Optimal Client Sampling in Federated Learning with Client-Level Heterogeneous Differential Privacy

Federated Learning with client-level differential privacy DP provides a promising framework for collaboratively training models while rigorously protecting clients' privacy. However, classic approaches like DP-FedAvg struggle when clients have heterogeneous privacy requirements, as they must...

Security Bulletin: Multiple Vulnerabilities affecting IBM Decision Optimization for Cloud Pak for Data are addressed

Summary There are multiple vulnerabilities impacting IBM Decision Optimization for Cloud Pak for Data. This bulletin identifies the steps to take to address the vulnerabilities. Vulnerability Details CVEID:CVE-2025-22150 DESCRIPTION: Undici is an HTTP/1.1 client. Starting in version 4.5.0 and pri...

Co-Evolutionary Defence of Active Directory Attack Graphs Via GNN-Approximated Dynamic Programming

Modern enterprise networks increasingly rely on Active Directory AD for identity and access management. However, this centralization exposes a single point of failure, allowing adversaries to compromise high-value assets. Existing AD defense approaches often assume static attacker behavior, but...

LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs

Efficient red-teaming method to uncover vulnerabilities in Large Language Models LLMs is crucial. While recent attacks often use LLMs as optimizers, the discrete language space make gradient-based methods struggle. We introduce LARGO Latent Adversarial Reflection through Gradient Optimization, a...

Anti-Sensing: Defense against Unauthorized Radar-Based Human Vital Sign Sensing with Physically Realizable Wearable Oscillators

Recent advancements in Ultra-Wideband UWB radar technology have enabled contactless, non-line-of-sight vital sign monitoring, making it a valuable tool for healthcare. However, UWB radar's ability to capture sensitive physiological data, even through walls, raises significant privacy concerns,...

Optimal Allocation of Privacy Budget on Hierarchical Data Release

Releasing useful information from datasets with hierarchical structures while preserving individual privacy presents a significant challenge. Standard privacy-preserving mechanisms, and in particular Differential Privacy, often require careful allocation of a finite privacy budget across differen...

DataSentinel: a Game-Theoretic Detection of Prompt Injection Attacks

LLM-integrated applications and agents are vulnerable to prompt injection attacks, where an attacker injects prompts into their inputs to induce attacker-desired outputs. A detection method aims to determine whether a given input is contaminated by an injected prompt. However, existing detection...

kernel: ext4: no need to continue when the number of entries is 1

No description is available for this CVE...

Improved Algorithms for Differentially Private Language Model Alignment

Language model alignment is crucial for ensuring that large language models LLMs align with human preferences, yet it often involves sensitive user data, raising significant privacy concerns. While prior work has integrated differential privacy DP with alignment techniques, their performance...

RuleGenie: SIEM Detection Rule Set Optimization

SIEM systems serve as a critical hub, employing rule-based logic to detect and respond to threats. Redundant or overlapping rules in SIEM systems lead to excessive false alerts, degrading analyst performance due to alert fatigue, and increase computational overhead and response latency for actual...

FedTDP: a Privacy-Preserving and Unified Framework for Trajectory Data Preparation Via Federated Learning

Trajectory data, which capture the movement patterns of people and vehicles over time and space, are crucial for applications like traffic optimization and urban planning. However, issues such as noise and incompleteness often compromise data quality, leading to inaccurate trajectory analyses and...

Webex App for VDI not optimized

Webex App for VDI is working with fallback mode, instead of VDI-optimized mode...

Preparing for the Post Quantum Era: Quantum Ready Architecture for Security and Risk Management (QUASAR) -- a Strategic Framework for Cybersecurity

As quantum computing progresses, traditional cryptographic systems face the threat of obsolescence due to the capabilities of quantum algorithms. This paper introduces the Quantum-Ready Architecture for Security and Risk Management QUASAR, a novel framework designed to help organizations prepare...

DMRL: Data- and Model-Aware Reward Learning for Data Extraction

Large language models LLMs are inherently vulnerable to unintended privacy breaches. Consequently, systematic red-teaming research is essential for developing robust defense mechanisms. However, current data extraction methods suffer from several limitations: 1 rely on dataset duplicates...

SUSE-SU-2025:1452-1 Security update for libva

This update for libva fixes the following issues: Update to libva version 2.20.0, which includes security fix for: - CVE-2023-39929: Uncontrolled search path may allow an authenticated user to escalate privilege via local access bsc1224413, jscPED-11066 This includes latest version of one of the...

SUSE-SU-2025:1451-1 Security update for libva

This update for libva fixes the following issues: Update to libva version 2.20.0, which includes security fix for: uncontrolled search path may allow an authenticated user to escalate privilege via local access CVE-2023-39929, bsc1224413, jscPED-11066 This includes latest version of one of the...

CVE-2023-53134 bnxt_en: Avoid order-5 memory allocation for TPA data

In the Linux kernel, the following vulnerability has been resolved: bnxten: Avoid order-5 memory allocation for TPA data The driver needs to keep track of all the possible concurrent TPA GRO/LRO completions on the aggregation ring. On P5 chips, the maximum number of concurrent TPA is 256 and the...

HoneyBee: Efficient Role-Based Access Control for Vector Databases Via Dynamic Partitioning

As vector databases gain traction in enterprise applications, robust access control has become critical to safeguard sensitive data. Access control in these systems is often implemented through hybrid vector queries, which combine nearest neighbor search on vector data with relational predicates...

Zero-Day Botnet Attack Detection in IoV: a Modular Approach Using Isolation Forests and Particle Swarm Optimization

The Internet of Vehicles IoV is transforming transportation by enhancing connectivity and enabling autonomous driving. However, this increased interconnectivity introduces new security vulnerabilities. Bot malware and cyberattacks pose significant risks to Connected and Autonomous Vehicles CAVs, ...

Cert-SSB: toward Certified Sample-Specific Backdoor Defense

Deep neural networks DNNs are vulnerable to backdoor attacks, where an attacker manipulates a small portion of the training data to implant hidden backdoors into the model. The compromised model behaves normally on clean samples but misclassifies backdoored samples into the attacker-specified...