SRE_BBC: A Self-Adaptive Security Enabled Requirements Engineering Approach for SLA Smart Contracts in Blockchain-Based Cloud Systems

Abstract

Current blockchain-based cloud (BBC) systems have several security vulnerabilities regarding smart contracts (SC), and several attacks have been reported recently. The SC development lacks standard design processes that follow software lifecycle principles to model secure SC. Secondly, the security mechanisms in the SC are not constantly evolved to resist evolving adversary attacks. BBC systems lack self-adaptive security capability to make spontaneous decisions when adversarial attacks are encountered. To build a self-adaptive secure BBC system that follows standard software development lifecycle principles to model secure SC, we propose the so-called self-adaptive security RE_BBC framework. The framework would utilize the MAPE-BBC adaptation loop to make decisions internally based on the threat models, goal models, and service level agreement (SLA) SC security specifications. The framework identifies vulnerabilities and threats and takes precautionary measures using self-adaptive SC agents. We validated the proposed methodology theoretically and empirically, and statistically proved the research questions and hypothesis using the t-test and Mann–Whitney U test. Subsequently, we compare our proposed approach with the Security Quality Requirements Engineering approach (SQUARE). The feasibility results and the replicated study results indicate that the proposed approach outperformed the SQUARE approach in terms of artifacts quality, self-adaptive security evaluation quality, efficiency in response time, complexity, and usefulness of the proposed approach for the Healthcare Data Management (HDM) system. SC security developers can immensely benefit from our proposed methodology. They need not reengineer SC from scratch; depending on their security needs and plan, the contract can be adapted to execute a new plan.

Keywords

• security
• attacks
• vulnerabilities
• goal model
• threat model
• self-adaptation