A Lightweight Federated Learning Approach for Privacy-Preserving Botnet Detection in IoT

The rapid growth of the Internet of Things IoT has expanded opportunities for innovation but also increased exposure to botnet-driven cyberattacks. Conventional detection methods often struggle with scalability, privacy, and adaptability in resource-constrained IoT environments. To address these...

SoK: Systematic Analysis of Adversarial Threats against Deep Learning Approaches for Autonomous Anomaly Detection Systems in SDN-IoT Networks

Integrating SDN and the IoT enhances network control and flexibility. DL-based AAD systems improve security by enabling real-time threat detection in SDN-IoT networks. However, these systems remain vulnerable to adversarial attacks that manipulate input data or exploit model weaknesses,...

SandCell: Sandboxing Rust beyond Unsafe Code

Rust is a modern systems programming language that ensures memory safety by enforcing ownership and borrowing rules at compile time. While the unsafe keyword allows programmers to bypass these restrictions, it introduces significant risks. Various approaches for isolating unsafe code to protect...

Multi-Channel Secure Communication Framework for Wireless IoT (MCSC-WoT): Enhancing Security in Internet of Things

In modern smart systems, the convergence of the Internet of Things IoT and Wireless of Things WoT have been revolutionized by offering a broad level of wireless connectivity and communication among various devices. Hitherto, this greater interconnectivity poses important security problems,...

Revisiting Third-Party Library Detection: a Ground Truth Dataset and Its Implications across Security Tasks

Accurate detection of third-party libraries TPLs is fundamental to Android security, supporting vulnerability tracking, malware detection, and supply chain auditing. Despite many proposed tools, their real-world effectiveness remains unclear.We present the first large-scale empirical study of ten...

NodeShield: Runtime Enforcement of Security-Enhanced SBOMs for Node.Js

The software supply chain is an increasingly common attack vector for malicious actors. The Node.js ecosystem has been subject to a wide array of attacks, likely due to its size and prevalence. To counter such attacks, the research community and practitioners have proposed a range of static and...

CAN Networks Security in Smart Grids Communication Technologies

The rapid evolution of smart grids requires effective communication protocols to transfer data reliably and securely. Controller Area Network CAN is one of the most recognized protocols that offer reliable data transmission in smart grids due to its robustness, real-time capabilities, and...

Obfuscated Quantum and Post-Quantum Cryptography

In this work, we present an experimental deployment of a new design for combined quantum key distribution QKD and post-quantum cryptography PQC. Novel to our system is the dynamic obfuscation of the QKD-PQC sequence of operations, the number of operations, and parameters related to the operations...

Secure Development of a Hooking-Based Deception Framework against Keylogging Techniques

Keyloggers remain a serious threat in modern cybersecurity, silently capturing user keystrokes to steal credentials and sensitive information. Traditional defenses focus mainly on detection and removal, which can halt malicious activity but do little to engage or mislead adversaries. In this pape...

SenseCrypt: Sensitivity-Guided Selective Homomorphic Encryption for Joint Federated Learning in Cross-Device Scenarios

Homomorphic Encryption HE prevails in securing Federated Learning FL, but suffers from high overhead and adaptation cost. Selective HE methods, which partially encrypt model parameters by a global mask, are expected to protect privacy with reduced overhead and easy adaptation. However, in...

Per-Element Secure Aggregation against Data Reconstruction Attacks in Federated Learning

Federated learning FL enables collaborative model training without sharing raw data, but individual model updates may still leak sensitive information. Secure aggregation SecAgg mitigates this risk by allowing the server to access only the sum of client updates, thereby concealing individual...

undertow: potential security issue in flow control over HTTP/2 may lead to DOS(incomplete fix for CVE-2021-3629)

A flaw was found in Undertow. A potential security issue in flow control handling by the browser over HTTP/2 may cause overhead or a denial of service in the server...

Verifiable Unlearning on Edge

Machine learning providers commonly distribute global models to edge devices, which subsequently personalize these models using local data. However, issues such as copyright infringements, biases, or regulatory requirements may require the verifiable removal of certain data samples across all edg...

SecurityLingua: Efficient Defense of LLM Jailbreak Attacks Via Security-Aware Prompt Compression

Large language models LLMs have achieved widespread adoption across numerous applications. However, many LLMs are vulnerable to malicious attacks even after safety alignment. These attacks typically bypass LLMs' safety guardrails by wrapping the original malicious instructions inside adversarial...

Excessive Reasoning Attack on Reasoning LLMs

Recent reasoning large language models LLMs, such as OpenAI o1 and DeepSeek-R1, exhibit strong performance on complex tasks through test-time inference scaling. However, prior studies have shown that these models often incur significant computational costs due to excessive reasoning, such as...

Detecting Hardware Trojans in Microprocessors via Hardware Error Correction Code-based Modules

Software-exploitable Hardware Trojans HTs enable attackers to execute unauthorized software or gain illicit access to privileged operations. This manuscript introduces a hardware-based methodology for detecting runtime HT activations using Error Correction Codes ECCs on a RISC-V microprocessor...

Quantum Enhanced Entropy Pool for Cryptographic Applications and Proofs

This paper investigates the integration of quantum randomness into Verifiable Random Functions VRFs using the Ed25519 elliptic curve to strengthen cryptographic security. By replacing traditional pseudorandom number generators with quantum entropy sources, we assess the impact on key security and...

Regular Expression Denial of Service (ReDoS)

Overview Affected versions of this package are vulnerable to Regular Expression Denial of Service ReDoS via the listNames function. An attacker can cause significant CPU consumption and degrade server performance by supplying a crafted regular expression and influencing the set of resource names...

Tech-ASan: Two-Stage Check for Address Sanitizer

Address Sanitizer ASan is a sharp weapon for detecting memory safety violations, including temporal and spatial errors hidden in C/C++ programs during execution. However, ASan incurs significant runtime overhead, which limits its efficiency in testing large software. The overhead mainly comes fro...

ObfusBFA: a Holistic Approach to Safeguarding DNNs from Different Types of Bit-Flip Attacks

Bit-flip attacks BFAs represent a serious threat to Deep Neural Networks DNNs, where flipping a small number of bits in the model parameters or binary code can significantly degrade the model accuracy or mislead the model prediction in a desired way. Existing defenses exclusively focus on...