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Secure and Smart IoT

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Secure IoT with Blockchain and Smart IoT with AI , this presentation will explore both sides of Internet of Things .

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Secure and Smart IoT

  1. 1. Secure and Smart IoT Prof. Ahmed Banafa IoT Expert | Faculty | Author | Keynote Speaker College of Engineering San Jose State University San Jose, CA USA
  2. 2. Secure IoT
  3. 3. • The Internet of Things (IoT) as a concept is fascinating and exciting, but one of the major challenging aspects of IoT is having a secure ecosystem encompassing all building blocks of IoT- architecture.
  4. 4. • Things: These are defined as uniquely identifiable nodes, primarily sensors that communicate without human interaction using different connectivity methods.
  5. 5. • Gateways: These act as intermediaries between things and the cloud to provide the needed connectivity, security, and manageability.
  6. 6. • Network infrastructure: This is comprised of routers, aggregators, gateways, repeaters and other devices that control and secure data flow.
  7. 7. • Cloud infrastructure: Cloud infrastructure contains large pools of virtualized servers and storage that are networked together with computing and analytical capabilities
  8. 8. Challenges to secure IoT deployments
  9. 9. • Many IoT Systems are poorly designed and implemented, using diverse protocols and technologies that create complex and sometimes conflicting configurations. • Limited guidance for life cycle maintenance and management of IoT devices • IoT privacy concerns are complex and not always readily evident.
  10. 10. • There is a lack of standards for authentication and authorization of IoT edge devices. • Security standards, for platform configurations, involving virtualized IoT platforms supporting multi- tenancy is immature. • The uses for Internet of Things technology are expanding and changing—often in uncharted waters.
  11. 11. • IoT security will be complicated by the fact that many "things" use simple processors and operating systems that may not support sophisticated security approaches.
  12. 12. • A prime example of the urgent need for such new security technologies is the recent massive distributed denial of service attack (DDoS) that crippled the servers of popular services like Twitter, Netflix, NYTimes, and PayPal across the U.S. on October 21st, 2016. It was the result of an immense assault that involved millions of internet addresses and malicious software. • One source of the traffic for the attacks was devices infected by the Mirai malware.
  13. 13. The Blockchain Approach
  14. 14. • Blockchain, the "distributed ledger" technology, has emerged as an object of intense interest in the tech industry and beyond.
  15. 15. What are some advantages of Blockchain?
  16. 16. • The big advantage of blockchain is that it's public. Everyone participating can see the blocks and the transactions stored in them. This doesn't mean everyone can see the actual content of your transaction, however; that's protected by your private key.
  17. 17. • A blockchain is decentralized, so there is no single authority that can approve the transactions or set specific rules to have transactions accepted. • That means there's a huge amount of trust involved since all the participants in the network have to reach a consensus to accept transactions.
  18. 18. • Most importantly, it's secure. The database can only be extended and previous records cannot be changed (at least, there's a very high cost if someone wants to alter previous records).
  19. 19. The blockchain and IoT
  20. 20. • This decentralized approach would eliminate Single Points of Failure, creating a more resilient ecosystem for devices to run on. The cryptographic algorithms used by blockchains would make consumer data more private.
  21. 21. • In an IoT network, the blockchain can keep an undisputable record of the history of smart devices. • This feature enables the autonomous functioning of smart devices without the need for centralized authority. • As a result, the blockchain opens the door to a series of IoT scenarios that were remarkably difficult, or even impossible to implement without it.
  22. 22. • In this model, the blockchain will treat message exchanges between devices similar to financial transactions in a bitcoin network. • To enable message exchanges, devices will leverage smart contracts which then model the agreement between the two parties
  23. 23. What are the challenges?
  24. 24. Challenges Facing Blockchain in IoT Scalability Processing Power and Time Storage Lack of Skills Legal and Compliance Issues
  25. 25. • Scalability issues pertaining to the blockchain that might lead to centralization, which is casting a shadow over the future of the cryptocurrency.
  26. 26. • Processing power and time required to perform encryption for all the objects involved in a blockchain-based ecosystem.
  27. 27. • Storage too will be a hurdle. Blockchain eliminates the need for a central server to store transactions and device IDs, but the ledger has to be stored on the nodes themselves. And the ledger will increase in size as time passes.
  28. 28. • Lack of skills: few people understand how blockchain technology really works and when you add IoT to the mix that number will shrink drastically.
  29. 29. • Legal and compliance issues: It's a new territory in all aspects without any legal or compliance code to follow, which is a serious problem for manufacturers and service providers.
  30. 30. Smart IoT
  31. 31. AI and IoT Data Analytics
  32. 32. There are six types of IoT Data Analysis where AI can help : • Data Preparation: Defining pools of data and clean them which will take us to concepts like Dark Data, Data Lakes.
  33. 33. • Data Discovery: Finding useful data in the defined pools of data
  34. 34. • Visualization of Streaming Data: On the fly dealing with streaming data by defining, discovering data, and visualizing it in smart ways to make it easy for the decision-making process to take place without delay.
  35. 35. • Time Series Accuracy of Data: Keeping the level of confidence in data collected high with high accuracy and integrity of data
  36. 36. • Predictive and Advance Analytics: a Very important step where decisions can be made based on data collected, discovered and analyzed
  37. 37. • Real-Time Geospatial and Location (logistical Data): Maintaining the flow of data smooth and under control.
  38. 38. Challenges facing AI in IoT
  39. 39. Challenges facing AI in IoT
  40. 40. • Compatibility: IoT is a collection of many parts and systems they are fundamentally different in time and space.
  41. 41. • Complexity: IoT is a complicated system with many moving parts and non –stop stream of data making it a very complicated ecosystem
  42. 42. • Privacy/Security/Safety (PSS): PSS is always an issue with every new technology or concept, how far IA can help without compromising PSS? One of the new solutions for such problem is using Blockchain technology.
  43. 43. • Ethical and legal Issues: It’s a new world for many companies with no precedents, untested territory with new laws and cases emerging rapidly.
  44. 44. • Artificial Stupidity: Back to the very simple concept of GIGO, AI still needs “training” to understand human reactions/emotions so the decisions will make sense.
  45. 45. Thank you! https://www.linkedin.com/in/ahmedbanafa ahmed.banafa@sjsu.edu @BanafaAhmed

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