Securing Transformer-Based AI Execution Via Unified TEEs and Crypto-Protected Accelerators

Recent advances in Transformer models, e.g., large language models LLMs, have brought tremendous breakthroughs in various artificial intelligence AI tasks, leading to their wide applications in many security-critical domains. Due to their unprecedented scale and prohibitively high development cos...

Detection of Intelligent Tampering in Wireless Electrocardiogram Signals Using Hybrid Machine Learning

With the proliferation of wireless electrocardiogram ECG systems for health monitoring and authentication, protecting signal integrity against tampering is becoming increasingly important. This paper analyzes the performance of CNN, ResNet, and hybrid Transformer-CNN models for tamper detection. ...

Security Bulletin: IBM Cognos Transformer is affected by vulnerabilities in IBM® Java™

Summary There are vulnerabilities in IBM® Java™ Version 8 used by IBM Cognos Transformer. Vulnerability Details CVEID:CVE-2024-21131 DESCRIPTION: An unspecified vulnerability in Java SE related to the VM component could allow a remote attacker to cause low integrity impact. CVSS Source: IBM X-For...

Boosting Generative Adversarial Transferability with Self-Supervised Vision Transformer Features

The ability of deep neural networks DNNs come from extracting and interpreting features from the data provided. By exploiting intermediate features in DNNs instead of relying on hard labels, we craft adversarial perturbation that generalize more effectively, boosting black-box transferability...

Deep CNN Face Matchers Inherently Support Revocable Biometric Templates

One common critique of biometric authentication is that if an individual's biometric is compromised, then the individual has no recourse. The concept of revocable biometrics was developed to address this concern. A biometric scheme is revocable if an individual can have their current enrollment i...

HARPT: a Corpus for Analyzing Consumers' Trust and Privacy Concerns in Mobile Health Apps

We present HARPT, a large-scale annotated corpus of mobile health app store reviews aimed at advancing research in user privacy and trust. The dataset comprises over 480,000 user reviews labeled into seven categories that capture critical aspects of trust in applications, trust in providers and...

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT

The rapid expansion of the Internet of Things IoT has introduced significant security challenges, necessitating efficient and adaptive Intrusion Detection Systems IDS. Traditional IDS models often overlook the temporal characteristics of network traffic, limiting their effectiveness in early thre...

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models

Vision-Language Models VLMs such as CLIP have demonstrated remarkable capabilities in understanding relationships between visual and textual data through joint embedding spaces. Despite their effectiveness, these models remain vulnerable to adversarial attacks, particularly in the image modality,...

Haptic-Based User Authentication for Tele-robotic System

Tele-operated robots rely on real-time user behavior mapping for remote tasks, but ensuring secure authentication remains a challenge. Traditional methods, such as passwords and static biometrics, are vulnerable to spoofing and replay attacks, particularly in high-stakes, continuous interactions...

BIT-MARIADB-MIN-2023-52970

MariaDB Server 10.4 through 10.5., 10.6 through 10.6., 10.7 through 10.11., 11.0 through 11.0., and 11.1 through 11.4. crashes in Itemdirectviewref::derivedfieldtransformerforwhere...

Quantifying Mix Network Privacy Erosion with Generative Models

Modern mix networks improve over Tor and provide stronger privacy guarantees by robustly obfuscating metadata. As long as a message is routed through at least one honest mixnode, the privacy of the users involved is safeguarded. However, the complexity of the mixing mechanisms makes it difficult ...

Ai-Driven Vulnerability Analysis in Smart Contracts: Trends, Challenges and Future Directions

Smart contracts, integral to blockchain ecosystems, enable decentralized applications to execute predefined operations without intermediaries. Their ability to enforce trustless interactions has made them a core component of platforms such as Ethereum. Vulnerabilities such as numerical overflows,...

Can In-Context Reinforcement Learning Recover from Reward Poisoning Attacks?

We study the corruption-robustness of in-context reinforcement learning ICRL, focusing on the Decision-Pretrained Transformer DPT, Lee et al., 2023. To address the challenge of reward poisoning attacks targeting the DPT, we propose a novel adversarial training framework, called Adversarially...

ZIV IDF和ZIV ZLF 代码注入漏洞

The ZIV IDF and ZIV ZLF are both transformer differential protection relays from ZIV Spain. A code injection vulnerability exists in ZIV IDF version v0.10.0-0C03-03 and ZLF version v0.10.0-0C03-04, which originates from a code injection that could lead to malicious code execution...

ZIV IDF和ZIV ZLF 安全漏洞

The ZIV IDF and ZIV ZLF are both transformer differential protection relays from ZIV Spain. A security vulnerability exists in ZIV IDF version v0.10.0-0C03-03 and ZLF version v0.10.0-0C03-04, which stems from a cross-resource sharing misconfiguration...

ZIV IDF 跨站脚本漏洞

The ZIV IDF is a transformer differential protection relay from ZIV Spain. A cross-site scripting vulnerability exists in ZIV IDF version v0.10.0-0C03-03 and ZLF v0.10.0-0C03-04, which originates from stored cross-site scripting and could lead to the execution of malicious scripts...

ZIV IDF和ZIV ZLF 安全漏洞

The ZIV IDF and ZIV ZLF are both transformer differential protection relays from ZIV Spain. A security vulnerability exists in ZIV IDF version v0.10.0-0C03-03 and ZLF version v0.10.0-0C03-04, which stems from a cross-resource sharing configuration error...

MAL-2025-4729 Malicious code in adobe-parcel-transformer-test-app (npm)

The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware b58e301f0f85b9d9bf91ef63a56544bc62c9002bb5ff0e59733da758b1115c73 Any computer that has this package installed or running should be considered...

Transformers in Protein: a Survey

As protein informatics advances rapidly, the demand for enhanced predictive accuracy, structural analysis, and functional understanding has intensified. Transformer models, as powerful deep learning architectures, have demonstrated unprecedented potential in addressing diverse challenges across...

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks

Verification of the integrity of deep learning inference is crucial for understanding whether a model is being applied correctly. However, such verification typically requires access to model weights and potentially sensitive or private training data. So-called Zero-knowledge Succinct...