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This position paper provides first, a literature survey of selected domains with significant contributions to simulation interoperability research, such as defense and healthcare simulation, including insights from academia and research organizations. Next, four main interoperability methods are reviewed, i.e., messages-oriented methods, use of information exchange models and common object models, and reference modeling, including ontological means. This review leads to the observation that successful approaches do not only rely on technical solutions but are also using conceptual alignment of the underlying models as well. The Levels of Conceptual Interoperability Model is revisited to consider how it contributed—and still contributes today—to reach meaningful interoperability between model-based solutions. Its descriptive and prescriptive use is discussed, and it is applied to the four methods to show its practical applicability. [ABSTRACT FROM AUTHOR]

Entropy can signify different things. For instance, heat transfer in thermodynamics or a measure of information in data analysis. Many entropies have been introduced, and it can be difficult to ascertain their respective importance and merits. Here, we consider entropy in an abstract sense, as a functional on a probability space, and we review how being able to handle the trivial case of non-interacting systems, together with the subtle requirement of extensivity, allows for a systematic classification of the functional form. [ABSTRACT FROM AUTHOR]

Security is a major concern when building large-scale computer systems. Cloud services have made it easier to provision large-scale systems on demand over the Internet. While the cloud service providers provide the required building blocks such as compute units, database servers, and storage, customers are still responsible for securely combining these systems to satisfy their organization’s security policy. The secure development and operation of such large-scale systems present technical challenges. Composing a larger system using components with known security properties that satisfy a given security policy without re-analyzing the individual components is a difficult problem. In this study, we attempted to analyze the composability of components from a security perspective using first-order predicate logic. We posit that if we build a system using individual components that satisfy a security policy, the composed system will be sound with regard to that policy. Additionally, the methodology can be used to identify drifts or violations during future changes in the system by running checks during the system release cycles for continuous verification.

Decentralized finance (DeFi) has revolutionized the financial industry in recent years. Industries such as banking, insurance, and investment are experiencing a significant shift due to the growth of DeFi. The decentralized finance market is expanding exponentially, emphasizing the potential of digital currencies and decentralized platforms in providing an alternative to the traditional finance paradigm. It eliminates the need for costly intermediaries, reduces transaction fees, and increases accessibility to financial services for everyone, regardless of their geographic location or economic status. With the enormous increase in cryptocurrency investment, individuals and institutions have started to use DeFi. In this context, understanding the architecture and working mechanisms of different DeFi protocols becomes crucial in creating new and innovative products. This review paper explores various DeFi protocols, including derivatives, decentralized exchanges (DEX), lending and borrowing, asset management, and stablecoins. It analyses their internal structure and composability, providing insights into how these protocols can be combined to create new and innovative DeFi products and explore the potential of DeFi in providing an alternative to the traditional finance paradigm.

A proof-of-location ( $pol$ ) is a digital credential issued to a user after proving their location to an issuer. The user can use the $pol$ at a later time to prove to a verifier that they have been present at a claimed location. A secure Proof-of-Location (POL) system requires that $pol\text{s}$ be unforgeable and non-transferable to other users. POL systems can be used to provide fine-grained authentication and authorization and must ensure the privacy of the $pol$ owner against the issuer and the verifier while allowing efficient presentation of $pol\text{s}$ combined with other credentials when needed. Efficiency is in terms of communication overhead in user-verifier POL sessions, which has particular significance in high-volume $pol$ verification scenarios. We first propose a POL system that (i) is provably secure in a simulation-based framework, allowing a $pol$ to be securely used with other credentials, and (ii) provides anonymity against the issuer and the verifier. We then extend the system to allow $pol\text{s}$ to be stored on a public distributed ledger system and selectively be presented to the verifiers by the user. This is the first POL system that satisfies the above properties. We implement POL algorithms on a mobile phone and present our experimental results showing the practicality of the system. Our proposed scheme is highly scalable compared to existing systems, reducing the user-verifier POL communication overhead by up to a factor of 94.

