Award Abstract # 2247370
SaTC: CORE: Medium: Cannot Trust Anything: A Tiny TCB Architecture for Secure Containers

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK
Initial Amendment Date: July 24, 2023
Latest Amendment Date: July 21, 2024
Award Number: 2247370
Award Instrument: Continuing Grant
Program Manager: Selcuk Uluagac
suluagac@nsf.gov
 (703)292-4540
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2023
End Date: September 30, 2028 (Estimated)
Total Intended Award Amount: $1,200,000.00
Total Awarded Amount to Date: $286,784.00
Funds Obligated to Date: FY 2023 = $286,784.00
History of Investigator:
  • Gail Kaiser (Principal Investigator)
    kaiser@cs.columbia.edu
  • Jason Nieh (Co-Principal Investigator)
Recipient Sponsored Research Office: Columbia University
615 W 131ST ST
NEW YORK
NY  US  10027-7922
(212)854-6851
Sponsor Congressional District: 13
Primary Place of Performance: Columbia University
202 LOW LIBRARY 535 W 116 ST MC 4309,
NEW YORK
NY  US  10027
Primary Place of Performance
Congressional District:
13
Unique Entity Identifier (UEI): F4N1QNPB95M4
Parent UEI:
NSF Program(s): Secure &Trustworthy Cyberspace
Primary Program Source: 01002425DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002526DB NSF RESEARCH & RELATED ACTIVIT

01002627DB NSF RESEARCH & RELATED ACTIVIT

01002728DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9102, 025Z, 7924
Program Element Code(s): 806000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

The goal of this project is to protect users' sensitive data in cyber space from determined and resourceful attackers while requiring no changes to applications and no actions from users or software developers. The project's novelties lie in its rethinking of containers, which represent a piece of software that includes all resources an application needs to run across diverse computing environments. Current container technology relies on the operating system (OS) as the trusted computing base (TCB) to enforce their security guarantees. However, modern OSes like Linux are simply too large, with many vulnerabilities and places for malicious software to hide. The project re-envisions containers with a tiny TCB, small enough to be carefully checked, offering defenses even from the OS itself and third-party software. The project's broader significance and importance are its (i) enhancements to modern computing infrastructure supporting mobile, web and desktop applications even when the computer infrastructure and network have been compromised by bad actors and (ii) broadening the participation of underrepresented minorities in computing.

The project is investigating creative solutions to the hard problems of protecting and defending the confidentiality and integrity of application state, including registers, physical memory, and files, while still enabling traditional computing and networking services. The approach supports system calls and libraries that receive data from and return data to the application, without requiring modifications to the application?s source code or special configuration by developers. The project will demonstrate that this new TCB architecture provides fine-grained protection of application state against a variety of real attacks, including side-channel attacks that traditional hypervisor and container architectures cannot shield against, while still adding only modest performance overhead to real application workloads. Society will benefit as users enjoy their favorite old apps and explore trending new apps with peace of mind in their safety, privacy, and security.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Yao, Jianan and Tao, Runzhou and Gu, Ronghui and Nieh, Jason "Mostly Automated Verification of Liveness Properties for Distributed Protocols with Ranking Functions" Proceedings of the ACM on Programming Languages , v.8 , 2024 https://doi.org/10.1145/3632877 Citation Details
Ding, Yangruibo and Min, Marcus J and Kaiser, Gail and Ray, Baishakhi "CYCLE: Learning to Self-Refine the Code Generation" Proceedings of the ACM on Programming Languages , v.8 , 2024 https://doi.org/10.1145/3649825 Citation Details
Ding, Yangruibo and Peng, Jinjun and Min, Marcus J and Kaiser, Gail and Yang, Junfeng and Ray, Baishakhi "SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning" , 2024 Citation Details
Ding, Yangruibo and Steenhoek, Benjamin and Pei, Kexin and Kaiser, Gail and Le, Wei and Ray, Baishakhi "TRACED: Execution-aware Pre-training for Source Code" , 2024 https://doi.org/10.1145/3597503.3608140 Citation Details
Min, Marcus J and Ding, Yangruibo and Buratti, Luca and Pujar, Saurabh and Kaiser, Gail and Jana, Suman and Ray, Baishakhi "Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain" , 2024 Citation Details
Saieva, Anthony and Chakraborty, Saikat and Kaiser, Gail "Reinforest: Reinforcing Semantic Code Similarity for Cross-Lingual Code Search Models" , 2024 https://doi.org/10.1109/SCAM63643.2024.00026 Citation Details
Sofaer, Raphael J and David, Yaniv and Kang, Mingqing and Yu, Jianjia and Cao, Yinzhi and Yang, Junfeng and Nieh, Jason "RogueOne: Detecting Rogue Updates via Differential Data-flow Analysis Using Trust Domains" , 2024 https://doi.org/10.1145/3597503.3639199 Citation Details
Um, Daniel H and Knowles, David A and Kaiser, Gail E "Vector embeddings by sequence similarity and context for improved compression, similarity search, clustering, organization, and manipulation of cDNA libraries" Computational Biology and Chemistry , v.114 , 2025 https://doi.org/10.1016/j.compbiolchem.2024.108251 Citation Details

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