TitleIoT and DLT in a telecom multi carriers architecture
Status

Difficulty

  


Description 


GOAL

GSMA during 2019 is planning to investigate the characteristics and behavior of DLT for IoT applications that utilize mobile connectivity. The idea is to gain a better understanding of the benefits of using DLT and how some of the challenges of IoT, where there are a lot of stakeholders involved, can be bridged. GSMA is also looking at the interoperability with other DLT technologies. One example could be in relation to device identity, or validation of the installed firmware/software. In general, we are not looking to store actual data produced by the devices, due to privacy and data protection laws (i.e. GDPR).


SCOPE

By 2020, there will be over 24 billion connected devices, which are equipped with sensing and actuating capabilities. Obviously, considering billions of people, trillions of IoT devices, and innumerable data resources,

The Internet of Things aims at connecting every entity ranging from

The 3 major characteristics of IoT are mobility, scalability, interoperability that play at three different levels/layers: identity, connectivity and application.

Blockchain and trusted identities enable the true potential of IoT

Current needs:

The solutions:


Existing identity management systems on the Internet cannot be directly transplanted to IoT environments due to native IoT characteristics and needs such as scalability, trustless, interoperability, mobility, security and privacy

Even though many promising solutions (i.e., blockchain-based identity management and socialized IoT paradigm) are proposed, other critical supporting components of building effective IdMS for IoT remain challenges such as access controls, privacy, trust and performance.


Task 1: 1º PoC

Using Indy to building up an IdM system taking into account the needs of an IoT architecture (mobility, scalability and interoperability) and challenges (access control, privacy, trust and performance).

a - proving basic feasibility and viability

b – proving feasibility with a real system and providing viability

Task 2:

Identify the metrics to measure the performance & scalability of a decentralized IdM for IoT


Task 3: 2º PoC

a - proving scalability to bi- parties (2 carriers) and a large amount of data

c- proving privacy and confidentiality in bi- parties (2 carriers) environment

d- exploring integration with different types of data & contract types

Additional Information

Learning Objectives


Expected Outcome


Relation to Hyperledger 

Education Level

Master’s or Phd

Skills

The project mainly focuses on Hyperledger Indy. The project will also showcase how Hyperledger projects can be utilized to enable an important Telecom use case.

Future plans

Task 3: 3º PoC


Preferred Hours and Length of Internship

Full-time (20 hours a week for 12 weeks during the summer)

Mentor(s) Names and Contact Info

Laura Spinaci laura@blockchainmentoringlab.com;  lauraspinaci.biz@hotmail.com