# Privacy Framework for the Development of IoT-Based Systems
## 6 Proposal of Privacy Guidelines
### Proposal
#### 6.3.1 Proposal Part 1: Proposed Privacy Guidelines for IoTS
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline  & **Proposed Guideline** & **Mapped LINDDUN Threat(s)** & **Novelty/Comment** & **Contribution** \\ \hline
1 & Minimize Data Acquisition & Excessive Amount of Data & Same objective, rephrased as a positive design principle & Direct Mapping \\
2 & Reduce Data & Excessively Sensitive Data & Emphasizes data precision control, not explicitly covered in LINDDUN & Enhanced \\
3 & Query Answering Without Raw Data & Overex of Personal Data & Proposes concrete privacy-preserving querying mechanisms absent in LINDDUN & \\
4 & Encrypted Data & Insufficient Security of Communication & Standard mitigation directly aligned with LINDDUN & Direct Mapping \\
5 & Encrypted Data & Insufficient Security of Storage & Standard mitigation directly aligned with LINDDUN & Direct Mapping \\
6 & Data Anonymization & Excessively Sensitive Data & Adds specific anonymization strategies & Enhanced \\
7 & Minimize Data Storage & Unnecessary Data Retention & Same goal expressed as a design principle & Direct Mapping \\
8 & Automated Data Deletion & Insufficient Rectification or Erasure & Adds automation aspects not explicitly covered by LINDDUN & Enhanced \\
9 & Knowledge Discovery-Based & Unnecessary Data Analysis & Suggests novel aggregation for privacy-preserving analytics absent in LINDDUN & New \\
10 & Distributed Data Storage & Insufficient Security of Processing (Resilience Dimension) & Introduces architectural identification absent in LINDDUN & New \\
11 & Information Disclosure Disclosure & Insufficient Transparency & Same goal rephrased positively & Direct Mapping \\
12 & User Privacy Controls & Insufficient Privacy Controls, Intelligent Access & Emphasizes user-centric, dynamic control mechanisms & Enhanced \\
13 & Logging and & Improper Data Lifecycle Auditing & Adds concrete mechanisms for traceability and accountability & Enhanced \\
14 & Compliance with Privacy Regulations & Non-Compliance of Processing with Applicable Regulations, Non-Adherence to Privacy Standards & Provides explicit reference to current regulations (e.g., GDPR), extending LINDDUN’s approach & Enhanced \\
15 & Privacy by Design and Default & Non-Adherence to Privacy & Introduces proactive privacy integration across the lifecycle & New \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Mapping of proposed privacy guidelines to selected LINDDUN threats, highlighting novelty and contribution. Security of Processing_, our guideline goes further by recommending _Encrypted Data Communication_ as a practical and developer-friendly mitigation strategy. 2. **Added technical and architectural contributions:** Several guidelines extend beyond LINDDUN's scope by introducing technical implementation patterns and architectural solutions specifically tailored to IoT environments and their constraints. For instance, _Distributed Data Storage_ and _Knowledge Discovery-Based Aggregation_ explicitly address resilience and privacy-preserving analytics in distributed IoT architectures, areas not explicitly covered in LINDDUN's original formulation. 3. **Objective prioritization:** The scoring-based approach guarantees that the guidelines align with stakeholder priorities in terms of clarity, practicality, and relevance, thereby reinforcing their applicability to real-world IoT systems. 4. **Avoiding developer overload:** We have considered the cognitive burden placed on developers, recognizing that an excessive number of guidelines can lead to developer fatigue, reducing their ability to effectively implement privacy protections.