In this paper, we present the design, implementation, and evaluation of a secure sensing data processing and logging system. The system is inspired and enabled by blockchain. In this system, a public blockchain is used as immutable data store to store the most critical data needed to secure the system. Furthermore, several innovative blockchain-inspired mechanisms have been incorporated into the system to provide additional security for the system's operations. The first priority in securing sensing data processing and logging is admission control, i.e., only legitimate sensing data are accepted for processing and logging. This is achieved via a sensor identification and authentication mechanism. The second priority is to ensure that the logged data remain intact overtime. This is achieved by storing a small amount of data condensed from the raw sensing data on a public blockchain. A Merkel-tree based mechanism is devised to link the raw sensing data stored off-chain to the condensed data placed on public blockchain. This mechanism passes the data immutability property of a public blockchain to the raw sensing data stored off-chain. Third, the raw sensing data stored off-chain are secured with a self-protection mechanism where the raw sensing data are grouped into chained blocks with a moderate amount of proof-of-work. This scheme prevents an adversary from making arbitrary changes to the logged data within a short period of time. Fourth, mechanisms are developed to facilitate the search of the condensed data placed on the public blockchain and the verification of the raw sensing data using the condensed data placed on the public blockchain. The system is implemented in Python except the graphical user interface, which is developed using C#. The functionality and feasibility of the system have been evaluated locally and with two public blockchain systems, one is the IOTA Shimmer test network, and the other is Ethereum.

In this paper, we present a secure datastore based on an Ethereum smart contract. Our research is guided by three research questions. First, we will explore to what extend a smart-contract-based datastore should resemble a traditional database system. Second, we will investigate how to store the data in a smart-contract-based datastore for maximum flexibility while minimizing the gas consumption. Third, we seek answers regarding whether or not a smart-contract-based datastore should incorporate complex processing such as data encryption and data analytic algorithms. The proposed smart-contract-based datastore aims to strike a good balance between several constraints: (1) smart contracts are publicly visible, which may create a confidentiality concern for the data stored in the datastore; (2) unlike traditional database systems, the Ethereum smart contract programming language (i.e., Solidity) offers very limited data structures for data management; (3) all operations that mutate the blockchain state would incur financial costs and the developers for smart contracts must make sure sufficient gas is provisioned for every smart contract call, and ideally, the gas consumption should be minimized. Our investigation shows that although it is essential for a smart-contract-based datastore to offer some basic data query functionality, it is impractical to offer query flexibility that resembles that of a traditional database system. Furthermore, we propose that data should be structured as tag-value pairs, where the tag serves as a non-unique key that describes the nature of the value. We also conclude that complex processing should not be allowed in the smart contract due to the financial burden and security concerns. The tag-based secure datastore designed this way also defines its applicative perimeter, i.e., only applications that align with our strategy would find the proposed datastore a good fit. Those that would rather incur higher financial cost for more data query flexibility and/or less user burden on data pre- and post-processing would find the proposed database too restrictive.