More Like this

1. Dynamic Approximate Multiplicatively-Weighted Nearest Neighbors

   https://doi.org/10.4230/LIPIcs.SWAT.2022.11  

   Aronov, Boris; Katz, Matthew J. (January 2022, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Czumaj, Artur; Xin, Qin (Ed.)

   We describe a dynamic data structure for approximate nearest neighbor (ANN) queries with respect to multiplicatively weighted distances with additive offsets. Queries take polylogarithmic time, while the cost of updates is amortized polylogarithmic. The data structure requires near-linear space and construction time. The approach works not only for the Euclidean norm, but for other norms in ℝ^d, for any fixed d. We employ our ANN data structure to construct a faster dynamic structure for approximate SINR queries, ensuring polylogarithmic query and polylogarithmic amortized update for the case of non-uniform power transmitters, thus closing a gap in previous state of the art. To obtain the latter result, we needed a data structure for dynamic approximate halfplane range counting in the plane. Since we could not find such a data structure in the literature, we also show how to dynamize one of the known static data structures. 

   more » « less
2. PACIFIC

   https://doi.org/10.62056/ay11fhbmo  

   Griffy, Scott; Lysyanskaya, Anna (July 2024, IACR Communications in Cryptology)

   To be useful and widely accepted, automated contact tracing schemes (also called exposure notification) need to solve two seemingly contradictory problems at the same time: they need to protect the anonymity of honest users while also preventing malicious users from creating false alarms. In this paper, we provide, for the first time, an exposure notification construction that guarantees the same levels of privacy and integrity as existing schemes but with a fully malicious database (notably similar to Auerbach et al. CT-RSA 2021) without special restrictions on the adversary. We construct a new definition so that we can formally prove our construction secure. Our definition ensures the following integrity guarantees: no malicious user can cause exposure warnings in two locations at the same time and that any uploaded exposure notifications must be recent and not previously uploaded. Our construction is efficient, requiring only a single message to be broadcast at contact time no matter how many recipients are nearby. To notify contacts of potential infection, an infected user uploads data with size linear in the number of notifications, similar to other schemes. Linear upload complexity is not trivial with our assumptions and guarantees (a naive scheme would be quadratic). This linear complexity is achieved with a new primitive: zero knowledge subset proofs over commitments which is used by our no cloning proof protocol. We also introduce another new primitive: set commitments on equivalence classes, which makes each step of our construction more efficient. Both of these new primitives are of independent interest. 

   more » « less
3. Robustly Self-Ordered Graphs: Constructions and Applications to Property Testing

   Goldreich, Oded; Wigderson, Avi (November 2020, Electronic colloquium on computational complexity)

   null (Ed.)

   A graph G is called {\em self-ordered} (a.k.a asymmetric) if the identity permutation is its only automorphism. Equivalently, there is a unique isomorphism from G to any graph that is isomorphic to G. We say that G=(VE) is {\em robustly self-ordered}if the size of the symmetric difference between E and the edge-set of the graph obtained by permuting V using any permutation :VV is proportional to the number of non-fixed-points of . In this work, we initiate the study of the structure, construction and utility of robustly self-ordered graphs. We show that robustly self-ordered bounded-degree graphs exist (in abundance), and that they can be constructed efficiently, in a strong sense. Specifically, given the index of a vertex in such a graph, it is possible to find all its neighbors in polynomial-time (i.e., in time that is poly-logarithmic in the size of the graph). We provide two very different constructions, in tools and structure. The first, a direct construction, is based on proving a sufficient condition for robust self-ordering, which requires that an auxiliary graph, on {\em pairs} of vertices of the original graph, is expanding. In this case the original graph is (not only robustly self-ordered but) also expanding. The second construction proceeds in three steps: It boosts the mere existence of robustly self-ordered graphs, which provides explicit graphs of sublogarithmic size, to an efficient construction of polynomial-size graphs, and then, repeating it again, to exponential-size(robustly self-ordered) graphs that are locally constructible. This construction can yield robustly self-ordered graphs that are either expanders or highly disconnected, having logarithmic size connected components. We also consider graphs of unbounded degree, seeking correspondingly unbounded robustness parameters. We again demonstrate that such graphs (of linear degree)exist (in abundance), and that they can be constructed efficiently, in a strong sense. This turns out to require very different tools. Specifically, we show that the construction of such graphs reduces to the construction of non-malleable two-source extractors with very weak parameters but with some additional natural features. We actually show two reductions, one simpler than the other but yielding a less efficient construction when combined with the known constructions of extractors. We demonstrate that robustly self-ordered bounded-degree graphs are useful towards obtaining lower bounds on the query complexity of testing graph properties both in the bounded-degree and the dense graph models. Indeed, their robustness offers efficient, local and distance preserving reductions from testing problems on ordered structures (like sequences) to the unordered (effectively unlabeled) graphs. One of the results that we obtain, via such a reduction, is a subexponential separation between the query complexities of testing and tolerant testing of graph properties in the bounded-degree graph model. Changes to previous version: We retract the claims made in our initial posting regarding the construction of non-malleable two-source extractors (which are quasi-orthogonal) as well as the claims about the construction of relocation-detecting codes (see Theorems 1.5 and 1.6 in the original version). The source of trouble is a fundamental flaw in the proof of Lemma 9.7 (in the original version), which may as well be wrong. Hence, the original Section 9 was omitted, except that the original Section 9.3 was retained as a new Section 8.3. The original Section 8 appears as Section 8.0 and 8.1, and Section 8.2 is new. 

