@misc{15108, abstract = {in the research article "Efficiency and resilience of cooperation in asymmetric social dilemmas" (by Valentin Hübner, Manuel Staab, Christian Hilbe, Krishnendu Chatterjee, and Maria Kleshnina). We used different implementations for the case of two and three players, both described below.}, author = {Hübner, Valentin and Kleshnina, Maria}, publisher = {Zenodo}, title = {{Computer code for "Efficiency and resilience of cooperation in asymmetric social dilemmas"}}, doi = {10.5281/ZENODO.10639167}, year = {2024}, } @inproceedings{18155, abstract = {We study the classical problem of verifying programs with respect to formal specifications given in the linear temporal logic (LTL). We first present novel sound and complete witnesses for LTL verification over imperative programs. Our witnesses are applicable to both verification (proving) and refutation (finding bugs) settings. We then consider LTL formulas in which atomic propositions can be polynomial constraints and turn our focus to polynomial arithmetic programs, i.e. programs in which every assignment and guard consists only of polynomial expressions. For this setting, we provide an efficient algorithm to automatically synthesize such LTL witnesses. Our synthesis procedure is both sound and semi-complete. Finally, we present experimental results demonstrating the effectiveness of our approach and that it can handle programs which were beyond the reach of previous state-of-the-art tools.}, author = {Chatterjee, Krishnendu and Goharshady, Amir Kafshdar and Goharshady, Ehsan and Karrabi, Mehrdad and Zikelic, Dorde}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, isbn = {9783031711619}, issn = {1611-3349}, location = {Milan, Italy}, pages = {600--619}, publisher = {Springer Nature}, title = {{Sound and complete witnesses for template-based verification of LTL properties on polynomial programs}}, doi = {10.1007/978-3-031-71162-6_31}, volume = {14933}, year = {2024}, } @misc{22798, abstract = {This repository contains the artifact of the paper titled "Sound and Complete Witnesses for Template-based Verification of LTL Properties on Polynomial Programs" accepted at FM 2024. The task of verifying an LTL formula on a program can be reduced to verifying a Büchi specification on the product transition system. This tool takes a non-deterministic transition system together with a Büchi specification as input and based on user preferences tries to either (i) prove the existence of a run in the program that satisfies the Büchi condition or (ii) demonstrate that every run of the program satisfies the Büchi condition. The tool is written in Java and works well with openjdk 11 on Ubuntu 22.04. Running all the experiments can take weeks to finish. We have provided a script for running the strongest configuration of our tool which solves most of the benchmarks and takes less than 48 hours. Detailed guidance is given in the readme file.}, author = {Chatterjee, Krishnendu and Kafshdar Goharshady, Amir and Kafshdar Goharshady, Ehsan and Karrabi, Mehrdad and Žikelić, Ðorđe}, publisher = {Repository}, title = {{Data for Sound and Complete Witnesses for Template-based Verification of LTL Properties on Polynomial Programs}}, doi = {10.5281/zenodo.12518216}, year = {2024}, } @article{18703, abstract = {Spatial games provide a simple and elegant mathematical model to study the evolution of cooperation in networks. In spatial games, individuals reside in vertices, adopt simple strategies, and interact with neighbors to receive a payoff. Depending on their own and neighbors’ payoffs, individuals can change their strategy. The payoff is determined by the Prisoners’ Dilemma, a classical matrix game, where players cooperate or defect. While cooperation is the desired behavior, defection provides a higher payoff for a selfish individual. There are many theoretical and empirical studies related to the role of the network in the evolution of cooperation. However, the fundamental question of whether there exist networks that for low initial cooperation rate ensure a high chance of fixation, i.e., cooperation spreads across the whole population, has remained elusive for spatial games with strong selection. In this work, we answer this fundamental question in the affirmative by presenting network structures that ensure high fixation probability for cooperators in the strong selection regime. Besides, our structures have many desirable properties: (a) they ensure the spread of cooperation even for a low initial density of cooperation and high temptation of defection, (b) they have constant degrees, and (c) the number of steps, until cooperation spreads, is at most quadratic in the size of the network.