International Association for Cryptologic Research

International Association
for Cryptologic Research


Maya Farber Brodsky


Monotone-Policy Aggregate Signatures
The notion of aggregate signatures allows for combining signatures from different parties into a short certificate that attests that *all* parties signed a message. In this work, we lift this notion to capture different, more expressive signing policies. For example, we can certify that a message was signed by a (weighted) threshold of signers. We present the first constructions of aggregate signatures for monotone policies based on standard polynomial-time cryptographic assumptions. The aggregate signatures in our schemes are succinct, i.e., their size is *independent* of the number of signers. Moreover, verification is also succinct if all parties sign the same message (or if the messages have a succinct representation). All prior work requires either interaction between the parties or non-standard assumptions (that imply SNARKs for NP). Our signature schemes are based on non-interactive batch arguments (BARGs) for monotone policies [Brakerski-Brodsky-Kalai-Lombardi-Paneth, Crypto'23]. In contrast to previous constructions, our BARGs satisfy a new notion of *adaptive* security which is instrumental to our application. Our new BARGs for monotone policies can be constructed from standard BARGs and other standard assumptions.
SNARGs for Monotone Policy Batch NP
We construct a succinct non-interactive argument ($\mathsf{SNARG}$) for the class of monotone policy batch $\mathsf{NP}$ languages, under the Learning with Errors ($\mathsf{LWE}$) assumption. This class is a subclass of $\mathsf{NP}$ that is associated with a monotone function~$f:\{0,1\}^k\rightarrow\{0,1\}$ and an $\mathsf{NP}$ language $\mathcal{L}$, and contains instances $(x_1,\ldots,x_k)$ such the $f(b_1,\ldots,b_k)=1$ where $b_j=1$ if and only if $x_j\in \mathcal{L}$. Our $\mathsf{SNARG}$s are arguments of knowledge in the non-adaptive setting, and satisfy a new notion of somewhere extractability against adaptive adversaries. This is the first $\mathsf{SNARG}$ under standard hardness assumptions for a sub-class of $\mathsf{NP}$ that is not known to have a (computational) non-signaling $\mathsf{PCP}$ with parameters compatible with the standard framework for constructing $\mathsf{SNARG}$s dating back to [Kalai-Raz-Rothblum, STOC '13]. Indeed, our approach necessarily departs from this framework. Our construction combines existing quasi-arguments for $\mathsf{NP}$ (based on batch arguments for $\mathsf{NP}$) with a new type of cryptographic encoding of the instance and a new analysis going from local to global soundness. The main novel ingredient used in our encoding is a {\em predicate-extractable hash} ($\mathsf{PEH}$) family, which is a primitive that generalizes the notion of a somewhere extractable hash. Whereas a somewhere extractable hash allows to extract a single input coordinate, our $\mathsf{PEH}$ extracts a {\em global} property of the input. We view this primitive to be of independent interest, and believe that it will find other applications.