Iryo

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Iryo (IRYO) ICO Review

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Iryo is a decentralized social networking platform that is putting users privacy and satisfaction as its first priority. It is an innovative approach towards transparent and independent means of user data ownership, reward on ads and free of speech. It is the first get paid to content creation and sharing ecosystem that leveraged OCR token payments for its reward system.

Essential Information

Ico TimeUnknown – Unknown
Token NameIryo
Token SymbolIRYO
WhitepaperView Whitepaper
Website LinkHome
Minimum investment1 ETH
PlatformEOS
Soft Cap8,000,000 USD
Hard Cap26,000,000 USD

More about Iryo (IRYO) ICO:

Iryo is the world’s first participatory, blockchain driven healthcare economy built on decentralising access to medical records. We’re driving the next generation of healthcare by standardising health-data, employing zero-knowledge encryption and giving medical record ownership back to the patient.

The Iryo Network is a global repository of openEHR data. Since few people are prepared to provide their medical data to a “GoogleEHR”-type of capture and shameless reaping of all the medical data for commercial purposes, Iryo has decided to give up it’s access to plain data. Iryo perceives the medical data it holds as a “toxic asset”, because we believe that holding too much data in one place presents too large a liability risk.

The solution to managing this risk is zero-knowledge data storage which is resistant to all attacks, including state-actors or “inside jobs’’. This works by way of users encrypting their data on their mobile device(s) with a public key.

A private decryption key remains on the patient’s device. Whenever someone wants to access patient data (a doctor or researcher, for example) the patient has to approve their access. This will be done by the patient clicking “yes’’ in their IryoEHR app. This gives a re-encryption key to the doctor’s public key. You can read more under the “Private key management section” to understand the details of this process and the application to the edge cases.

According to a study published by Dell’s, the healthcare industry is expected to generate more than 500 exabytes of data with an expected annual growth rate of 48%. This presents a looming challenge in data management. Although multiple standards try to address this issue, a lot of that data is still stored inside local silos in proprietary formats. As such reusability of the data and interoperability between different actors is often too expensive or even impossible. To make our data as open and as meaningful as possible we decided to use openEHR’s approach to data modeling and exchange. At the core of openEHR are simple and exchangeable archetypes that link values to their actual meaning (blood pressure as an example). Simple and widely used archetypes can then be linked together in more complex structures to support various types of procedures required by clinics. Archetypes don’t only solve data storage problems but are also used in openEHR’s Archetype Querying Language (AQL) where archetypes can be reused in building and running extensive queries across the data. The openEHR community (in collaboration with doctors and clinicians) have been preparing specifications and collecting archetypes for the last 15 years and have already been chosen as a level of standard in nation-wide data exchange programs in some European Union countries. Taking this into consideration, we deem it the best option to manage patient data with vendor independence by using openEHR.

The Iryo Network is a global repository of openEHR data. Since few people are prepared to provide their medical data to a “GoogleEHR”-type of capture and shameless reaping of all the medical data for commercial purposes, Iryo has decided to give up it’s access to plain data. Iryo perceives the medical data it holds as a “toxic asset”, because we believe that holding too much data in one place presents too large a liability risk. The solution to managing this risk is zero-knowledge data storage which is resistant to all attacks, including state-actors or “inside jobs’’. This works by way of users encrypting their data on their mobile device(s) with a public key. A private decryption key remains on the patient’s device. Whenever someone wants to access patient data (a doctor or researcher, for example) the patient has to approve their access. This will be done by the patient clicking “yes’’ in their IryoEHR app. This gives a re-encryption key to the doctor’s public key. You can read more under the “Private key management section” to understand the details of this process and the application to the edge cases.

Whenever data on end-user devices (point three above) is updated, the other devices would connect to the API of both redundant storage nodes (points one and two above) and sync/update the encrypted data to match the local copy. Both storage nodes would provide a “blockchain proof” (cryptographic receipt) of the location of the data saved with the same hash that clients requested. Clients would validate these by asking the independent node if the data was actually put in a chain.

If the device contains more current data (which could happen when a doctor syncs health record with a more recent version), then it would only connect to one endpoint API. This would be one that is reachable – preferably the local one (point two above) in the same clinic. In this manner, read access doesn’t consume hospital internet connection.
The diversity of network topologies and endpoint reachability would allow clinics to operate even if their local network was down (as long as they can find emergency hotspot). This greatly reduces risks of access outages which could have fatal consequences.
While there could be a complete loss of data at each of these points independently, when working in unison they provide reliable and robust system redundancy.

Risks in distributed data storage systems like Filecoin, Sia, Storj, Maidsafe


The problem with distributed systems like Filecoin/Sia/Storj/MaidSafe is that they can’t protect users from attackers storing and serving all data from the single server. Attackers can pretend to be geographically distributed and collect money for all 3-5 copies (Sybil attack). Trusting devices, hospitals, and the Iryo Network to keep at least one (encrypted) copy alive offers far greater guarantees against health data loss.


Who pays for the storage in Iryo network?


All text-based data will be funded by clinics who would stake IRYO tokens and the 1% yearly inflation would be partly used to cover the cost of storage on the Iryo platform. In some cases, in order to secure the storage of additional gigabytes of raw data being generated and stored, clinics would have to stake additional tokens. If patient-users do not want to be dependent on the staking decisions of their clinics, they would have the option to stake coins themselves. This would unlock the storage for their use, and limit potential abusers. The precise staking requirement would be updated based on the real data gathered when the Iryo Network goes live. We foresee that, at scale, this would be significantly cheaper than any current decentralized storage, especially in comparison to proprietary systems that cannot be easily upgraded. The Iryo Network has distanced itself from the current fixation on “Big Data” and has chosen to rather focus on patient privacy. This alternative focus would allow the Iryo Network to scale globally, enabling it to attract more users. Because users, clinics and governments are assured data security and privacy, storing data on the Iryo platform means that the number of users willing to share their data with researchers could increase the rate of current EHR participation significantly. Open-source end-user apps would ensure that there are no secret back-doors circumventing the protection.

In actual implementation, the patient’s device will receive a silent notification which will wake up a background process to query the requested criteria i.e. female, 30-35 years old with diabetes. If a patient does not fall within the defined parameters, the silent notification disappears. It will do so without providing a report to the requester thereby keeping patient-users anonymous. If the patient meets the criteria, a notification would be shown on the patient’s device. The notification would include the name of the research institution, the justification for the query requested i.e. the aim(s) of the research, and the number of tokens available as an incentive to allow query results to be sent back.
Iryo envisions three types of opt-out, anonymous requests that present various potential implications for privacy which would require distinct user consent. These types are identified as a pseudo anonymous query, an anonymous query used for AI validation across a dataset and an anonymous query to deliver patient value.

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