2.5D Root of Trust: Secure System-Level Integration of Untrusted Chiplets
September 04, 2020 Β· Declared Dead Β· π IEEE transactions on computers
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Mohammed Nabeel, Mohammed Ashraf, Satwik Patnaik, Vassos Soteriou, Ozgur Sinanoglu, Johann Knechtel
arXiv ID
2009.02412
Category
cs.CR: Cryptography & Security
Cross-listed
cs.AR
Citations
38
Venue
IEEE transactions on computers
Last Checked
6 months ago
Abstract
Dedicated, after acceptance and publication, in memory of the late Vassos Soteriou. For the first time, we leverage the 2.5D interposer technology to establish system-level security in the face of hardware- and software-centric adversaries. More specifically, we integrate chiplets (i.e., third-party hard intellectual property of complex functionality, like microprocessors) using a security-enforcing interposer. Such hardware organization provides a robust 2.5D root of trust for trustworthy, yet powerful and flexible, computation systems. The security paradigms for our scheme, employed firmly by design and construction, are: 1) stringent physical separation of trusted from untrusted components, and 2) runtime monitoring. The system-level activities of all untrusted commodity chiplets are checked continuously against security policies via physically separated security features. Aside from the security promises, the good economics of outsourced supply chains are still maintained; the system vendor is free to procure chiplets from the open market, while only producing the interposer and assembling the 2.5D system oneself. We showcase our scheme using the Cortex-M0 core and the AHB-Lite bus by ARM, building a secure 64-core system with shared memories. We evaluate our scheme through hardware simulation, considering different threat scenarios. Finally, we devise a physical-design flow for 2.5D systems, based on commercial-grade design tools, to demonstrate and evaluate our 2.5D root of trust.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Cryptography & Security
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
The Limitations of Deep Learning in Adversarial Settings
R.I.P.
π»
Ghosted
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
R.I.P.
π»
Ghosted
Spectre Attacks: Exploiting Speculative Execution
R.I.P.
π»
Ghosted
How To Backdoor Federated Learning
R.I.P.
π»
Ghosted
Evasion Attacks against Machine Learning at Test Time
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted