Empower Users and Protect Against GenAI Data Loss

When generative AI tools became widely available in late 2022, it wasn't just technologists who paid attention. Employees across all industries immediately recognized the potential of generative AI to boost productivity, streamline communication and accelerate work. Like so many waves of...

Connect with us at the Gartner Security & Risk Management Summit

Security professionals visiting booths scattered around a hall, eager for solutions to today’s top cybersecurity challenges to protect their resources and people. The hum of hundreds of conversations. Presenters in packed sessions sharing expertise, trends, and stories to energize attendees. Few...

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery

To boost the encoder stealing attack under the perturbation-based defense that hinders the attack performance, we propose a boosting encoder stealing attack with perturbation recovery named BESA. It aims to overcome perturbation-based defenses. The core of BESA consists of two modules: perturbati...

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation Via Few-Shot Private Data and Generative APIs

The rise of generative APIs has fueled interest in privacy-preserving synthetic data generation. While the Private Evolution PE algorithm generates Differential Privacy DP synthetic images using diffusion model APIs, it struggles with few-shot private data due to the limitations of its DP-protect...

Poisoning Behavioral-Based Worker Selection in Mobile Crowdsensing Using Generative Adversarial Networks

With the widespread adoption of Artificial intelligence AI, AI-based tools and components are becoming omnipresent in today's solutions. However, these components and tools are posing a significant threat when it comes to adversarial attacks. Mobile Crowdsensing MCS is a sensing paradigm that...

VideoMarkBench: Benchmarking Robustness of Video Watermarking

The rapid development of video generative models has led to a surge in highly realistic synthetic videos, raising ethical concerns related to disinformation and copyright infringement. Recently, video watermarking has been proposed as a mitigation strategy by embedding invisible marks into...

Repository Vector Search Methods

The emergence of Large Language Models LLM has propelled Generative AI and surfaced one of its key components to a broad audience: Embeddings. Embeddings are a vector representation of data in a high-dimensional space capturing their semantic meaning. Vector representations allow for more efficie...

SuperPure: Efficient Purification of Localized and Distributed Adversarial Patches Via Super-Resolution GAN Models

As vision-based machine learning models are increasingly integrated into autonomous and cyber-physical systems, concerns about physical adversarial patch attacks are growing. While state-of-the-art defenses can achieve certified robustness with minimal impact on utility against highly-concentrate...

Securing Generative AI: Navigating Risk and Building Resilience

Running short on time but still want to stay in the know? Well, we’ve got you covered! We’ve condensed all the key takeaways into a handy audio summary. Our AI-driven podcasts are fit for on the go. Click right here to hear it all on CAASM & CDMB Inefficiencies! Generative AI has changed the way ...

CSAGC-IDS: a Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data

As computer networks proliferate, the gravity of network intrusions has escalated, emphasizing the criticality of network intrusion detection systems for safeguarding security. While deep learning models have exhibited promising results in intrusion detection, they face challenges in managing...

GenAI Security: Outsmarting the Bots with a Proactive Testing Framework

The increasing sophistication and integration of Generative AI GenAI models into diverse applications introduce new security challenges that traditional methods struggle to address. This research explores the critical need for proactive security measures to mitigate the risks associated with...

Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data

Federated learning FL presents an effective solution for collaborative model training while maintaining data privacy across decentralized client datasets. However, data quality issues such as noisy labels, missing classes, and imbalanced distributions significantly challenge its effectiveness. Th...

System Prompt Poisoning: Persistent Attacks on Large Language Models beyond User Injection

Large language models LLMs have gained widespread adoption across diverse applications due to their impressive generative capabilities. Their plug-and-play nature enables both developers and end users to interact with these models through simple prompts. However, as LLMs become more integrated in...

IBM Concert 代码问题漏洞

IBM Concert is a new tool from International Business Machines IBM, Inc. that uses generative AI to help manage complex cloud-native applications. A code issue vulnerability exists in IBM Concert 1.0.5 and prior versions that stems from the presence of server-side request forgery, which could...

Generative AI in Financial Institution: a Global Survey of Opportunities, Threats, and Regulation

Generative Artificial Intelligence GenAI is rapidly reshaping the global financial landscape, offering unprecedented opportunities to enhance customer engagement, automate complex workflows, and extract actionable insights from vast financial data. This survey provides an overview of GenAI adopti...

Guard Against GenAI and LLM Risks from Development to Deployment with Qualys TotalAI

Artificial intelligence is fundamentally reshaping the enterprise. From automating customer service to accelerating code generation, large language models LLMs are rapidly becoming embedded in how businesses operate and compete. But as organizations embrace this innovation, they are also opening...

TriniMark: a Robust Generative Speech Watermarking Method for Trinity-Level Attribution

Whitepaper called TriniMark: A Robust Generative Speech Watermarking Method For Trinity-Level Attribution...

A Cryptographic Perspective on Mitigation Vs. Detection in Machine Learning

In this paper, we initiate a cryptographically inspired theoretical study of detection versus mitigation of adversarial inputs produced by attackers of Machine Learning algorithms during inference time. We formally define defense by detection DbD and defense by mitigation DbM. Our definitions com...

Securing GenAI Multi-Agent Systems against Tool Squatting: a Zero Trust Registry-Based Approach

The rise of generative AI GenAI multi-agent systems MAS necessitates standardized protocols enabling agents to discover and interact with external tools. However, these protocols introduce new security challenges, particularly; tool squatting; the deceptive registration or representation of tools...

DeeCLIP: a Robust and Generalizable Transformer-Based Framework for Detecting AI-Generated Images

This paper introduces DeeCLIP, a novel framework for detecting AI-generated images using CLIP-ViT and fusion learning. Despite significant advancements in generative models capable of creating highly photorealistic images, existing detection methods often struggle to generalize across different...