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| en:iot-open:security_and_privacy_in_iot_ume:iot_privacy [2017/10/25 18:41] – kap2fox | en:iot-open:security_and_privacy_in_iot_ume:iot_privacy [2020/07/20 12:00] (current) – external edit 127.0.0.1 | ||
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| - | ====== | + | ===== ===== |
| + | <box # | ||
| + | <box # | ||
| + | ===== IoT Privacy | ||
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| - | Protecting consumer privacy becomes increasingly | + | Protecting consumer privacy becomes increasingly |
| - | Control can be lost if someone hacks into the smartphone or computer acting as a remote for the other devices. In the case of computers and smartphones, | + | Control can be lost if someone hacks into the smartphone or computer acting as a remote for the other devices. In the case of computers and smartphones, |
| - | In another sense, control can be lost as more and more companies collect data about users. This data often paints a detailed picture of individual users through the collection of activities online. Everything you search, all of your activities online, are being tracked by companies that use that data. These companies often use the data to improve the user's experience, but they also use this data to sell users products or sell to other companies who sell users products. | + | In another sense, control can be lost as more and more companies collect data about users. This data often paints a detailed picture of individual users through the collection of activities online. Everything you search, all of your activities online, are being tracked by companies that use that data ((Arijit Ukil, Soma Bandyopadhyay, |
| - | Innovation in this realm means that companies must alter the privacy policies that are in place as well as how they interact with these devices. Companies will need to take another look at the policies that they have in place to ensure that consumers are offered opportunities to access and control their own data. Consumers will become increasingly aware of the privacy implications of this level of connectivity through interaction with the IoT and exposure to the policies that companies provide to them. | + | Innovation in this realm means that companies must alter the privacy policies that are in place as well as how they interact with these devices. Companies will need to take another look at the policies that they have in place to ensure that consumers are offered opportunities to access and control their data. Consumers will become increasingly aware of the privacy implications of this level of connectivity through interaction with the IoT and exposure to the policies that companies provide to them. |
| - | Frank Pasquale, law professor and EPIC advisory board member discusses privacy concerns related to the IoT in a May 2014 Pew Research Report. Pasquale states that the expansion of the IoT will result in a world that is more "prison-like" | + | Frank Pasquale, law professor and EPIC advisory board member |
| - | EPIC President, Marc Rotenberg, explains in the Pew Research Report that the problem with the IoT is that "users are just another category of things," | + | EPIC President, Marc Rotenberg, explains in the Pew Research Report that the problem with the IoT is that “users are just another category of things,” and states that this “is worth thinking about more deeply about in the future.” |
| - | There are many actual | + | There are many real issues with IoT privacy, and all of them must be in detailed explored, but here are general ways **IoT developers can improve IoT privacy**((https:// |
| - | __Minimize | + | **Minimize |
| - | Software | + | software |
| - | __Minimize | + | **Minimize |
| - | Aggregation | + | aggregation |
| - | __Minimize | + | **Minimize |
| - | Raw data could lead to secondary usage and privacy violation. Therefore, IoT platforms should consider converting or transforming raw data into secondary context data. | + | raw data could lead to secondary usage and privacy violation. Therefore, IoT platforms should consider converting or transforming raw data into secondary context data. |
| - | __Minimize | + | **Minimize |
| IoT applications should discover only the knowledge necessary to achieve their primary objectives. For example, if the objective is to recommend food plans, the app should not attempt to infer users’ health status without their explicit permission. | IoT applications should discover only the knowledge necessary to achieve their primary objectives. For example, if the objective is to recommend food plans, the app should not attempt to infer users’ health status without their explicit permission. | ||
| - | __Minimize | + | **Minimize |
| - | Raw data should be deleted once secondary context is derived. | + | raw data should be deleted once a secondary context is derived. |
| - | __Minimize | + | **Minimize |
| - | Longer | + | more extended |
| - | __Support | + | **Support |
