Next-Gen Identity Security
Next-Gen Identity Security
2026-09-06 归档
今日共收录 918 条安全情报，包含 147 个 CVE，434 篇安全通告，以及 81 篇研究论文。
← 返回归档列表CrowdStrike Expands Identity Leadership with OpenID and IDPro
CrowdStrike Expands Identity Leadership with OpenID and IDPro
cloud architecture assessment
cloud architecture assessment
ransomware and multifaceted extortion defense
ransomware and multifaceted extortion defense
Google Cloud Next 2026Catch-up sessions on the keynotes and select sessions are now available on demand.Explore content on-demand
Google Cloud Next 2026Catch-up sessions on the keynotes and select sessions are now available on demand.Explore content
The Identity Problem Hiding in AI Agent Deployments
The Identity Problem Hiding in AI Agent Deployments
94% of Organizations Report Cloud Breaches: CrowdStrike State of CDR Survey
94% of Organizations Report Cloud Breaches: CrowdStrike State of CDR Survey
Falcon Cloud Security June 2026 Release: Updates for Azure and Google Cloud
Falcon Cloud Security June 2026 Release: Updates for Azure and Google Cloud
Falcon Cloud Security July 2026 Release: Helping Security Teams Move Faster in the Cloud
Falcon Cloud Security July 2026 Release: Helping Security Teams Move Faster in the Cloud
CrowdStrike Named Strongest Overall Leader in 2026 Frost Radar™: Cloud Workload Protection Platforms
CrowdStrike Named Strongest Overall Leader in 2026 Frost Radar™: Cloud Workload Protection Platforms
CrowdStrike Extends Endpoint Security to Stop Software Supply Chain Attacks
CrowdStrike Extends Endpoint Security to Stop Software Supply Chain Attacks
CrowdStrike Announces Agentic Identity Provider
CrowdStrike Announces Agentic Identity Provider
CounterSEVeillance: Performance-Counter Attacks on AMD SEV-SNP.
CounterSEVeillance 是一篇针对 AMD SEV-SNP 机密虚拟机的新型侧信道攻击研究。SEV-SNP 是一种处理器扩展，旨在通过可信执行环境保护虚拟机的完整性和机密性，即使在共享托管环境中也能防止恶意管理程序访问客户机内
Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple's Count Mean Sketch in Practice.
本文针对Apple在本地差分隐私（Local Differential Privacy, LDP）实践中使用的Count Mean Sketch（CMS）机制，提出了一种名为'池推断攻击'（Pool Inference Attack）的新颖
Lend Me Your Ear: Passive Remote Physical Side Channels on PCs.
该论文针对个人计算设备在实际运行时不可避免地向外辐射物理信号（如电磁波、声音、热变化等）的问题，研究如何在不接触目标设备的前提下，利用这些信号窃取敏感信息。传统密码分析通常假设攻击者能够直接观测设备或拥有网络控制权，而物理侧信道攻击则通过分
"Like Lesbians Walking the Perimeter": Experiences of U.S. LGBTQ+ Folks With Online Security, Safety, and Privacy Advice.
本研究以美国LGBTQ+社群为对象，采用质性研究方法（访谈或调查），探讨该群体在获取和应用在线安全、安全与隐私建议时的独特经历与挑战。论文标题中“Like Lesbians Walking the Perimeter”源自参与者对自身处境的
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
联邦学习（FL）允许多个客户端在服务器协调下协同训练全局机器学习模型，而无需交换私有训练数据。然而，其分布式特性使其容易受到投毒攻击：恶意客户端可通过发送篡改后的本地模型更新来操纵全局模型。为此，学术界提出了多种针对拜占庭故障的鲁棒聚合规则
Invisible Finger: Practical Electromagnetic Interference Attack on Touchscreen-based Electronic Devices.
该论文系统地研究了触摸屏电子设备（如智能手机、平板电脑）对故意电磁干扰（IEMI）的脆弱性，并首次提出了一种实用的 IEMI 攻击向量。研究背景是：虽然电子设备安全性已被广泛研究，但触摸屏面对电磁攻击的鲁棒性尚未被充分探索。论文的核心贡献在
Private Approximate Nearest Neighbor Search with Sublinear Communication.
本文提出了一种面向隐私保护的近似最近邻搜索（Private Approximate Nearest Neighbor Search）的轻量级协议，解决了现有方案依赖重量级密码学工具导致计算和带宽开销过高的问题。该协议基于两个不共谋的服务器，
Concept-based Adversarial Attacks: Tricking Humans and Classifiers Alike.
这篇论文提出了一种全新的对抗样本生成方法，称为基于概念的对抗攻击。与传统的像素级扰动（例如添加不可见噪声来欺骗深度神经网络）不同，该方法通过直接修改神经网络高层中编码语义概念的激活值，将原始样本的表示向目标样本的方向移动，然后利用修改后的激