromises, highlight urgent security gaps in Industrial IoT IIoT deployments. While Federated Learning FL enables privacy-preserving collaborative intrusion detection,...

Google Android 安全漏洞

Google Android is a Linux-based open source operating system from Google, Inc. in the United States. A security vulnerability exists in Google Android that stems from a logic error issue in Session.java that could lead to viewing images of other users on the device...

Kaspersky Security Bulletin 2025. Statistics

All statistics in this report come from Kaspersky Security Network KSN, a global cloud service that receives information from components in our security solutions voluntarily provided by Kaspersky users. Millions of Kaspersky users around the globe assist us in collecting information about...

New Android malware lets criminals control your phone and drain your bank account

Albiriox is a new family of Android banking malware that gives attackers live remote control over infected phones, letting them quietly drain bank and crypto accounts during real sessions. Researchers have analyzed a new Android malware family called Albiriox which is showing signs of developing...

New Albiriox MaaS Malware Targets 400+ Apps for On-Device Fraud and Screen Control

A new Android malware named Albiriox has been advertised under a malware-as-a-service MaaS model to offer a "full spectrum" of features to facilitate on-device fraud ODF, screen manipulation, and real-time interaction with infected devices. The malware embeds a hard-coded list comprising over 400...

Google Launches 'Private AI Compute' — Secure AI Processing with On-Device-Level Privacy

Google on Tuesday unveiled a new privacy-enhancing technology called Private AI Compute to process artificial intelligence AI queries in a secure platform in the cloud. The company said it has built Private AI Compute to "unlock the full speed and power of Gemini cloud models for AI experiences,...

Google's Built-In AI Defenses on Android Now Block 10 Billion Scam Messages a Month

Google on Thursday revealed that the scam defenses built into Android safeguard users around the world from more than 10 billion suspected malicious calls and messages every month. The tech giant also said it has blocked over 100 million suspicious numbers from using Rich Communication Services...

Meta boosts scam protection on WhatsApp and Messenger

Vulnerable Facebook Messenger and WhatsApp users are getting more protection thanks to a move from the applications' owner, Meta. The company has announced more safeguards to protect users especially the elderly from scammers. The social media, publishing, and VR giant has added a new warning on...

CVE-2025-11645

CVE-2025-11645 (Tomofun Furbo Mobile App) affects Android versions up to 7.57.0a, arising from insecure storage in the Authentication Token Handler. The issue may allow information disclosure on a physical device; the exploit has been publicly disclosed. Multiple connected sources (including PT-2...

EUVD-2021-17194

Malware in sbrugna...

Google Pixel 10 Adds C2PA Support to Verify AI-Generated Media Authenticity

Google on Tuesday announced that its new Google Pixel 10 phones support the Coalition for Content Provenance and Authenticity C2PA standard out of the box to verify the origin and history of digital content. To that end, support for C2PA's Content Credentials has been added to Pixel Camera and...

Breaking SafetyCore: Exploring the Risks of On-Device AI Deployment

Due to hardware and software improvements, an increasing number of AI models are deployed on-device. This shift enhances privacy and reduces latency, but also introduces security risks distinct from traditional software. In this article, we examine these risks through the real-world case study of...

CVE-2025-41689

An unauthenticated remote attacker can get access without password protection to the affected device. This enables the unprotected read-only access to the stored measurement data...

Invitation Is All You Need! Promptware Attacks against LLM-Powered Assistants in Production Are Practical and Dangerous

The growing integration of LLMs into applications has introduced new security risks, notably known as Promptware - maliciously engineered prompts designed to manipulate LLMs to compromise the CIA triad of these applications. While prior research warned about a potential shift in the threat...

Semantic Encryption: Secure and Effective Interaction with Cloud-Based Large Language Models Via Semantic Transformation

The increasing adoption of Cloud-based Large Language Models CLLMs has raised significant concerns regarding data privacy during user interactions. While existing approaches primarily focus on encrypting sensitive information, they often overlook the logical structure of user inputs. This oversig...

Hot-Swap MarkBoard: an Efficient Black-Box Watermarking Approach for Large-Scale Model Distribution

Recently, Deep Learning DL models have been increasingly deployed on end-user devices as On-Device AI, offering improved efficiency and privacy. However, this deployment trend poses more serious Intellectual Property IP risks, as models are distributed on numerous local devices, making them...

EdgeAgentX-DT: Integrating Digital Twins and Generative AI for Resilient Edge Intelligence in Tactical Networks

We introduce EdgeAgentX-DT, an advanced extension of the EdgeAgentX framework that integrates digital twin simulations and generative AI-driven scenario training to significantly enhance edge intelligence in military networks. EdgeAgentX-DT utilizes network digital twins, virtual replicas...

Towards Privacy-Preserving and Personalized Smart Homes Via Tailored Small Language Models

Large Language Models LLMs have showcased remarkable generalizability in language comprehension and hold significant potential to revolutionize human-computer interaction in smart homes. Existing LLM-based smart home assistants typically transmit user commands, along with user profiles and home...

SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding

Federated recommender system FedRec has emerged as a solution to protect user data through collaborative training techniques. A typical FedRec involves transmitting the full model and entire weight updates between edge devices and the server, causing significant burdens to devices with limited...

Evaluating Apple Intelligence'S Writing Tools for Privacy against Large Language Model-Based Inference Attacks: Insights from Early Datasets

The misuse of Large Language Models LLMs to infer emotions from text for malicious purposes, known as emotion inference attacks, poses a significant threat to user privacy. In this paper, we investigate the potential of Apple Intelligence's writing tools, integrated across iPhone, iPad, and...