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CSCI E11 (The Frontiers of Computer Science) Big data, IoT, and Cybersecurity is an online course on computer science taught for Harvard Extension School by professors from MIT.

Course and Big Data Introduction

Sam Madden presents an introduction to Big Data, its Challenges, and a few research case studies. Daniela Rus also presents case studies particularly relevant to Transportation.

Big Data Collection

Michael Stonebraker talks about tackling the problem of ingesting and integrating disparate data sources into a single unified data set that can be accessed and queried. After that, Matei Zaharia discusses how cloud infrastructure can be used to store and process Big Data.

Big Data Storage

Michael Stonebraker, Matei Zaharia and Sam Madden talk about data storing processing technologies that have been developed to process Big Data.

Big Data Systems

Additional aspects of managing Big Data are presented, including security and multicore scalability from Nickolai Zeldovich and user interfaces and visualization from Professor David Karger.

Big Data Analytics

Big data analytics presents several algorithms and machine learning techniques that can be used to extract patterns, trends, and insights from data. Case studies on Information Summarization by Regina Barzilay and Applications in the Medical Field by John Guttag.

Internet of Things Introduction and Architectures

Professor Sanjay Sarma introduces the world of the Internet of Things and an in-depth look at RFID technologies. Professor Tim Berners-Lee discusses the differences between the Internet of Things and the Web of Things. Considerations on Security issues of IoT devices as well as current techniques used to keep these devices secure. Professor David D. Clark presents his knowledge of how the Internet influences the Internet of things and lessons learned from the Internet that are still relevant when considering other devices in the Internet of Things.

IoT Technologies Part 1

Hari Balakrishnan talks about the complexity of connecting IoT devices, communication between devices, how robust these communication systems are, and how power-intensive various communication methods are. Data returns as Sam Madden shares his insight into data processing and storage challenges in IoT systems. Professor Rus introduces IoT localization, how devices find their location and orientation, and how accurate those readings can be. She presents some algorithms and techniques to reduce noise and uncertainty in determining a device's location.

IoT Technologies Part 2

Professor Srini Devadas discusses security procedures and security issues in IoT devices, presenting the types of defense needed in security - preventing an attack, dealing with a current attack, and detecting and recovering from an attack if the attack had already occurred. Dr. Jim Glass talks about human-computer interaction with IoT devices. Graphical interfaces, hardware interfaces, other ways to interact with IoT devices, and the challenges of interacting with IoT devices. Professor John Leonard talks about robots and autonomous vehicles using IoT technologies and protocols. Also, how autonomous vehicles use localization and mapping to determine the type of environment they are in and how robots keep track of their state. Different levels of autonomy are discussed, some current advances in autonomous robots, and what kind of autonomy we can look forward to seeing in the future! This unit ends with papers on how IoT can help in the COVID-19 pandemic. Contact tracing is discussed as a method for which IoT systems can help reduce the spread of the disease. This section also features an article regarding Professor Subirana's work on detecting COVID-19 positive individuals through smartphone-recorded coughs!

IoT Applications and Conclusion

Joe Paradiso talks about ubiquitous sensing and the human experience covering sensor measuring, storing, and transmitting data from almost everywhere in daily life and technologies that allow remote monitoring and sensory projection into distant areas and regions. Dina Katabi covers wireless technologies for indoor localization, smart homes, and health. Carlo Ratti shares some of his research on smart cities. IoT can help future urban planning exercises and have a direct impact on urban comfort. He will discuss how big data can be harvested from cities and the people in them and how such data can be used to transform and improve a city. Professor Sanjay Sarma will return to show a roadmap of IoT and reinforce topics discussed throughout the IoT section of the course. He will add some thoughts for the future of IoT and its applications, such as business opportunities and avenues for IoT integration into everyday life. The paper by Professor Brian Subirana will suggest a voice name system for IoT objects. As voice-activated IoT systems continue to rise in popularity, it may be necessary to standardize ways to call upon and access these services and devices.

Cybersecurity Intro

Howard Shrobe provides an introduction to cybersecurity and an overview of the different contributions in the cybersecurity unit. Then Professor Srini Devedas describes cybersecurity, its challenges with a focus on attacks and defenses. He describes why security is a complex problem and the diversity of threat models that designers and attackers have at their disposal to reaffirm that security is nearly impossible to achieve. He concludes with the prevention, resilience under attack, and the detection and recovery from an attack.

