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Blockchain integration in industries like online advertising is hindered by its connectivity limitations to off-chain data. These industries heavily rely on precise counting systems for collecting and analyzing off-chain data. This requires mechanisms, often called oracles, to feed off-chain data into smart contracts. However, current oracle solutions are ill-suited for counting systems since the oracles do not know when to expect the data, posing a significant challenge. To address this, we present CountChain, a decentralized oracle network for counting systems. In CountChain, data is received by all oracle nodes, and any node can submit a proposition request. Each proposition contains enough data to evaluate the occurrence of an event. Only randomly selected nodes participate in a game to evaluate the truthfulness of each proposition by providing proof and some stake. Finally, the propositions with the outcome of True increment the counter in a smart contract. Thus, instead of a contract calling oracles for data, in CountChain, the oracles call a smart contract when the data is available. Furthermore, we present a formal analysis and experimental evaluation of the system's parameters on over half a million data points to obtain optimal system parameters. In such conditions, our game-theoretical analysis demonstrates that a Nash equilibrium exists wherein all rational parties participate with honesty., Comment: being published at https://ieee-cybermatics.org/2024/blockchain/

In recent years we have witnessed a dramatic increase in the adoption and application of smart contracts in a variety of contexts such as decentralized finance, supply chain management, and identity management. However, a critical stumbling block to the further adoption of smart contracts is their security. A particularly widespread class of security vulnerabilities that afflicts Ethereum smart contracts is the gas limit denial of service(DoS) on a contract via unbounded operations. These vulnerabilities result in a failed transaction with an out-of-gas error and are often present in contracts containing loops whose bounds are affected by end-user input. Note that such vulnerabilities differ from gas limit DoS on the network via block stuffing. Therefore, we present Gas Gauge, a tool aimed at detecting Out-of-Gas DoS vulnerabilities in Ethereum smart contracts. Gas Gauge consists of three major components: the Detection, Identification, and Correction Phases. The Detection Phase consists of an accurate static analysis approach that finds and summarizes all the loops in a smart contract. The Identification Phase uses a white-box fuzzing approach to generate a set of inputs that causes the contract to run out of gas. The Correction Phase uses static analysis and run-time verification to predict the maximum loop bounds consistent with allowable gas usage and suggest appropriate repairs to the user of the tool. Each part of the tool can be used separately for different purposes or all together to detect, identify and help repair the contracts vulnerable to Out-of-Gas DoS vulnerabilities. Gas Gauge was tested on 1,000 real-world solidity smart contracts deployed on the Ethereum Mainnet. The results were compared to seven state-of-the-art static and symbolic tools, and it was empirically demonstrated that Gas Gauge is far more effective than competing state-of-the-art tools., Comment: 13 pages, 12 figures