}, author = {Svoboda, Jakub and Chatterjee, Krishnendu}, issn = {1091-6490}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, number = {50}, publisher = {National Academy of Sciences}, title = {{Density amplifiers of cooperation for spatial games}}, doi = {10.1073/pnas.2405605121}, volume = {121}, year = {2024}, } @article{18630, abstract = {Markov chains are the de facto finite-state model for stochastic dynamical systems, and Markov decision processes (MDPs) extend Markov chains by incorporating non-deterministic behaviors. Given an MDP and rewards on states, a classical optimization criterion is the maximal expected total reward where the MDP stops after T steps, which can be computed by a simple dynamic programming algorithm. We consider a natural generalization of the problem where the stopping times can be chosen according to a probability distribution, such that the expected stopping time is T, to optimize the expected total reward. Quite surprisingly we establish inter-reducibility of the expected stopping-time problem for Markov chains with the Positivity problem (which is related to the well-known Skolem problem), for which establishing either decidability or undecidability would be a major breakthrough. Given the hardness of the exact problem, we consider the approximate version of the problem: we show that it can be solved in exponential time for Markov chains and in exponential space for MDPs.}, author = {Chatterjee, Krishnendu and Doyen, Laurent}, issn = {1860-5974}, journal = {Logical Methods in Computer Science}, number = {4}, pages = {11:1--11:34}, publisher = {EPI Sciences}, title = {{Stochastic processes with expected stopping time}}, doi = {10.46298/lmcs-20(4:11)2024}, volume = {20}, year = {2024}, } @inproceedings{18600, abstract = {The analysis of formal models that include quantitative aspects such as timing or probabilistic choices is performed by quantitative verification tools. Broad and mature tool support is available for computing basic properties such as expected rewards on basic models such as Markov chains. Previous editions of QComp, the comparison of tools for the analysis of quantitative formal models, focused on this setting. Many application scenarios, however, require more advanced property types such as LTL and parameter synthesis queries as well as advanced models like stochastic games and partially observable MDPs. For these, tool support is in its infancy today. This paper presents the outcomes of QComp 2023: a survey of the state of the art in quantitative verification tool support for advanced property types and models. With tools ranging from first research prototypes to well-supported integrations into established toolsets, this report highlights today’s active areas and tomorrow’s challenges in tool-focused research for quantitative verification.}, author = {Andriushchenko, Roman and Bork, Alexander and Budde, Carlos E. and Češka, Milan and Grover, Kush and Hahn, Ernst Moritz and Hartmanns, Arnd and Israelsen, Bryant and Jansen, Nils and Jeppson, Joshua and Junges, Sebastian and Köhl, Maximilian A. and Könighofer, Bettina and Kretinsky, Jan and Meggendorfer, Tobias and Parker, David and Pranger, Stefan and Quatmann, Tim and Ruijters, Enno and Taylor, Landon and Volk, Matthias and Weininger, Maximilian and Zhang, Zhen}, booktitle = {TOOLympics Challenge 2023}, isbn = {9783031676949}, issn = {1611-3349}, pages = {90--146}, publisher = {Springer Nature}, title = {{Tools at the Frontiers of Quantitative Verification: QComp 2023 Competition Report}}, doi = {10.1007/978-3-031-67695-6_4}, volume = {14550}, year = {2024}, } @inproceedings{17099, abstract = {We study two-player zero-sum concurrent stochastic games with finite state and action space played for an infinite number of steps. In every step, the two players simultaneously and independently choose an action. Given the current state and the chosen actions, the next state is obtained according to a stochastic transition function. An objective is a measurable function on plays (or infinite trajectories) of the game, and the value for an objective is the maximal expectation that the player can guarantee against the adversarial player. We consider: (a) stateful-discounted objectives, which are similar to the classical discounted-sum objectives, but states are associated with different discount factors rather than a single discount factor; and (b) parity objectives, which are a canonical representation for ω-regular objectives. For stateful-discounted