Systems Security

In this module, system security is presented, which studies the security and vulnerabilities of individual computers. Professor Shrobe returns to discuss the use of hardware architectures to enforce fundamental security principles. Then, Professor Frans Kaashoek explores how to build secure operating systems. Later, Professor Adam Chlipala talks about using mathematical logic to provide formal proofs of a system's security properties. Finally, Professor Armando SolarLezama examines how programming language design guarantees that applications will respect fundamental security properties.

Cryptography and Network

In this module, cryptography and the extent of its use in avoiding malicious attacks are introduced and its critical role in the construction of secure systems, the protection of confidentiality and integrity of data, and building secure networks. Ron Rivest and Shafi Goldwasser give lectures on the basics of modern public-key cryptography, more advanced topics on zero-knowledge proofs, secret sharing, and distributed trust. Professor Vinod Vaikuntanathan, a leader in fully homomorphic encryption, explains this concept and illustrates related ideas such as functional encryption. Finally, Professor David Clark discusses network security and protocol design.

Cybersecurity Case Studies

In this module, actual attempts to build valuable and secure systems are examined by analyzing several case studies illustrating how one can design or fail to design a secure approach in various domains. Professor Nickolai Zeldovich describes the design of BitLocker. Then Professor Martin Reinhard explores how to design resilient systems to detect, diagnose, and recover from attacks. Finally, Professor Daniel Jackson explores web security. Finally, Professor Zeldovich returns to examine decisions made in designing the security infrastructure of mobile phone systems.

Cybersecurity Policy

Notable people

The lead instructor is Harvard University and MIT professor Brian Subirana and Teaching Assistant David Anderton-Yang. The following notable people give some of the lectures.

References

^[1] ^[2] ^[3] ^[4] ^[5] ^[6] ^[7] ^[8]

^ Bastani, F., He, S., Jagwani, S., Park, E., Abbar, S., Alizadeh, M., Balakrishnan, H., Chawla, S., Madden, S. and Sadeghi, M.A., 2019. Inferring and Improving Street Maps with Data-Driven Automation. arXiv preprint arXiv:1910.04869
^ Amini, A., Soleimany, A.P., Schwarting, W., Bhatia, S.N. and Rus, D., 2019, January. Uncovering and mitigating algorithmic bias through learned latent structure. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (pp. 289-295).
^ Dean, Jeffrey, Ghemawat, Sanjay MapReduce: Simplified Data Processing on Large Clusters
^ Kallman, Kimura, Natkings, Pavlo, Rasin, Zdonik, Jones, Madden, Stonebraker, Zhang H-Store: A High-Performance, Distributed Main Memory Transaction Processing System
^ Jones, Abadi, Madden Low Overhead Concurrency Control for Partitioned Main Memory Databases
^ Curino, Jones, Zhang, Madden Schism: a Workload-Driven Approach to Database Replication and Partitioning
^ Tu, Zheng, Kohler, Liskov, Madden Speedy Transactions in Multicore In-Memory Databases
^ Brian Subirana. 2020. Call for a wake standard for artificial intelligence. Commun. ACM 63, 7 (July 2020), 32–35.

[1] Bastani, F., He, S., Jagwani, S., Park, E., Abbar, S., Alizadeh, M., Balakrishnan, H., Chawla, S., Madden, S. and Sadeghi, M.A., 2019. Inferring and Improving Street Maps with Data-Driven Automation. arXiv preprint arXiv:1910.04869

[2] Amini, A., Soleimany, A.P., Schwarting, W., Bhatia, S.N. and Rus, D., 2019, January. Uncovering and mitigating algorithmic bias through learned latent structure. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (pp. 289-295).

[3] Dean, Jeffrey, Ghemawat, Sanjay MapReduce: Simplified Data Processing on Large Clusters

[4] Kallman, Kimura, Natkings, Pavlo, Rasin, Zdonik, Jones, Madden, Stonebraker, Zhang H-Store: A High-Performance, Distributed Main Memory Transaction Processing System

[5] Jones, Abadi, Madden Low Overhead Concurrency Control for Partitioned Main Memory Databases

[6] Curino, Jones, Zhang, Madden Schism: a Workload-Driven Approach to Database Replication and Partitioning

[7] Tu, Zheng, Kohler, Liskov, Madden Speedy Transactions in Multicore In-Memory Databases

[8] Brian Subirana. 2020. Call for a wake standard for artificial intelligence. Commun. ACM 63, 7 (July 2020), 32–35.

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