A survey of Sybil attack countermeasures in IoT-based wireless sensor networks

Area of Science:

• Computer Science
• Network Security
• Wireless Sensor Networks (WSN)
• Internet of Things (IoT)

Background:

• Wireless sensor networks (WSN) are integral to emerging Internet of Things (IoT) applications, enabling ubiquitous connectivity.
• The distributed nature and routing protocols of WSNs make them vulnerable to security threats, particularly Sybil attacks.
• A Sybil attack involves an adversary creating multiple false identities or nodes to compromise network integrity.

Purpose of the Study:

• To provide a comprehensive survey of contemporary methods for defending against Sybil attacks in WSNs.
• To analyze the advantages and disadvantages of various Sybil attack mitigation techniques.
• To identify lessons learned and future research directions in WSN security.

Main Methods:

• Review and analysis of existing literature on Sybil attack countermeasures in WSNs.
• Categorization of defense mechanisms including encryption, trust-based systems, Received Signal Strength Indicator (RSSI), and artificial intelligence.
• Comparative discussion of the effectiveness and limitations of different approaches.

Main Results:

• Identified key Sybil attack countermeasures: encryption, trust, RSSI, and artificial intelligence.
• Detailed the strengths and weaknesses associated with each surveyed defense strategy.
• Highlighted the ongoing challenges and open research questions in securing WSNs against Sybil attacks.

Conclusions:

• Sybil attacks pose a significant threat to the security and reliability of wireless sensor networks.
• A combination of advanced techniques, including AI and robust encryption, shows promise for effective mitigation.
• Further research is needed to develop resilient and scalable solutions for WSN security in the evolving IoT landscape.