| - | To make it more difficult for internet activities to be traced back to the users, this guideline suggests that IoT applications should support and employ an anonymous | + | to make it more difficult for internet activities to be traced back to the users, this guideline suggests that IoT applications should support and employ an unknown |
| - | __Anonymize data__ | + | **Anonymize data**: |
| - | Remove | + | remove |
| - | __Encrypt | + | **Encrypt |
| - | Typically, device-to-device communications are encrypted at the link layer using special | + | typically, device-to-device communications are encrypted at the link layer using specialised |
| - | __Encrypt | + | **Encrypt |
| - | Sometimes | + | sometimes |
| - | __Encrypt | + | **Encrypt |
| - | Encrypted | + | encrypted |
| - | __Reduce | + | **Reduce |
| - | IoT applications should request the minimum level of granularity that is required to perform their primary tasks. A higher level of granularity could lead to secondary data usage and eventually privacy violations. For example, location can be coarse-based on cell tower location or fine-based on address. | + | IoT applications should request the minimum level of granularity that is required to perform their primary tasks. A higher level of granularity could lead to secondary data usage and eventually, privacy violations. For example, location can be coarse, based on cell tower location or fine, based on the address. |
| - | __Query answering__ | + | **Query answering**: |
| - | Raw data can lead to identification and privacy violations due to secondary usage. Instead of providing a numeric response to a query a relative scale, e.q. 1 - 5 should be used. | + | raw data can lead to identification and privacy violations due to secondary usage. Instead of providing a numeric response to a query a relative scale, e.q. 1–5 should be used. |
| - | __Block | + | **Block |
| - | Query responses should block multiple queries that maliciously could discover knowledge that violates user privacy, such as analyzing | + | query responses should block multiple queries that maliciously could discover knowledge that violates user privacy, such as analysing |
| - | __Distribute | + | **Distribute |
| - | Distributed | + | distributed |
| - | __Distribute | + | **Distribute |
| - | Distributed | + | distributed |
| - | __Knowledge | + | **Knowledge |
| - | New knowledge, such as the visitors to the park were young students during a time period, is sufficient for a gift shop to perform time series sales analysis. But the exact timing of their movement is not necessary. | + | new knowledge, such as the visitors to the park were young students during a time period, is sufficient for a gift shop to perform time series sales analysis. But the exact timing of their movement is not necessary. |
| - | __Aggregate | + | **Aggregate |
| - | Geographic | + | geographic |
| - | __Aggregate | + | **Aggregate |
| - | Energy | + | energy |
| - | __Aggregate | + | **Aggregate |
| - | Aggregating | + | aggregating |
| - | __Disclose | + | **Disclose |
| - | Data subjects should be adequately informed whenever data they own is acquired, processed or disseminated. | + | data subjects should be adequately informed whenever data they own is acquired, processed or disseminated. |
| - | __Apply controls__ | + | **Apply controls**: |
| - | It is the software architects’ responsibility to consider what kind of controls are useful to data owners, especially when data owners are not knowledgeable. Some of the considerations: | + | it is the software architects’ responsibility to consider what kind of controls are useful to data owners, especially when data owners are not knowledgeable. Some of the considerations: |
| + | 1) data granularity; 2) anonymisation | ||
| - | __Log events__ | + | **Log events**: |
| - | Logging | + | logging |
| - | __Perform | + | **Perform regularly |
| - | Systematic | + | regular, |
| - | __Make | + | **Make |
| - | Wherever | + | wherever |
| - | __Use data flow diagrams__ | + | **Use data flow diagrams**: |
| - | Data flow diagrams used by unified | + | data flow diagrams used by unified |
| - | __Get IoT apps certified__ | + | **Get IoT apps certified**: |
| - | Certifications | + | certifications |
| - | + | ||
| - | __Use industry standards__ | + | |
| - | Industry-wide standards such as AllJoyn and the All Seen Alliance typically inherit security measures that would reduce some privacy risks. | + | |
| - | + | ||
| - | __Comply with policies and regulations__ | + | |
| - | Adherence to policies, laws, and regulations such as ISO 29100, OECD privacy principles and the European Commission’s rules on the protection of personal data will reduce privacy risks. | + | |
| + | **Use industry standards**: | ||
| + | industry-wide standards such as AllJoyn and the All Seen Alliance typically inherit security measures that would reduce some privacy risks. | ||
| + | **Comply with policies and regulations**: | ||
| + | adherence to policies, laws, and regulations such as ISO 29100, OECD privacy principles and the European Commission’s rules on the protection of personal data will reduce privacy risks. | ||