Smart Cities Data Security

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Updated: Oct 16, 2021
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Data and privacy challenges solutions

In this part we will briefly explain the basic building blocks for the privacy enhancing technologies that have been created over the past decades. The sort of security that PETs ensure relies upon the setting where they are utilized, for instance privacy in smart mobility, or privacy of body & mind in smart health.

Process-Oriented Privacy Protection

We start with the different privacy techniques that are used to develop the privacy –friendly systems and in most of the technologies they are applicable.

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Privacy by Design

Privacy by design is a procedure to fix the security issues in smart cities. Privacy by design has seven principles that must be followed: proactive protection insurance rather than medicinal activity after security violations have occurred; security as the default setting ;security installed into the plan; full usefulness with full protection insurance; security assurance through the whole lifecycle of the information; visibility and transparency; and respect for user privacy.

Testing and Verification

The most important part of any privacy friendly system design is privacy testing and verification to make sure that the design and implementation of the system should fulfill its privacy requirements. As per MITRE, security testing isn’t on a very basic level not the same as different kinds of testing and in this way should be consolidated into existing testing processes. Testing approaches that are explicit to security requirements target discovering information leaks from applications, for example through black box differential fuzz testing or taint tracking, for example investigation of the data stream of delicate program inputs to program outputs. The security properties of cryptographic protocols can likewise be officially confirmed utilizing formal languages e.g. the applied pi analytics, utilizing ontology’s, or utilizing model-based methodologies.

Data Minimization

As we discussed above, the information minimization can be acquire from the privacy by design concepts. In smart, data minimization has just been utilized to officially investigate structural decisions for electronic toll pricing and to determine privacy-preserving solutions for big data analysis.


Encryption preserves security by ensuring the privacy of messages or other information. Customarily, symmetric encryption requires two gatherings to have a shared encryption/decryption key, while public- key encryption permits to encrypt the messages utilizing a public key, and just the comparing private key can decode the messages. Identity- based encryption is a kind of public-key encryption where the public key can be a subjective string, for example, a client’s name or email address. This permits to encode messages for a receiver regardless of whether the receiver has not created a public/private key pair. Identity based encryption can be utilized to acknowledge private assistance disclosure.

Secure Multi-Party Computation

Secure multi-party calculation is a cryptographic technique that permits at least two gatherings to together compute the value of a public function without uncovering the parties private data sources, and without depending on a trusted third party. Secure multi-party calculations give privacy and unlink ability. They are computationally costly, yet true applications have just been accounted for, for instance to acknowledge barters where the final cost can be computed without uncovering individual offers. In smart cities, secure multi-party calculations can be utilized to plan human services arrangements, for instance to compute the consequences of genomic tests where both the patient’s genome and the test succession stay private.


Smart cities are very complicated. Different ideas, applications and advances interface to envelop each part of the computerized resident’s life. Understanding this security challenging condition is the most important and basic requirement for the development of the effective protection procedures. We examined smart cities around the globe and found that, with not many exemptions, security assurance or even data on privacy policies is still rare. Understanding this security challenging condition is the essential and basic requirement for the development of effective protection procedures. We examined smart cities around the globe and found that, with barely any special cases, security assurance or even data on protection strategies is still rare. In summary, we trust that our systematic review of privacy in smart cities will support comprehensive privacy solutions for smart cities.

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Smart cities data security. (2021, Oct 16). Retrieved from