objectives, given an ordering of the discount factors, the limit value is the limit of the value of the stateful-discounted objectives, as the discount factors approach zero according to the given order. The computational problem we consider is the approximation of the value within an arbitrary additive error. The above problem is known to be in EXPSPACE for the limit value of statefuldiscounted objectives and in PSPACE for parity objectives. The best-known algorithms for both the above problems are at least exponential time, with an exponential dependence on the number of states and actions. Our main results for the value approximation problem for the limit value of stateful-discounted objectives and parity objectives are as follows: (a) we establish TFNP[NP] complexity; and (b) we present algorithms that improve the dependency on the number of actions in the exponent from linear to logarithmic. In particular, if the number of states is constant, our algorithms run in polynomial time.}, author = {Asadi, Ali and Chatterjee, Krishnendu and Saona Urmeneta, Raimundo J and Svoboda, Jakub}, booktitle = {44th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science}, isbn = {9783959773553}, issn = {1868-8969}, location = {Gujarat, India}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{Concurrent stochastic games with stateful-discounted and parity objectives: Complexity and algorithms}}, doi = {10.4230/LIPIcs.FSTTCS.2024.5}, volume = {323}, year = {2024}, } @inproceedings{18159, abstract = {Markov Decision Processes (MDPs) are a classical model for decision making in the presence of uncertainty. Often they are viewed as state transformers with planning objectives defned with respect to paths over MDP states. An increasingly popular alternative is to view them as distribution transformers, giving rise to a sequence of probability distributions over MDP states. For instance, reachability and safety properties in modeling robot swarms or chemical reaction networks are naturally defned in terms of probability distributions over states. Verifying such distributional properties is known to be hard and often beyond the reach of classical state-based verifcation techniques. In this work, we consider the problems of certifed policy (i.e. controller) verifcation and synthesis in MDPs under distributional reach-avoidance specifcations. By certifed we mean that, along with a policy, we also aim to synthesize a (checkable) certifcate ensuring that the MDP indeed satisfes the property. Thus, given the target set of distributions and an unsafe set of distributions over MDP states, our goal is to either synthesize a certifcate for a given policy or synthesize a policy along with a certifcate, proving that the target distribution can be reached while avoiding unsafe distributions. To solve this problem, we introduce the novel notion of distributional reach-avoid certifcates and present automated procedures for (1) synthesizing a certifcate for a given policy, and (2) synthesizing a policy together with the certifcate, both providing formal guarantees on certifcate correctness. Our experimental evaluation demonstrates the ability of our method to solve several non-trivial examples, including a multi-agent robot-swarm model, to synthesize certifed policies and to certify existing policies. }, author = {Akshay, S and Chatterjee, Krishnendu and Meggendorfer, Tobias and Zikelic, Dorde}, booktitle = {Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence}, isbn = {9781956792041}, issn = {1045-0823}, location = {Jeju, Korea}, pages = {3--12}, publisher = {International Joint Conferences on Artificial Intelligence}, title = {{Certified policy verification and synthesis for MDPs under distributional reach-avoidance properties}}, doi = {10.24963/ijcai.2024/1}, year = {2024}, } @article{12738, abstract = {We study turn-based stochastic zero-sum games with lexicographic preferences over objectives. Stochastic games are standard models in control, verification, and synthesis of stochastic reactive systems that exhibit both randomness as well as controllable and adversarial non-determinism. Lexicographic order allows one to consider multiple objectives with a strict preference order. To the best of our knowledge, stochastic games with lexicographic objectives have not been studied before. For a mixture of reachability and safety objectives, we show that deterministic lexicographically optimal strategies exist and memory is only required to remember the already satisfied and violated objectives. For a constant number of objectives, we show that the relevant decision problem is in