Course description

In this course, we review use cases and challenges of three interrelated areas in computer science: big data, the internet of things, and cybersecurity. Students gain an overview of the possibilities and challenges of building complex information systems that take advantage of recent advances in these fields. The course is divided into three parts, each presented by leading MIT experts in their field. The first part surveys state-of-the-art topics in big data: data collection (smartphones, sensors, the web), data storage and processing (scalable relational databases, Hadoop, Spark), extracting structured data from unstructured data, systems issues (exploiting multicore processors, security), analytics (machine learning, data compression, efficient algorithms), visualization, and a range of applications. In this first part students learn to distinguish big data (volume, velocity, variety), learn where it comes from, and the key challenges in gathering and using it; determine how and where big data challenges arise in a number of domains, including social media, transportation, finance, and medicine; investigate multicore challenges and how to engineer around them; explore the relational model, SQL, and capabilities of new relational systems in terms of scalability and performance; understand the capabilities of NoSQL systems, their capabilities and pitfalls, and how the NewSQL movement addresses these issues; and maximize the MapReduce programming model: its benefits, how it compares to relational systems, and new developments that improve its performance and robustness. The second part of the course looks at the internet of things (IoT). While the promise of the IoT brings many new business prospects, it also presents significant challenges ranging from technology architectural choices to security concerns. This part of the course offers important insights on how to overcome these challenges and thrive in this exciting space. The concept of IoT has begun to make an impact in industries ranging from industrial systems to home automation to healthcare. MIT researchers continue to conduct ground-breaking research on topics that are presented ranging from RFID to cloud technologies, from sensors to the world wide web. The third and final part of the course covers cybersecurity issues related to hardware, software, cryptography, and policy to make better, safer decisions. Topics include systems (secure architectures, network security, secure programming languages, system verification); algorithmic solutions (public key cryptography, multi-party computation, secret sharing, distributing trust, computing on encrypted data); public policy issues in cybersecurity; and case studies (BitLocker, web security, mobile phone security).


  • Director, Auto-ID Laboratory, Massachusetts Institute of Technology
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