Advanced Defense Adaptation Against Dynamic Mobile Malware Threats: Navigating Evolving Strategies

EasyChair Preprint 12753

Abstract

With the pervasive use of mobile devices in today's digital landscape, the threat of mobile malware continues to evolve, presenting challenges for effective defense strategies. This paper proposes advanced defense adaptation techniques to counter dynamic mobile malware threats by navigating evolving strategies. Through a comprehensive analysis of the mobile threat landscape, including emerging attack vectors and sophisticated evasion tactics employed by malware, this research explores innovative approaches for bolstering mobile security defenses. Leveraging proactive measures such as behavior analysis, anomaly detection, and machine learning algorithms, organizations can enhance their ability to detect and mitigate mobile malware in real-time. Additionally, this paper discusses the importance of continuous monitoring, threat intelligence sharing, and collaboration among stakeholders to stay ahead of evolving threats. By adopting a multi-layered defense approach and staying vigilant against emerging attack techniques, organizations can effectively protect their mobile ecosystems from the growing menace of mobile malware.

Keyphrases: Advanced strategies, Defense adaptation, Dynamic Threats, anomaly detection, behavior analysis, machine learning, mobile malware

@booklet{EasyChair:12753,
  author    = {Lia Don},
  title     = {Advanced Defense Adaptation Against Dynamic Mobile Malware Threats: Navigating Evolving Strategies},
  howpublished = {EasyChair Preprint 12753},
  year      = {EasyChair, 2024}}