Cybersecurity@CSAIL: Creating security by default

This Initiative is designed to identify and develop technologies to address the most significant security issues confronting organizations in the next decade. Presently, approaches to system security do not give overall security guarantees, but rather attacks are fought individually - “patch and pray” style. CyberSecurity@CSAIL aims to provide an integrated and formal approach to the security of systems, combining design and analysis methods from cryptography, software and hardware. Specifically, we focus on stopping whole classes of attacks, helping systems recover from attacks more quickly, enabling systems to remain functional despite attacks, privacy and cyber policy.
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Systems That Learn: Accelerating the development, deployment and evolution of large-scale AI systems

With this Initiative, we combine expertise in systems and machine learning to create new applications for understanding complex relationships from the avalanche of data available today. STL has been created to enable cross-collaboration and accelerate development of innovative human-like systems to serve the world.
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FinTech@CSAIL will bring together industry, thought leaders, innovators, academics, disruptive technology development and start-up companies that are reinventing global financial services.
Through FINTECH@CSAIL, we will work closely with industry partners in leveraging innovation from cutting edge research to develop the next generation of impactful technologies that will open up new business models, broaden access, gain new data insights, and improve security.
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A huge part of our computing future will be wireless and mobile.

To realize that future, CSAIL researchers are developing novel solutions to four challenges: dramatic improvements in spectrum use, systems to develop and run distributed mobile applications at scale, security and privacy in the mobile world, and energy-efficient designs.

These efforts are part of the MIT Center for Wireless Networks and Mobile Computing, housed at CSAIL, whose participants also include researchers from LIDS, MTL, and RLE.
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