Shill Bidding Prevention in Decentralized Auctions Using Smart Contracts

In online auctions, fraudulent behaviors such as shill bidding pose significant risks. This paper presents a conceptual framework that applies dynamic, behavior-based penalties to deter auction fraud using blockchain smart contracts. Unlike traditional post-auction detection methods, this approac...

Adaptive Privacy-Preserving SSD

Data remanence in NAND flash complicates complete deletion on IoT SSDs. We design an adaptive architecture offering four privacy levels PL0-PL3 that select among address, data, and parity deletion techniques. Quantitative analysis balances efficacy, latency, endurance, and cost. Machine-learning...

TensorShield: Safeguarding On-Device Inference by Shielding Critical DNN Tensors with TEE

To safeguard user data privacy, on-device inference has emerged as a prominent paradigm on mobile and Internet of Things IoT devices. This paradigm involves deploying a model provided by a third party on local devices to perform inference tasks. However, it exposes the private model to two primar...

Accountable, Scalable and DoS-Resilient Secure Vehicular Communication

Paramount to vehicle safety, broadcasted Cooperative Awareness Messages CAMs and Decentralized Environmental Notification Messages DENMs are pseudonymously authenticated for security and privacy protection, with each node needing to have all incoming messages validated within an expiration...

CVE-2024-9310

By utilizing software-defined radios and a custom low-latency processing pipeline, RF signals with spoofed location data can be transmitted to aircraft targets. This can lead to the appearance of fake aircraft on displays and potentially trigger undesired Resolution Advisories RAs...

Towards Anonymous Neural Network Inference

We introduce funion, a system providing end-to-end sender-receiver unlinkability for neural network inference. By leveraging the Pigeonhole storage protocol and BACAP blinding-and-capability scheme from the Echomix anonymity system, funion inherits the provable security guarantees of modern...

CVE-2021-25402

Information Exposure vulnerability in Samsung Notes prior to version 4.2.04.27 allows attacker to access s pen latency information...

IOLeak - CPU Side Channel Attacks

AMD ID: AMD-SB-7042 Potential Impact: N/A Severity: N/A Summary Researchers have provided AMD with a summary of relevant remarks and findings detailed in a paper titled “IOLeak Side-Channel Attack Exploiting CPU Frequency Scaling and I/O Latency.” AMD reviewed the summary and believes this attack...

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...

AI-Driven Dynamic Firewall Optimization Using Reinforcement Learning for Anomaly Detection and Prevention

The growing complexity of cyber threats has rendered static firewalls increasingly ineffective for dynamic, real-time intrusion prevention. This paper proposes a novel AI-driven dynamic firewall optimization framework that leverages deep reinforcement learning DRL to autonomously adapt and update...

Zero-Trust Mobility-Aware Authentication Framework for Secure Vehicular Fog Computing Networks

Vehicular Fog Computing VFC is a promising paradigm to meet the low-latency and high-bandwidth demands of Intelligent Transportation Systems ITS. However, dynamic vehicle mobility and diverse trust boundaries introduce critical security challenges. This paper presents a novel Zero-Trust...

Quantum-Resilient Blockchain for Secure Transactions in UAV-Assisted Smart Agriculture Networks

The integration of unmanned aerial vehicles UAVs into smart agriculture has enabled real-time monitoring, data collection, and automated farming operations. However, the high mobility, decentralized nature, and low-power communication of UAVs pose significant security challenges, particularly in...

CRYPTONITE: Scalable Accelerator Design for Cryptographic Primitives and Algorithms

Cryptographic primitives, consisting of repetitive operations with different inputs, are typically implemented using straight-line C code due to traditional execution on CPUs. Computing these primitives is necessary for secure communication; thus, dedicated hardware accelerators are required in...

Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction

LLM-based autonomous agents possess capabilities such as reasoning, tool invocation, and environment interaction, enabling the execution of complex multi-step tasks. The internal reasoning process, i.e., thought, of behavioral trajectory significantly influences tool usage and subsequent actions...

Privacy-Preserving AI for Encrypted Medical Imaging: a Framework for Secure Diagnosis and Learning

The rapid integration of Artificial Intelligence AI into medical diagnostics has raised pressing concerns about patient privacy, especially when sensitive imaging data must be transferred, stored, or processed. In this paper, we propose a novel framework for privacy-preserving diagnostic inferenc...

AES-RV: Hardware-Efficient RISC-V Accelerator with Low-Latency AES Instruction Extension for IoT Security

The Advanced Encryption Standard AES is a widely adopted cryptographic algorithm essential for securing embedded systems and IoT platforms. However, existing AES hardware accelerators often face limitations in performance, energy efficiency, and flexibility. This paper presents AES-RV, a...

Assessing the Latency of Network Layer Security in 5G Networks

In contrast to its predecessors, 5G supports a wide range of commercial, industrial, and critical infrastructure scenarios. One key feature of 5G, ultra-reliable low latency communication, is particularly appealing to such scenarios for its real-time capabilities. However, 5G's enhanced security,...

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...

Sponge Attacks on Sensing AI: Energy-Latency Vulnerabilities and Defense Via Model Pruning

Recent studies have shown that sponge attacks can significantly increase the energy consumption and inference latency of deep neural networks DNNs. However, prior work has focused primarily on computer vision and natural language processing tasks, overlooking the growing use of lightweight AI...

USN-7492-1: Linux kernel vulnerability

A security issues was discovered in the Linux kernel. An attacker could possibly use this to compromise the system. This update corrects flaws in the following subsystems: - Bluetooth drivers; CVE-2024-56653...