Yuval Elovici

Senior Academic

SMuF

State machine based mutational fuzzing framework for internet of things

Neeraj Karamchandani, Vinay Sachidananda, Suhas Setikere, Jianying Zhou, Yuval Elovici

The Internet of Things (IoT) exposes vulnerabilities at various levels. In this paper, we propose a mutation-based fuzzing framework called SMuF in order to find various vulnerabilities in IoT devices. We harness the power of state machine to generate distinct states of a protocol. In addition, we also generate legitimate packets as levels and sub-levels to intelligently mutate the data fields in the packet. Our mutation technique lies in mutation based on location, context and time. We propose a probability score for selecting the inputs for fuzzing based on payload length. We implemented and evaluated the proposed framework in our IoT security testbed. Using SMuF, we have discovered various vulnerabilities such as Denial of Service (DoS), Buffer Overflow, Session Hijacking etc.

Publication language English
Pages 101-112
Publication status Published - 01.01.2019

Keywords

IoT security
Mutational fuzzing
Vulnerability discovery

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science
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Link to publication in Scopus