How can RF imaging security and privacy be evaluated and audited?

1 Threat models and scenarios

The first step is to identify the potential threats and scenarios that could compromise the security and privacy of RF imaging. For example, who are the adversaries, what are their capabilities and motivations, what are the attack vectors and surfaces, and what are the consequences and impacts of the attacks? Depending on the context and use case, the threats and scenarios could vary widely. For instance, a terrorist could try to smuggle a bomb through an airport RF scanner, a hacker could intercept and manipulate RF images transmitted over a network, or a voyeur could use a hidden RF camera to spy on people.

2 Security and privacy requirements

The next step is to define the security and privacy requirements that the RF imaging system or application should meet. These requirements could be based on legal, ethical, or technical standards, as well as user expectations and preferences. For example, some common security and privacy requirements are confidentiality, integrity, availability, authentication, authorization, accountability, anonymity, consent, and transparency. Depending on the context and use case, some requirements could be more important or challenging than others. For instance, ensuring confidentiality and consent for medical RF imaging could be more critical and difficult than for industrial RF imaging.

3 Security and privacy mechanisms

The third step is to implement and evaluate the security and privacy mechanisms that can address the threats and scenarios and meet the requirements. These mechanisms could be classified into three categories: preventive, detective, and corrective. Preventive mechanisms aim to prevent or deter attacks from happening, such as encryption, authentication, access control, and physical protection. Detective mechanisms aim to detect or monitor attacks that have occurred or are occurring, such as intrusion detection, anomaly detection, and auditing. Corrective mechanisms aim to recover or mitigate the damage caused by attacks, such as backup, restoration, and notification.

4 Security and privacy metrics

The fourth step is to measure and quantify the security and privacy of the RF imaging system or application using appropriate metrics. These metrics could be based on objective or subjective criteria, as well as quantitative or qualitative data. For example, some objective and quantitative metrics are error rates, false positives, false negatives, throughput, latency, and overhead. Some subjective and qualitative metrics are user satisfaction, trust, perceived risk, and perceived benefit. Depending on the context and use case, some metrics could be more relevant or reliable than others. For instance, measuring user satisfaction and trust for security screening RF imaging could be more important and challenging than for wireless communication RF imaging.

5 Security and privacy trade-offs

The fifth step is to analyze and balance the security and privacy trade-offs that arise from the design and implementation of the RF imaging system or application. These trade-offs could involve technical, economic, social, or ethical factors, as well as user needs and preferences. For example, some common security and privacy trade-offs are performance, cost, usability, functionality, and quality. Depending on the context and use case, some trade-offs could be more acceptable or unavoidable than others. For instance, sacrificing performance and cost for security and privacy could be more acceptable for medical RF imaging than for industrial RF imaging.

6 Security and privacy best practices

The final step is to follow and adopt the security and privacy best practices that can improve the security and privacy of the RF imaging system or application. These best practices could be derived from research, standards, guidelines, or experience, as well as user feedback and evaluation. For example, some common security and privacy best practices are risk assessment, security by design, privacy by design, data minimization, data protection, user education, user empowerment, and user participation. Depending on the context and use case, some best practices could be more effective or feasible than others. For instance, applying data minimization and data protection for RF imaging could be more effective and feasible for industrial RF imaging than for security screening RF imaging.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?