Provenance Forgery and Packet Drop Attacks Detection in Wireless Networks

Abstract

Large-scale sensor networks are deployed in numerous application domains, and the data they collect are
used in decision-making for critical infrastructures. Data are streamed from multiple sources through intermediate
processing nodes that aggregate information. A malicious adversary may introduce additional nodes in the network or
compromise existing ones. Therefore, assuring high data trustworthiness is crucial for correct decision-making. Data
provenance represents a key factor in evaluating the trustworthiness of sensor data. Provenance management for sensor
networks introduces several challenging requirements, such as low energy and bandwidth consumption, efficient storage
and secure transmission. In this paper, we propose a novel lightweight scheme to securely transmit provenance for
sensor data. The proposed technique relies on in packet Bloom filters to encode provenance. We introduce efficient
mechanisms for provenance verification and reconstruction at the base station. In addition, we extend the secure
provenance scheme with functionality to detect packet drop attacks staged by malicious data forwarding nodes. We
evaluate the proposed technique both analytically and empirically, and the results prove the effectiveness and efficiency
of the lightweight secure provenance scheme in detecting packet forgery and loss attacks.