University Events

Description: Topic: Anomaly Report Cycling Low Energy Adaptive Clustering Hierarchy (ARC-LEACH) for Defense in Wireless Sensor Networks (WSN)

Location: Lester Cory Conference Room, Science & Engineering Building (SENG), Room 213A

Abstract:
Wireless Sensor Networks (WSNs) allow a large area to be monitored with various sensors. WSNs, although useful, are subject to black hole attacks. Defenses against attacks typically require more energy which reduces WSN lifetime. This thesis proposes a novel approach to detect and recover from attacks using an improved version of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. LEACH is an energy efficient protocol for groups of battery- operated computers with sensor components in WSNs. This protocol works by having a node become a cluster head responsible for sending data to a sink. The sink can be either an access point or base station. After a set time the cluster heads go back to being regular nodes and a completely new set of nodes become cluster heads. There are secure versions of LEACH such as S-LEACH and MS-LEACH that provide encryption, but LEACH and its encrypted variants do not secure against black hole attacks. Our proposed approach, referred to as Anomaly Report Cycling - Low Energy Adaptive Clustering Hierarchy (ARC-LEACH), aims to provide defense from black hole attacks while also providing low energy cost. ARC-LEACH does this by absorbing an attack. When an attack occurs, it rotates cluster heads to reestablish communication, then sending a message from the sink to coordinate all nodes against the malicious nodes. ARC-LEACH actively blocks malicious nodes while leveraging the resilience of LEACH by building up stronger resistance to attacks. ARC-LEACH provides more defense capability when under attack from multiple malicious nodes that would otherwise be defenseless by LEACH, with only a limited increase in power consumption. Prototype for ARC-LEACH is implemented to show feasibility of the proposed approach.

Advisor(s):
Dr. Hong Liu, Commonwealth Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth

Committee Members:
Dr. Lance Fiondella, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
Dr. Liudong Xing, Professor & Graduate Program Director, Department of Electrical & Computer Engineering, UMASS Dartmouth
Dr. John Donahue, Information System Security Manager, Naval Undersea Warfare Center (NUWC)

https://www.umassd.edu/events/?day=16&month=11&year=2023&search=day

Zoom Conference Link: https://umassd.zoom.us/j/93281343753
Meeting ID: 932 8134 3753
Passcode: 518247

NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.

*For further information, please contact Dr. Hong Liu via email at hliu@umassd.edu