International Association
for Cryptologic Research

Amortized bootstrapping offers a way to simultaneously refresh many ciphertexts of a fully homomorphic encryption scheme, at a total cost comparable to that of refreshing a single ciphertext. An amortization method for FHEW-style cryptosystems was first proposed by (Micciancio and Sorrell, ICALP 2018), who showed that the amortized cost of bootstrapping $n$ FHEW-style ciphertexts can be reduced from $\tilde O(n)$ basic cryptographic operations to just $\tilde O(n^{\epsilon})$, for any constant $\epsilon>0$. However, despite the promising asymptotic saving, the algorithm was rather inpractical due to a large constant (exponential in $1/\epsilon$) hidden in the asymptotic notation. In this work, we propose an alternative amortized boostrapping method with much smaller overhead, still achieving $O(n^\epsilon)$ asymptotic amortized cost, but with a hidden constant that is only linear in $1/\epsilon$, and with reduced noise growth. This is achieved following the general strategy of (Micciancio and Sorrell), but replacing their use of the Nussbaumer transform, with a much more practical Number Theoretic Transform, with multiplication by twiddle factors implemented using ring automorphisms. A key technical ingredient to do this is a new ``scheme switching'' technique proposed in this paper which may be of independent interest.

<p> Side-channel attacks targeting cryptography may leak only partial or indirect information about the secret keys. There are a variety of techniques in the literature for recovering secret keys from partial information. In this work, we survey several of the main families of partial key recovery algorithms for RSA, (EC)DSA, and (elliptic curve) Diffie-Hellman, the classical public-key cryptosystems in common use today. We categorize the known techniques by the structure of the information that is learned by the attacker, and give simplified examples for each technique to illustrate the underlying ideas. </p>

In this article, we give evidences that free modules (i.e., modules which admit a basis) are no weaker than arbitrary modules, when it comes to solving cryptographic algorithmic problems (and when the rank of the module is at least 2). More precisely, we show that for three algorithmic problems used in cryptography, namely the shortest vector problem, the Hermite shortest vector problem and a variant of the closest vector problem, there is a reduction from solving the problem in any module of rank n ≥ 2 to solving the problem in any free module of the same rank n. As an application, we show that this can be used to dequantize the LLL algorithm for module lattices presented by Lee et al. (Asiacrypt 2019).

The tower variant of the number field sieve (TNFS) is known to be asymptotically the most efficient algorithm to solve the discrete logarithm problem in finite fields of medium characteristics, when the extension degree is composite. A major obstacle to an efficient implementation of TNFS is the collection of algebraic relations, as it happens in dimension greater than 2. This requires the construction of new sieving algorithms which remain efficient as the dimension grows. In this article, we overcome this difficulty by considering a lattice enumeration algorithm which we adapt to this specific context. We also consider a new sieving area, a high-dimensional sphere, whereas previous sieving algorithms for the classical NFS considered an orthotope. Our new sieving technique leads to a much smaller running time, despite the larger dimension of the search space, and even when considering a larger target, as demonstrated by a record computation we performed in a 521-bit finite field  $${{{\mathbb {F}}}}_{p^6}$$ F p 6 . The target finite field is of the same form as finite fields used in recent zero-knowledge proofs in some blockchains. This is the first reported implementation of TNFS.

The Tower variant of the Number Field Sieve (TNFS) is known to be asymptotically the most efficient algorithm to solve the discrete logarithm problem in finite fields of medium characteristics, when the extension degree is composite. A major obstacle to an efficient implementation of TNFS is the collection of algebraic relations, as it happens in dimension greater than 2. This requires the construction of new sieving algorithms which remain efficient as the dimension grows. In this article, we overcome this difficulty by considering a lattice enumeration algorithm which we adapt to this specific context. We also consider a new sieving area, a high-dimensional sphere, whereas previous sieving algorithms for the classical NFS considered an orthotope. Our new sieving technique leads to a much smaller running time, despite the larger dimension of the search space, and even when considering a larger target, as demonstrated by a record computation we performed in a 521-bit finite field GF(p^6). The target finite field is of the same form than finite fields used in recent zero-knowledge proofs in some blockchains. This is the first reported implementation of TNFS.

We study the discrete logarithm problem at the boundary case between small and medium characteristic finite fields, which is precisely the area where finite fields used in pairing-based cryptosystems live. In order to evaluate the security of pairing-based protocols, we thoroughly analyze the complexity of all the algorithms that coexist at this boundary case: the Quasi-Polynomial algorithms, the Number Field Sieve and its many variants, and the Function Field Sieve. We adapt the latter to the particular case where the extension degree is composite, and show how to lower the complexity by working in a shifted function field. All this study finally allows us to give precise values for the characteristic asymptotically achieving the highest security level for pairings. Surprisingly enough, there exist special characteristics that are as secure as general ones.

Intel Software Guard Extensions (SGX) allows users to perform secure computation on platforms that run untrusted software. To validate that the computation is correctly initialized and that it executes on trusted hardware, SGX supports attestation providers that can vouch for the user’s computation. Communication with these attestation providers is based on the Extended Privacy ID (EPID) protocol, which not only validates the computation but is also designed to maintain the user’s privacy. In particular, EPID is designed to ensure that the attestation provider is unable to identify the host on which the computation executes. In this work we investigate the security of the Intel implementation of the EPID protocol. We identify an implementation weakness that leaks information via a cache side channel. We show that a malicious attestation provider can use the leaked information to break the unlinkability guarantees of EPID. We analyze the leaked information using a lattice-based approach for solving the hidden number problem, which we adapt to the zero-knowledge proof in the EPID scheme, extending prior attacks on signature schemes.