NP∩coNP, matching the current known bound for single objectives; and in general the decision problem is PSPACE-hard and can be solved in NEXPTIME∩coNEXPTIME. We present an algorithm that computes the lexicographically optimal strategies via a reduction to the computation of optimal strategies in a sequence of single-objectives games. For omega-regular objectives, we restrict our analysis to one-player games, also known as Markov decision processes. We show that lexicographically optimal strategies exist and need either randomization or finite memory. We present an algorithm that solves the relevant decision problem in polynomial time. We have implemented our algorithms and report experimental results on various case studies.}, author = {Chatterjee, Krishnendu and Katoen, Joost P and Mohr, Stefanie and Weininger, Maximilian and Winkler, Tobias}, issn = {1572-8102}, journal = {Formal Methods in System Design}, pages = {40--80}, publisher = {Springer Nature}, title = {{Stochastic games with lexicographic objectives}}, doi = {10.1007/s10703-023-00411-4}, volume = {63}, year = {2024}, } @inproceedings{18160, abstract = {Markov decision processes (MDPs) provide a standard framework for sequential decision making under uncertainty. However, MDPs do not take uncertainty in transition probabilities into account. Robust Markov decision processes (RMDPs) address this shortcoming of MDPs by assigning to each transition an uncertainty set rather than a single probability value. In this work, we consider polytopic RMDPs in which all uncertainty sets are polytopes and study the problem of solving long-run average reward polytopic RMDPs. We present a novel perspective on this problem and show that it can be reduced to solving long-run average reward turn-based stochastic games with finite state and action spaces. This reduction allows us to derive several important consequences that were hitherto not known to hold for polytopic RMDPs. First, we derive new computational complexity bounds for solving long-run average reward polytopic RMDPs, showing for the first time that the threshold decision problem for them is in NP∩CONP and that they admit a randomized algorithm with sub-exponential expected runtime. Second, we present Robust Polytopic Policy Iteration (RPPI), a novel policy iteration algorithm for solving long-run average reward polytopic RMDPs. Our experimental evaluation shows that RPPI is much more efficient in solving long-run average reward polytopic RMDPs compared to state-of-the-art methods based on value iteration. }, author = {Chatterjee, Krishnendu and Kafshdar Goharshadi, Ehsan and Karrabi, Mehrdad and Novotný, Petr and Zikelic, Dorde}, booktitle = {33rd International Joint Conference on Artificial Intelligence}, isbn = {9781956792041}, issn = {1045-0823}, location = {Jeju, South Korea}, pages = {6707--6715}, publisher = {International Joint Conferences on Artificial Intelligence}, title = {{Solving long-run average reward robust MDPs via stochastic games}}, doi = {10.24963/ijcai.2024/741}, year = {2024}, } @article{17474, abstract = {Entropic risk (ERisk) is an established risk measure in finance, quantifying risk by an exponential re-weighting of rewards. We study ERisk for the first time in the context of turn-based stochastic games with the total reward objective. This gives rise to an objective function that demands the control of systems in a risk-averse manner. We show that the resulting games are determined and, in particular, admit optimal memoryless deterministic strategies. This contrasts risk measures that previously have been considered in the special case of Markov decision processes and that require randomization and/or memory. We provide several results on the decidability and the computational complexity of the threshold problem, i.e. whether the optimal value of ERisk exceeds a given threshold. Furthermore, an approximation algorithm for the optimal value of ERisk is provided.