In this work, we considered three main data types generated in IoT: context data, continuous data, and media data, and the main contributions are:Ī stream data anonymisation method for IoT device is proposed based on k-anonymity, which is able to continuously facilitate k-anonymity over data stream in IoT scenarios. Among the arsenal of data analysis tools available, data anonymisation is highly recommended to satisfy the requirements of GDPR on the basis of the data is identifiable before sharing to third party or public. Many exciting applications in IoT, such as Facebook, Twitters, Tictok, Skyscanner, Hungryhouse, Trainline, Smart home, etc., collects key information such as user’s name, address, credit card, timeline, behaviour patterns of using apps, which may be re-associated with the data at a later time to identify personally identifying information. However, this will significantly increase the risk of data loss or accidental data breaches. Many IoT applications collect as much as data in order to improve their service and develop new products. The direct identifiers are the attributes that can directly identify a user, such as names, address, photo, etc., while the indirect identifiers are attributes that can identify a user by linking with other available dataset or information, such as ages, salary, occupations, etc. Basically, user identifiers include direct identifiers and indirect identifiers. 2019).ĭata anonymisation is a valuable privacy-preserving tool that can anonymise identifiers using removing, substituting, distorting, generalisation or aggregation, etc. Even using irreversible suppression, probably the most fail-safe method of anonymisation, the remaining data could be cross-referenced with other data sets to identify the source (Yao et al. E.g., hashed data could be de-anonymised by guessing the data until a matching hash was found. Many anonymisation techniques can be reversible. Data anonymisation does not mean it is always impossible to discover the identity of the subject. Some of this data might not directly linked to a user, privacy problems arise when information is tied to personally identifiable information (PII), including email, name, ip address, location, etc. If you live in a ‘smart home’, then daily actions, like the use of digit kitchen, temperature, clothes, etc. Virtual everything related to user, both online/offline can be tracked in the form of data, such as doctor visits, interaction with companies, browsing habits, app use, etc. In IoT scenarios, massive data being gathered and much of this data is digitised and stored online (cloud server, etc.) Although much of this is not made public, authorised accesses and the threat of hackers looking to steal data, often with malicious intent. In addition, resource limited IoT devices compromise through vulnerability can cause disclosure of critical data ( e.g., in healthcare, smart home, etc.) (Li et al. In an IoT environment, massive number of smart devices are connected that are used to gather data, this comes with security and privacy risks and the sensitive data breach might can be caused by malicious behaviours or careless. The most recent data link technologies, such as big data analytic, etc., are able to establish links between dataset created by different components in IoT (Zhang et al. The GDPR also permits businesses to collect anonymised data without consent, use it for any purpose, and store it for an indefinite time (Otgonbayar et al. It aims to simply the regulatory environment for business so both individuals and businesses can fully benefit from the digital economy. In IoT, the data anonymisation techniques are wildly used to protect sensitive information and privacy related to personally identifiable information by erasing or encryption identifiers that connect an individual to stored data.
The EU’s General Data Protection Regulation (GDPR) outlines data protection and privacy and addresses the transfer of personal data and give users more control over their personal data.
With the great potentials, there are however significant security and privacy concerns and legal issues to be aware of Zhang et al. The Internet of things (IoT) provides great promising in support a variety of IoT applications, such as healthcare, smart manufacturing, industrial 4.0, smart home, etc., which create huge volume of data that need to be processed and shared that might contain sensitive information needs to be protected before share with others (Zhao et al.
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