Access Control for Emerging Distributed Systems

Area of Science:

• Computer Science
• Information Technology
• Cybersecurity

Background:

• Emerging technologies like BigData, Cloud, Grid, and the Internet of Things (IoT) are fundamentally altering data systems.
• There is a growing interest among IT professionals in utilizing distributed systems for enhanced security and fraud prevention.

Purpose of the Study:

• To investigate how the capabilities of massive distributed systems can be optimized for improved data processing.
• To explore methods for harnessing distributed systems to mitigate, rather than increase, security risks and potential fraud.

Main Methods:

• Analysis of distributed system architectures.
• Review of current security and fraud prevention strategies in BigData, Cloud, Grid, and IoT environments.
• Exploration of risk management frameworks for large-scale data processing.

Main Results:

• Identified key architectural patterns in distributed systems that facilitate efficient data processing.
• Highlighted specific security vulnerabilities and fraud vectors unique to massive distributed environments.
• Proposed strategies for integrating security measures seamlessly into distributed data workflows.

Conclusions:

• Massive distributed systems offer significant potential for enhancing data processing efficiency and security.
• Proactive risk management and tailored security protocols are essential for preventing fraud in these systems.
• Further research is needed to develop robust, scalable solutions for secure distributed data management.