}, author = {Baier, Christel and Chatterjee, Krishnendu and Meggendorfer, Tobias and Piribauer, Jakob}, issn = {1090-2651}, journal = {Information and Computation}, publisher = {Elsevier}, title = {{Entropic risk for turn-based stochastic games}}, doi = {10.1016/j.ic.2024.105214}, volume = {301}, year = {2024}, } @inproceedings{18925, abstract = {Given the increasingly stringent requirements on the performance and efficiency of communication networks, over the last years, great efforts have been made to render networks more flexible and programmable. In particular, modern networks support a flexible rerouting of flows, e.g., depending on the dynamically changing traffic or network conditions. However, the underlying algorithmic problems are still not well-understood today.In this paper, we revisit the k-Network Flow Update problem that asks for a schedule to reroute k unsplittable flows from their current paths to the given new paths, in a congestion-free manner in a capacitated network. We show that the problem is already NP-hard for three acyclic flows on simple directed graphs. Our main contribution is an efficient algorithm for sparse networks; specifically the algorithm is fixed parameter tractable in the number of flows and the treewidth of a graph that is the union of all flows. Our results also settle the open complexity question in the literature.}, author = {Ceylan, Esra and Chatterjee, Krishnendu and Schmid, Stefan and Svoboda, Jakub}, booktitle = {NOMS 2024-2024 IEEE Network Operations and Management Symposium}, isbn = {9798350327946}, issn = {2374-9709}, location = {Seoul, Republic of Korea}, publisher = {IEEE}, title = {{Congestion-free rerouting of network flows: Hardness and an FPT algorithm}}, doi = {10.1109/noms59830.2024.10575579}, year = {2024}, } @inproceedings{17328, abstract = {We study selfish mining attacks in longest-chain blockchains like Bitcoin, but where the proof of work is replaced with efficient proof systems - like proofs of stake or proofs of space - and consider the problem of computing an optimal selfish mining attack which maximizes expected relative revenue of the adversary, thus minimizing the chain quality. To this end, we propose a novel selfish mining attack that aims to maximize this objective and formally model the attack as a Markov decision process (MDP). We then present a formal analysis procedure which computes an ϵ-tight lower bound on the optimal expected relative revenue in the MDP and a strategy that achieves this ϵ-tight lower bound, where ϵ > 0 may be any specified precision. Our analysis is fully automated and provides formal guarantees on the correctness. We evaluate our selfish mining attack and observe that it achieves superior expected relative revenue compared to two considered baselines. In concurrent work [Sarenche FC'24] does an automated analysis on selfish mining in predictable longest-chain blockchains based on efficient proof systems. Predictable means the randomness for the challenges is fixed for many blocks (as used e.g., in Ouroboros), while we consider unpredictable (Bitcoin-like) chains where the challenge is derived from the previous block.}, author = {Chatterjee, Krishnendu and Ebrahimzadeh, Amirali and Karrabi, Mehrdad and Pietrzak, Krzysztof Z and Yeo, Michelle X and Zikelic, Dorde}, booktitle = {Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing}, isbn = {9798400706684}, location = {Nantes, France}, pages = {268--278}, publisher = {Association for Computing Machinery}, title = {{Fully automated selfish mining analysis in efficient proof systems blockchains}}, doi = {10.1145/3662158.3662769}, year = {2024}, } @inproceedings{15007, abstract = {Traditional blockchains grant the miner of a block full control not only over which transactions but also their order. This constitutes a major flaw discovered with the introduction of decentralized finance and allows miners to perform MEV attacks. In this paper, we address the issue of sandwich attacks by providing a construction that takes as input a blockchain protocol and outputs a new blockchain protocol with the same security but in which sandwich attacks are not profitable. Furthermore, our protocol is fully decentralized with no trusted third parties or heavy cryptography primitives and carries a linear increase in latency and minimum computation overhead.}, author = {Alpos, Orestis and Amores-Sesar, Ignacio and Cachin, Christian and Yeo, Michelle X}, booktitle = {27th International Conference on Principles of Distributed Systems}, isbn = {9783959773089}, issn = {1868-8969}, location = {Tokyo, Japan}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{Eating sandwiches: Modular and lightweight elimination of transaction reordering attacks}}, doi = {10.4230/LIPIcs.OPODIS.2023.12}, volume = {286}, year = {2024}, } @inproceedings{17051, abstract = {Memory-hard functions (MHF) are functions whose evaluation provably requires a lot of memory. While MHFs are an unkeyed primitive, it is natural to consider the notion of trapdoor MHFs (TMHFs). A TMHF is like an MHF, but when sampling the public parameters one also samples a trapdoor which allows evaluating the function much cheaper. Biryukov and Perrin (Asiacrypt’17) were the first to consider TMHFs and put forth a candidate