Crystals-Kyber, a key encapsulation mechanism (KEM) whose security is based on the Module-LWE problem, has recently been selected by NIST as part of its post-quantum cryptography initiative. At ASIACRYPT 2021, Qin et ...
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ISBN:
(纸本)9783031708954;9783031708961
Crystals-Kyber, a key encapsulation mechanism (KEM) whose security is based on the Module-LWE problem, has recently been selected by NIST as part of its post-quantum cryptography initiative. At ASIACRYPT 2021, Qin et al. gave a method to evaluate the number of forged ciphertexts to recover a reused private key. For CPA-secure Kyber KEM, key mismatch attack is applied to get the first position of the decrypted message. However, for CCA-secure KEM, the Fujisaki-Okamoto transformation is used to detect the forged ciphertexts, thus, side channel techniques are necessary to get the first position of the decrypted message. Once the first position is obtained, the reused private key can be recovered. Using Qin et al.'s method the adversary should forge ciphertexts for several times, but the number of forged ciphertexts does not reach the Huffman bound. In this paper, we propose a generalized key mismatch attack based on dynamic chunking approach for CPA-secure Kyber KEM, and a new key recovery attack based on linear programming for CCA-secure Kyber KEM, where the number of forged ciphertexts reaches the Huffman bound. Meanwhile, the two approaches can also be applied to Saber KEM, which is the third round candidate scheme.
Open educational resources (OERs) can provide useful online materials to facilitate teaching and learning. It is desirable to provide a focused list for the global computing education community. In this short paper, w...
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ISBN:
(纸本)9798350376975;9798350376968
Open educational resources (OERs) can provide useful online materials to facilitate teaching and learning. It is desirable to provide a focused list for the global computing education community. In this short paper, we present the top 10 computerscience OERs based on voting, as organized by the MERLOT computerscience Editorial Board. These OERs cover various important computing topics, including general computing topics, programming, algorithms, machine learning etc. They provide good references for instructors to complement their lectures and strengthen student computing backgrounds.
programming is one of the most popular and demanding courses in universities around the world for students to build a strong foundation for their future in the field of computerscience. Unlike other subjects, compute...
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Advances in digitization and resource-sharing business models have created new opportunities for manufacturing companies, enhancing competitiveness and resilience. However, these benefits bring computational challenge...
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We present a kind inference algorithm for the FREEST programming language. The input to the algorithmis FREEST source code with (possibly part of) kind annotations replaced by kind variables. The algorithm infers conc...
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We present a kind inference algorithm for the FREEST programming language. The input to the algorithmis FREEST source code with (possibly part of) kind annotations replaced by kind variables. The algorithm infers concrete kinds for all kind variables. We ran the algorithm on the FREEST test suite by first replacing kind annotation on all type variables by fresh kind variables, and concluded that the algorithm correctly infers all kinds. Non surprisingly, we found out that programmers do not choose the most general kind in 20% of the cases.
As a transport mode, bike-sharing has gained popularity worldwide because it is environmentally friendly and cost-efficient. However, as a bike-sharing network grows, operating costs at rental centers increase. The pr...
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ISBN:
(纸本)9783031618154;9783031618161
As a transport mode, bike-sharing has gained popularity worldwide because it is environmentally friendly and cost-efficient. However, as a bike-sharing network grows, operating costs at rental centers increase. The problem is determining the locations of rental centers to open and the number of bicycles that will be transferred daily between rental centers while minimizing the total operating costs. We present a stochastic programming model and a Benders decomposition-based hybrid algorithm. We consider two scenarios for demand-return machine learning models - time series-based prediction and weather-based forecasting. Finally, we provide a case study of developing a bike-sharing network in New York City to verify the significance of the proposed models. We also evaluate the performances of demand-return prediction models and the impact of the relative ratio between demand and return on bike-sharing network design. We find no bicycle transfer if the penalty cost for a rental station has an inverse linear relationship with the ratio of returns to rentals. Nevertheless, when the penalty cost is exponentially dependent on the negative ratio of returns to rentals, bicycle transfer occurs between rental stations with large ratios.
A key part of learning to program is learning to understand programming error messages. They can be hard to interpret and identifying the cause of errors can be time-consuming. One factor in this challenge is that the...
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ISBN:
(纸本)9781450394314
A key part of learning to program is learning to understand programming error messages. They can be hard to interpret and identifying the cause of errors can be time-consuming. One factor in this challenge is that the messages are typically intended for an audience that already knows how to program, or even for programming environments that then use the information to highlight areas in code. Researchers have been working on making these errors more novice friendly since the 1960s, however progress has been slow. The present work contributes to this stream of research by using large language models to enhance programming error messages with explanations of the errors and suggestions on how to fix them. Large language models can be used to create useful and novice-friendly enhancements to programming error messages that sometimes surpass the original programming error messages in interpretability and actionability. These results provide further evidence of the benefits of large language models for computing educators, highlighting their use in areas known to be challenging for students. We further discuss the benefits and downsides of large language models and highlight future streams of research for enhancing programming error messages.
Mixed integer programming (MIP) is a fundamental model in operations research. Local search is a powerful method for solving hard problems, but the development of local search solvers for MIP still needs to be explore...
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A novel Weighted Bipolar Argumentation Framework (WBAF) is proposed in this paper, which deals with attack and support relations equally and takes into account the weight of arguments and relations, and is a more...
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We present methods for testing and incremental testing of systems modeled as finite state machines with timeouts (TFSMs). For testing, we establish an appropriate fault model and show how a complete test suite can be ...
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We present methods for testing and incremental testing of systems modeled as finite state machines with timeouts (TFSMs). For testing, we establish an appropriate fault model and show how a complete test suite can be derived for a given TFSM specification using traditional FSM-based test derivation approaches considering an untimed FSM abstraction of the given specification. In addition, we consider reducing the cost of testing a modified or an evolving TFSM specification by the selection of appropriate incremental test suites that can verify whether the modified parts of a modified specification are correctly implemented in a corresponding implementation under test. In particular, we define the incremental testing problem for TFSMs and investigate appropriate fault models that can be used for incremental test derivation and accordingly propose related test selection algorithms. According to conducted experiments length and run time (sum of time delays) of obtained test suites are much lower than their theoretic upper bounds;in some cases, these bounds are linear. In addition, for incremental testing, when the modified part is up to 20% of the whole specification, length and run time of incremental test suites are at least twice as less than those obtained using the whole modified specification.
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