   more » « less
4. Interval universal approximation for neural networks

   https://doi.org/10.1145/3498675  

   Wang, Zi; Albarghouthi, Aws; Prakriya, Gautam; Jha, Somesh (January 2022, Proceedings of the ACM on Programming Languages)

   To verify safety and robustness of neural networks, researchers have successfully appliedabstract interpretation, primarily using the interval abstract domain. In this paper, we study the theoretical power and limits of the interval domain for neural-network verification. First, we introduce theinterval universal approximation(IUA) theorem. IUA shows that neural networks not only can approximate any continuous functionf(universal approximation) as we have known for decades, but we can find a neural network, using any well-behaved activation function, whose interval bounds are an arbitrarily close approximation of the set semantics off(the result of applyingfto a set of inputs). We call this notion of approximationinterval approximation. Our theorem generalizes the recent result of Baader et al. from ReLUs to a rich class of activation functions that we callsquashable functions. Additionally, the IUA theorem implies that we can always construct provably robust neural networks under ℓ_∞-norm using almost any practical activation function. Second, we study the computational complexity of constructing neural networks that are amenable to precise interval analysis. This is a crucial question, as our constructive proof of IUA is exponential in the size of the approximation domain. We boil this question down to the problem of approximating the range of a neural network with squashable activation functions. We show that the range approximation problem (RA) is a Δ₂-intermediate problem, which is strictly harder thanNP-complete problems, assumingcoNP⊄NP. As a result,IUA is an inherently hard problem: No matter what abstract domain or computational tools we consider to achieve interval approximation, there is no efficient construction of such a universal approximator. This implies that it is hard to construct a provably robust network, even if we have a robust network to start with. 

   more » « less
5. The Fiat-Shamir Zoo: Relating the Security of Different Signature Variants

   Backendal, Matilda; Bellare, Mihir; Sorrell, Jessica; Sun, Jiahao (November 2018, Secure IT Systems - 23rd Nordic Conference, NordSec 2018, Oslo, Norway, November 28-30, 2018, Proceedings. Lecture Notes in Computer Science 11252, Springer 2018)

   The Fiat-Shamir paradigm encompasses many different ways of turning a given identification scheme into a signature scheme. Security proofs pertain sometimes to one variant, sometimes to another. We systematically study three variants that we call the challenge (signature is challenge and response), commit (signature is commitment and response), and transcript (signature is challenge, commitment and response) variants. Our framework captures the variants via transforms that determine the signature scheme as a function of not only the identification scheme and hash function (to cover both standard and random oracle model hashing), but also what we call a signing algorithm, to cover both classical and with-abort signing. We relate the security of the signature schemes produced by these transforms, giving minimal conditions under which uf-security of one transfers to the other. To apply this comprehensively, we formalize linear identification schemes, show that many schemes in the literature are linear, and show that any linear scheme meets our conditions for the signature schemes given by the three transforms to have equivalent uf-security. Our results give a comprehensive picture of the Fiat-Shamir zoo and allow proofs of security in the literature to be transferred automatically from one variant to another. 

   more » « less