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Locking-based intellectual property (IP) protection for integrated circuits (ICs) being manufactured at untrusted facilities has been largely defeated by the satisfiability (SAT) attack, which can retrieve the secret key needed for instantiating proprietary functionality on locked circuits. As a result, redaction-based methods have gained popularity as a more secure way of protecting hardware IP. Among these methods, transistor-level programming (TRAP) prohibits the outright use of SAT attacks due to the mismatch between the logic-level at which SAT attack operates and the switch-level at which the TRAP fabric is programmed. Herein, we discuss the challenges involved in launching SAT attacks on TRAP and we propose solutions which enable expression of TRAP in propositional logic modeling in a way that accurately reflects switch-level circuit capabilities. Results obtained using a transistor-level SAT attack tool-set that we developed and are releasing corroborate that SAT attacks can be launched against TRAP. However, the increased complexity of switch-level circuit modeling prevents the attack from realistically compromising all but the most trivial IP-protected designs. 

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CRISPR-engineered physical unclonable functions establish a foundational security technology for provenance attestation protocols. 

Abstract A Physical Unclonable Function (PUF) is a security primitive that exploits inherent variations in manufacturing protocols to generate unique, random‐like identifiers. These identifiers are used for authentication and encryption purposes in hardware security applications in the semiconductor industry. Inspired by the success of silicon PUFs, herein it is leverage Terminal deoxynucleotidyl Transferase (TdT), a template‐independent polymerase belonging to the X‐family of DNA polymerases, to augment the intrinsic entropy generated during DNA lesion repair and rapidly produce genetic PUFs that satisfy the following properties: robustness (i.e., they repeatedly produce the same output), uniqueness (i.e., they do not coincide with any other identically produced PUF), and unclonability (i.e., they are virtually impossible to replicate). Furthermore, a post‐sequencing feature selection methodology based on logistic regression to facilitate PUF classification is developed. This experimental and computational pipeline drastically reduces production time and cost compared to conventional genetic barcoding without compromising the stringent PUF criteria of uniqueness and unclonability. This results provide novel insights into the function of TdT and represent a major step toward utilization of PUFs as a biosecurity primitive for cell line authentication and provenance attestation.