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Large-scale sensor networks are being deployed in numerous application domains, and often 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 tamper with the data by introducing additional nodes in the network, or by compromising existing ones. Therefore, assuring high data trustworthiness in such a context 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 light-weight scheme to securely transmit provenance for sensor data. The proposed technique relies on in-packet Bloom filters to encode provenance. In addition, we introduce efficient mechanisms for provenance verification and reconstruction at the base station. We evaluate the proposed technique both analytically and empirically, and the results prove its effectiveness and efficiency for secure provenance encoding and decoding.