TMHF construction called Diodon that is based on the Scrypt MHF (Percival, BSDCan’09). To allow for a trapdoor, Scrypt’s initial hash chain is replaced by a sequence of squares in a group of unknown order where the order of the group is the trapdoor. For a length n sequence of squares and a group of order N, Diodon’s cumulative memory complexity (CMC) is O(n2log N) without the trapdoor and O(n log(n) log(N)2) with knowledge of it. While Scrypt is proven to be optimally memory-hard in the random oracle model (Alwen et al., Eurocrypt’17), Diodon’s memory-hardness has not been proven so far. In this work, we fill this gap by rigorously analyzing a specific instantiation of Diodon. We show that its CMC is lower bounded by Ω( n2log nlog N) which almost matches the upper bound. Our proof is based Alwen et al.’s lower bound on Scrypt’s CMC but requires non-trivial modifications due to the algebraic structure of Diodon. Most importantly, our analysis involves a more elaborate compression argument and a solvability criterion for certain systems of Diophantine equations.}, author = {Auerbach, Benedikt and Günther, Christoph Ullrich and Pietrzak, Krzysztof Z}, booktitle = {43rd Annual International Conference on the Theory and Applications of Cryptographic Techniques}, isbn = {9783031587337}, issn = {1611-3349}, location = {Zurich, Switzerland}, pages = {315--344}, publisher = {Springer Nature}, title = {{Trapdoor memory-hard functions}}, doi = {10.1007/978-3-031-58734-4_11}, volume = {14653}, year = {2024}, } @article{17283, abstract = {We consider the problems of statically refuting equivalence and similarity of output distributions defined by a pair of probabilistic programs. Equivalence and similarity are two fundamental relational properties of probabilistic programs that are essential for their correctness both in implementation and in compilation. In this work, we present a new method for static equivalence and similarity refutation. Our method refutes equivalence and similarity by computing a function over program outputs whose expected value with respect to the output distributions of two programs is different. The function is computed simultaneously with an upper expectation supermartingale and a lower expectation submartingale for the two programs, which we show to together provide a formal certificate for refuting equivalence and similarity. To the best of our knowledge, our method is the first approach to relational program analysis to offer the combination of the following desirable features: (1) it is fully automated, (2) it is applicable to infinite-state probabilistic programs, and (3) it provides formal guarantees on the correctness of its results. We implement a prototype of our method and our experiments demonstrate the effectiveness of our method to refute equivalence and similarity for a number of examples collected from the literature.}, author = {Chatterjee, Krishnendu and Kafshdar Goharshadi, Ehsan and Novotný, Petr and Zikelic, Dorde}, issn = {2475-1421}, journal = {Proceedings of the ACM on Programming Languages}, publisher = {Association for Computing Machinery}, title = {{Equivalence and similarity refutation for probabilistic programs}}, doi = {10.1145/3656462}, volume = {8}, year = {2024}, } @article{14820, abstract = {We consider a natural problem dealing with weighted packet selection across a rechargeable link, which e.g., finds applications in cryptocurrency networks. The capacity of a link (u, v) is determined by how many nodes u and v allocate for this link. Specifically, the input is a finite ordered sequence of packets that arrive in both directions along a link. Given (u, v) and a packet of weight x going from u to v, node u can either accept or reject the packet. If u accepts the packet, the capacity on link (u, v) decreases by x. Correspondingly, v's capacity on increases by x. If a node rejects the packet, this will entail a cost affinely linear in the weight of the packet. A link is “rechargeable” in the sense that the total capacity of the link has to remain constant, but the allocation of capacity at the ends of the link can depend arbitrarily on the nodes' decisions. The goal is to minimise the sum of the capacity injected into the link and the cost of rejecting packets. We show that the problem is NP-hard, but can be approximated efficiently with a ratio of (1+E) . (1+3) for some arbitrary E>0.