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20182026
most citedPrecision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy

396 citations · 1.6k across the 95 of their papers we have counts for

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Showing 2025 · cs.CRShow all

7 papers · 2 filters

cs.CR2025

AdaDoS: Adaptive DoS Attack via Deep Adversarial Reinforcement Learning in SDN

Wei Shao, Yuhao Wang, Rongguang He +2

Existing defence mechanisms have demonstrated significant effectiveness in mitigating rule-based Denial-of-Service (DoS) attacks, leveraging predefined signatures and static heuris…

cs.CR2025

TELSAFE: Security Gap Quantitative Risk Assessment Framework

Sarah Ali Siddiqui, Chandra Thapa, Derui Wang +5

Gaps between established security standards and their practical implementation have the potential to introduce vulnerabilities, possibly exposing them to security risks. To effecti…

cs.CR2025

FuncVul: An Effective Function Level Vulnerability Detection Model using LLM and Code Chunk

Sajal Halder, Muhammad Ejaz Ahmed, Seyit Camtepe

Software supply chain vulnerabilities arise when attackers exploit weaknesses by injecting vulnerable code into widely used packages or libraries within software repositories. Whil…

cs.CR2025

Data Encryption Battlefield: A Deep Dive into the Dynamic Confrontations in Ransomware Attacks

Arash Mahboubi, Hamed Aboutorab, Seyit Camtepe +5

In the rapidly evolving landscape of cybersecurity threats, ransomware represents a significant challenge. Attackers increasingly employ sophisticated encryption methods, such as e…

cs.CR2025

CyberAlly: Leveraging LLMs and Knowledge Graphs to Empower Cyber Defenders

Minjune Kim, Jeff Wang, Kristen Moore +7

The increasing frequency and sophistication of cyberattacks demand innovative approaches to strengthen defense capabilities. Training on live infrastructure poses significant risks…

cs.CR2025

Setup Once, Secure Always: A Single-Setup Secure Federated Learning Aggregation Protocol with Forward and Backward Secrecy for Dynamic Users

Nazatul Haque Sultan, Yan Bo, Yansong Gao +10

Federated Learning (FL) enables multiple users to collaboratively train a machine learning model without sharing raw data, making it suitable for privacy-sensitive applications. Ho…

cs.CR2025

Provisioning Time-Based Subscription in NDN: A Secure and Efficient Access Control Scheme

Nazatul H. Sultan, Chandan Kumar, Saurab Dulal +3

This paper proposes a novel encryption-based access control mechanism for Named Data Networking (NDN). The scheme allows data producers to share their content in encrypted form bef…