# Privacy Framework for the Development of IoT-Based Systems
## 6 Proposal of Privacy Guidelines
### Proposal
#### 6.3.3 Proposal Part 3: Automated Privacy Enforcement in IoTS
Context-Awareness and PrivacyThe concept of context awareness, first introduced in 1994 [49], has evolved significantly, with several researchers providing domain-specific definitions. In the realm of IoT security, context awareness is described as the ability of a system to detect, sense, interpret, and respond to aspects of a user's environment and computing devices. This is especially important in IoTS, where the security and privacy requirements of users must adapt to varying contexts such as location (e.g., home, office, workplace) [50]. In this sense, context-based security involves explicitly considering context in the specification of security solutions such as access control models and cryptographic protocols. These solutions must incorporate mechanisms that dynamically adjust to the user's environment, ensuring that the IoT system continuously protects the user's privacy and security. Thus, enhancing the overall effectiveness and appropriateness of security measures based on the user's current situation. For example, rule-based strategies are employed in context-aware privacy enforcement to make automatic decisions based on predefined rules that govern system behavior across different contexts. These systems can enforce privacy policies without manual intervention, making them efficient and responsive. Additionally, they can be integrated with other technologies, such as ML, to adapt to changing user behaviors and dynamic environments over time. An illustrative example is the Privacy Oracle, introduced by [PERSON] et al. [51]. This context-aware approach helps users safeguard their privacy by identifying risks in real time. It utilizes semantic user environment modeling (SUEM) ontologies to represent and update user information and environmental data. Privacy risks are dynamically inferred through a reasoning process based on a set of privacy rules. Blockchain for Privacy ManagementIn the realm of IoT, secure data storage is often achieved through cloud-based solutions, where differential privacy mechanisms are employed to ensure confidentiality and protect user data against unauthorized access [52]. To strengthen access control in such distributed environments, [PERSON] et al. [52] proposed a dynamic and lightweight attribute-based access control framework specifically designed for blockchain-enabled IoT systems. This framework leverages decentralizedapplications to maintain tamper resistance and accommodate delay-sensitive applications, offering fine-grained authorization while reducing central dependencies. Complementing this, [PERSON] et al. [53] emphasized the importance of decentralization in enhancing privacy and transparency through blockchain technologies. Blockchain has been increasingly integrated across various IoT applications--ranging from sensor networks and data storage to identity management, timestamp services, and supply chain monitoring--bringing forth enhanced transparency, security, credibility, and operational efficiency. These contributions collectively demonstrate the growing reliance on blockchain-based solutions to address the privacy and security challenges in IoT ecosystems [48]. This highlights the importance of implementing blockchain-based solutions in a well-considered and monitored manner to prevent potential performance issues in resource-constrained IoT environments, while ensuring adherence to established security and privacy standards.