}, author = {Schmid, Stefan and Svoboda, Jakub and Yeo, Michelle X}, issn = {0304-3975}, journal = {Theoretical Computer Science}, keywords = {General Computer Science, Theoretical Computer Science}, publisher = {Elsevier}, title = {{Weighted packet selection for rechargeable links in cryptocurrency networks: Complexity and approximation}}, doi = {10.1016/j.tcs.2023.114353}, volume = {989}, year = {2024}, } @inproceedings{17126, abstract = {Functional encryption (FE) is a primitive where the holder of a master secret key can control which functions a user can evaluate on encrypted data. It is a powerful primitive that even implies indistinguishability obfuscation (iO), given sufficiently compact ciphertexts (Ananth-Jain, CRYPTO’15 and Bitansky-Vaikuntanathan, FOCS’15). However, despite being extensively studied, there are FE schemes, such as function-hiding inner-product FE (Bishop-Jain-Kowalczyk, AC’15, Abdalla-Catalano-Fiore-Gay-Ursu, CRYPTO’18) and compact quadratic FE (Baltico-Catalano-Fiore-Gay, Lin, CRYPTO’17), that can be only realized using pairings. This raises the question if there are some mathematical barriers that hinder us from realizing these FE schemes from other assumptions. In this paper, we study the difficulty of constructing lattice-based compact FE. We generalize the impossibility results of Ünal (EC’20) for lattice-based function-hiding FE, and extend it to the case of compact FE. Concretely, we prove lower bounds for lattice-based compact FE schemes which meet some (natural) algebraic restrictions at encryption and decryption, and have ciphertexts of linear size and secret keys of minimal degree. We see our results as important indications of why it is hard to construct lattice-based FE schemes for new functionalities, and which mathematical barriers have to be overcome.}, author = {Tairi, Erkan and Ünal, Akin}, booktitle = {Advances in Cryptology – EUROCRYPT 2024}, isbn = {9783031587221}, issn = {1611-3349}, location = {Zurich, Switzerland}, pages = {249--279}, publisher = {Springer Nature}, title = {{Lower bounds for lattice-based compact functional encryption}}, doi = {10.1007/978-3-031-58723-8_9}, volume = {14652}, year = {2024}, } @inproceedings{18755, abstract = {A universalthresholdizer (UT), constructed from a threshold fully homomorphic encryption by Boneh et. al , Crypto 2018, is a general framework for universally thresholdizing many cryptographic schemes. However, their framework is insufficient to construct strongly secure threshold schemes, such as threshold signatures and threshold public-key encryption, etc. In this paper, we strengthen the security definition for a universal thresholdizer and propose a scheme which satisfies our stronger security notion. Our UT scheme is an improvement of Boneh et. al ’s construction at the level of threshold fully homomorphic encryption using a key homomorphic pseudorandom function. We apply our strongly secure UT scheme to construct strongly secure threshold signatures and threshold public-key encryption.}, author = {Ebrahimi, Ehsan and Yadav, Anshu}, booktitle = {30th International Conference on the Theory and Application of Cryptology and Information Security}, isbn = {9789819608904}, issn = {1611-3349}, location = {Kolkata, India}, pages = {207--239}, publisher = {Springer Nature}, title = {{Strongly secure universal thresholdizer}}, doi = {10.1007/978-981-96-0891-1_7}, volume = {15486}, year = {2024}, } @inproceedings{18974, abstract = {Reinforcement Learning (RL) from temporal logical specifications is a fundamental problem in sequential decision making. One of the basic and core such specification is the reachability specification that requires a target set to be eventually visited. Despite strong empirical results for RL from such specifications, the theoretical guarantees are bleak, including the impossibility of Probably Approximately Correct (PAC) guarantee for reachability specifications. Given the impossibility result, in this work we consider the problem of RL from reachability specifications along with the information of expected conditional distance (ECD). We present (a) lower bound results which establish the necessity of ECD information for PAC guarantees and (b) an algorithm that establishes PAC-guarantees given the ECD information. To the best of our knowledge, this is the first RL from reachability specifications that does not make any assumptions on the underlying environment to learn policies.}, author = {Svoboda, Jakub and Bansal, Suguman and Chatterjee, Krishnendu}, booktitle = {41st International Conference on Machine Learning}, location = {Vienna, Austria}, pages = {47331--47344}, publisher = {ML Research Press}, title = {{Reinforcement learning from reachability specifications: PAC guarantees with expected conditional distance}}, volume = {235}, year = {2024}, }