Reputation-Based Partition Scheme for IoT Security

With the popularity of smart terminals, such as the Internet of Things, crowdsensing is an emerging data aggregation paradigm, which plays a pivotal role in data-driven applications. There are some key issues in the development of crowdsensing such as platform security and privacy protection. As...

Real-World Evaluation of Protocol-Compliant Denial-Of-Service Attacks on C-V2X-Based Forward Collision Warning Systems

Cellular Vehicle-to-Everything C-V2X technology enables low-latency, reliable communications essential for safety applications such as a Forward Collision Warning FCW system. C-V2X deployments operate under strict protocol compliance with the 3rd Generation Partnership Project 3GPP and the Societ...

Experimental Evaluation of Post-Quantum Homomorphic Encryption for Privacy-Preserving V2X Communication

Intelligent Transportation Systems ITS fundamentally rely on vehicle-generated data for applications such as congestion monitoring and route optimization, making the preservation of user privacy a critical challenge. Homomorphic Encryption HE offers a promising solution by enabling computation on...

USN-7682-4 linux-lowlatency, linux-lowlatency-hwe-6.8 vulnerabilities

Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - Network traffic control; CVE-2025-38083, CVE-2025-37797...

Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems

The increasing digitization of smart grids has improved operational efficiency but also introduced new cybersecurity vulnerabilities, such as False Data Injection Attacks FDIAs targeting Automatic Generation Control AGC systems. While machine learning ML and deep learning DL models have shown...

EdgeAgentX-DT: Integrating Digital Twins and Generative AI for Resilient Edge Intelligence in Tactical Networks

We introduce EdgeAgentX-DT, an advanced extension of the EdgeAgentX framework that integrates digital twin simulations and generative AI-driven scenario training to significantly enhance edge intelligence in military networks. EdgeAgentX-DT utilizes network digital twins, virtual replicas...

Analysis of Post-Quantum Cryptography in User Equipment in 5G and Beyond

The advent of quantum computing threatens the security of classical public-key cryptographic systems, prompting the transition to post-quantum cryptography PQC. While PQC has been analyzed in theory, its performance in practical wireless communication environments remains underexplored. This pape...

Efficient Private Inference Based on Helper-Assisted Malicious Security Dishonest Majority MPC

Private inference based on Secure Multi-Party Computation MPC addresses data privacy risks in Machine Learning as a Service MLaaS. However, existing MPC-based private inference frameworks focuses on semi-honest or honest majority models, whose threat models are overly idealistic, while malicious...

Hybrid Quantum Security for IPsec

Quantum Key Distribution QKD offers information-theoretic security against quantum computing threats, but integrating QKD into existing security protocols remains an unsolved challenge due to fundamental mismatches between pre-distributed quantum keys and computational key exchange paradigms. Thi...

Bullshark on Narwhal: Implementation-Level Workflow Analysis of Round-Based DAG Consensus in Theory and Practice

Round-based DAGs enable high-performance Byzantine fault-tolerant consensus, yet their technical advantages remain underutilized due to their short history. While research on consensus protocols is active in both academia and industry, many studies overlook implementation-level algorithms, leavin...

Leveraging Photonic Interconnects for Scalable and Efficient Fully Homomorphic Encryption

Fully Homomorphic Encryption FHE facilitates secure computations on encrypted data but imposes significant demands on memory bandwidth and computational power. While current FHE accelerators focus on optimizing computation, they often face bandwidth limitations that result in performance...

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...

Real-Time Agile Software Management for Edge and Fog Computing Based Smart City Infrastructure

The evolution of smart cities demands scalable, secure, and energy-efficient architectures for real-time data processing. With the number of IoT devices expected to exceed 40 billion by 2030, traditional cloud-based systems are increasingly constrained by bandwidth, latency, and energy limitation...

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems

The growing deployment of deep learning models in real-world environments has intensified the need for efficient inference under strict latency and resource constraints. To meet these demands, dynamic deep learning systems DDLSs have emerged, offering input-adaptive computation to optimize runtim...

Real-Time, Low-Latency Surveillance Using Entropy-Based Adaptive Buffering and MobileNetV2 on Edge Devices

This paper describes a high-performance, low-latency video surveillance system designed for resource-constrained environments. We have proposed a formal entropy-based adaptive frame buffering algorithm and integrated that with MobileNetV2 to achieve high throughput with low latency. The system is...

Optimizing System Latency for Blockchain-Encrypted Edge Computing in Internet of Vehicles

As Internet of Vehicles IoV technology continues to advance, edge computing has become an important tool for assisting vehicles in handling complex tasks. However, the process of offloading tasks to edge servers may expose vehicles to malicious external attacks, resulting in information loss or...

Astra Linux – Vulnerability in Linux 6.12

In the Linux kernel, the following vulnerabilities have been resolved: media: intel/ipu6: The CPU latency QoS request is removed in case of errors. The issue with corruption in the CPU latency QoS list is also fixed. This occurs when the CPU latency request is not removed during error handling,...

FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks

Graph Convolutional Neural Networks GCNs have gained widespread popularity in various fields like personal healthcare and financial systems, due to their remarkable performance. Despite the growing demand for cloud-based GCN services, privacy concerns over sensitive graph data remain significant...

Enhance Your Edge Native Apps with Low Latency Using Multiple EdgeWorkers

Learn how Flexible Composition lets you seamlessly deploy multiple EdgeWorkers in a single request for easier-to-build, scalable, edge native applications...

First-Spammed, First-Served: MEV Extraction on Fast-Finality Blockchains

This research analyzes the economics of spam-based arbitrage strategies on fast-finality blockchains. We begin by theoretically demonstrating that, splitting a profitable MEV opportunity into multiple small transactions is the optimal strategy for CEX-DEX arbitrageurs. We then empirically validat...