Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses

With the wide application of deep reinforcement learning DRL techniques in complex fields such as autonomous driving, intelligent manufacturing, and smart healthcare, how to improve its security and robustness in dynamic and changeable environments has become a core issue in current research...

Forward to Hell? on the Potentials of Misusing Transparent DNS Forwarders in Reflective Amplification Attacks

The DNS infrastructure is infamous for facilitating reflective amplification attacks. Various countermeasures such as server shielding, access control, rate limiting, and protocol restrictions have been implemented. Still, the threat remains throughout the deployment of DNS servers. In this paper...

EUVD-2025-18921

Malicious code in bioql PyPI...

EUVD-2023-42478

Malicious code in bioql PyPI...

EUVD-2023-46895

Malicious code in bioql PyPI...

Securing IoT Devices in Smart Cities: A Review of Proposed Solutions

Privacy and security in Smart Cities remain at constant risk due to the vulnerabilities introduced by Internet of Things IoT devices. The limited computational resources of these devices make them especially susceptible to attacks, while their widespread adoption increases the potential impact of...

Centralized Vs. Decentralized Security for Space AI Systems? A New Look

This paper investigates the trade-off between centralized and decentralized security management in constellations of satellites to balance security and performance. We highlight three key AI architectures for automated security management: a centralized, b distributed and c federated. The...

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...

Adaptive Network Security Policies Via Belief Aggregation and Rollout

Evolving security vulnerabilities and shifting operational conditions require frequent updates to network security policies. These updates include adjustments to incident response procedures and modifications to access controls, among others. Reinforcement learning methods have been proposed for...

Quantum Blockchain Survey: Foundations, Trends, and Gaps

Quantum computing poses fundamental risks to classical blockchain systems by undermining widely used cryptographic primitives. In response, two major research directions have emerged: post-quantum blockchains, which integrate quantum-resistant algorithms, and quantum blockchains, which leverage...

Quantum-Resilient Privacy Ledger (QRPL): a Sovereign Digital Currency for the Post-Quantum Era

The emergence of quantum computing presents profound challenges to existing cryptographic infrastructures, whilst the development of central bank digital currencies CBDCs has raised concerns regarding privacy preservation and excessive centralisation in digital payment systems. This paper propose...

Cascade: Token-Sharded Private LLM Inference

As LLMs continue to increase in parameter size, the computational resources required to run them are available to fewer parties. Therefore, third-party inference services -- where LLMs are hosted by third parties with significant computational resources -- are becoming increasingly popular...

Static Analysis for Detecting Transaction Conflicts in Ethereum Smart Contracts

Ethereum smart contracts operate in a concurrent environment where multiple transactions can be submitted simultaneously. However, the Ethereum Virtual Machine EVM enforces sequential execution of transactions within each block to prevent conflicts arising from concurrent access to the same state...

[SECURITY] Fedora 41 Update: trafficserver-9.2.11-1.fc41

Traffic Server is a high-performance building block for cloud services. It's more than just a caching proxy server; it also has support for plugins to build large scale web applications. Key features: Caching - Improve your response time, while reducing server load and bandwidth needs by caching...

[SECURITY] Fedora 42 Update: trafficserver-10.0.6-1.fc42

Traffic Server is a high-performance building block for cloud services. It's more than just a caching proxy server; it also has support for plugins to build large scale web applications. Key features: Caching - Improve your response time, while reducing server load and bandwidth needs by caching...

ZKPROV: a Zero-Knowledge Approach to Dataset Provenance for Large Language Models

As the deployment of large language models LLMs grows in sensitive domains, ensuring the integrity of their computational provenance becomes a critical challenge, particularly in regulated sectors such as healthcare, where strict requirements are applied in dataset usage. We introduce ZKPROV, a...

Yotta: a Large-Scale Trustless Data Trading Scheme for Blockchain System

Data trading is one of the key focuses of Web 3.0. However, all the current methods that rely on blockchain-based smart contracts for data exchange cannot support large-scale data trading while ensuring data security, which falls short of fulfilling the spirit of Web 3.0. Even worse, there is...

The Trip to ZigBee Backscatter across a Decade, a Systematic Review

The field of backscatter communication has undergone a profound transformation, evolving from a niche technology for radio-frequency identification RFID into a sophisticated paradigm poised to enable a truly battery-free Internet of Things IoT. This evolution is built upon a deepening understandi...

CVE-2025-48886

Hydra is a layer-two scalability solution for Cardano. Prior to version 0.22.0, the process assumes L1 event finality and does not consider failed transactions. Currently, Cardano L1 is monitored for certain events which are necessary for state progression. At the moment, Hydra considers those...

CVE-2025-48886 hydra-node dangerously assumes L1 event finality and does not consider failed transactions

Hydra is a layer-two scalability solution for Cardano. Prior to version 0.22.0, the process assumes L1 event finality and does not consider failed transactions. Currently, Cardano L1 is monitored for certain events which are necessary for state progression. At the moment, Hydra considers those...