Side-channel attacks are a fundamental threat to the security of cryptographic implementations. One of the most prominent countermeasures against side-channel attacks is masking, where each intermediate value of the computation is secret shared, thereby concealing the computation’s sensitive information. An important security model to study the security of masking schemes is the random probing model, in which the adversary obtains each intermediate value of the computation with some probability p. To construct secure masking schemes, an important building block is the refreshing gadget, which updates the randomness of the secret shared intermediate values. Recently, Dziembowski, Faust, and Zebrowski (ASIACRYPT’19) analyzed the security of a simple refreshing gadget by using a new technique called the leakage diagram. In this work, we follow the approach of Dziembowski et al. and significantly improve its methodology. Concretely, we refine the notion of a leakage diagram via so-called dependency graphs, and show how to use this technique for arbitrary complex circuits via composition results and approximation techniques. To illustrate the power of our new techniques, as a case study, we designed provably secure parallel gadgets for the random probing model, and adapted the ISW multiplication such that all gadgets can be parallelized. Finally, we evaluate concrete security levels, and show how our new methodology can further improve the concrete security level of masking schemes. This results in a compiler provable secure up to a noise level of O(1) for affine circuits and O(1/√n) in general.

Entropy can signify different things. For instance, heat transfer in thermodynamics or a measure of information in data analysis. Many entropies have been introduced, and it can be difficult to ascertain their respective importance and merits. Here, we consider entropy in an abstract sense, as a functional on a probability space, and we review how being able to handle the trivial case of non-interacting systems, together with the subtle requirement of extensivity, allows for a systematic classification of the functional form.

Decentralized finance (DeFi) has revolutionized the financial industry in recent years. Industries such as banking, insurance, and investment are experiencing a significant shift due to the growth of DeFi. The decentralized finance market is expanding exponentially, emphasizing the potential of digital currencies and decentralized platforms in providing an alternative to the traditional finance paradigm. It eliminates the need for costly intermediaries, reduces transaction fees, and increases accessibility to financial services for everyone, regardless of their geographic location or economic status. With the enormous increase in cryptocurrency investment, individuals and institutions have started to use DeFi. In this context, understanding the architecture and working mechanisms of different DeFi protocols becomes crucial in creating new and innovative products. This review paper explores various DeFi protocols, including derivatives, decentralized exchanges (DEX), lending and borrowing, asset management, and stablecoins. It analyses their internal structure and composability, providing insights into how these protocols can be combined to create new and innovative DeFi products and explore the potential of DeFi in providing an alternative to the traditional finance paradigm. [ABSTRACT FROM AUTHOR]

Albeit its many benefits, masking cryptographic hardware designs has proven to be a non-trivial and error-prone task, even for experienced engineers. Masked variants of atomic logic gates, like AND or XOR – commonly referred to as gadgets – aim to facilitate the process of masking large circuits by offering free composition while sustaining the overall design’s security in the d-probing adversary model. A wide variety of research has already been conducted to (i) find formal properties a gadget must fulfill to guarantee composability and (ii) construct gadgets that fulfill these properties, while minimizing overhead requirements. In all existing composition frameworks like NI/SNI/PINI and all corresponding gadget realizations, the security argument relies on the fact that each gadget requires individual fresh randomness. Naturally, this approach leads to very high randomness requirements of the resulting composed circuit. In this work, we present composable gadgets with reused fresh masks (COMAR), allowing the composition of any first-order secure hardware circuit utilizing only 6 fresh masks in total. By construction, our newly presented gadgets render individual fresh randomness unnecessary, while retaining free composition and first-order security in the robust probing model. More precisely, we give an instantiation of gadgets realizing arbitrary XOR and AND gates with an arbitrary number of inputs which can be trivially extended to all basic logic gates. With these, we break the linear dependency between the number of (non-linear) gates in a circuit and the randomness requirements, hence offering the designers the possibility to highly optimize a masked circuit’s randomness requirements while keeping error susceptibility to a minimum.

Mathematical modeling has become a major tool to guide the characterization and synthetic construction of cellular processes. However, models typically lose their capacity to explain or predict experimental outcomes as soon as any, even minor, modification of the studied system or its operating conditions is implemented. This limits our capacity to fully comprehend the functioning of natural biological processes and is a major roadblock for the de novo design of complex synthetic circuits. A common cause of this problem is that cell-to-cell variability creates couplings between single-cell circuits and population processes such as selection or growth. Altering the circuit may then have unforeseen consequences inside growing populations. Here we construct a yeast optogenetic differentiation system that exploits cell-to-cell variability to enable external control of the population composition. We show that a simple deterministic model can explain the dynamics of the core system. However, modifying the context of the circuit by expressing system components from plasmids leads to failure of model predictions. Subsequently, we deploy theory from stochastic chemical kinetics to construct models of the system's components that simultaneously track single-cell and population processes and demonstrate that this allows us to quantitatively predict emerging dynamics of the plasmid-based system without any adjustment of model parameters. We conclude that carefully characterizing the dynamics of cell-to-cell variability using appropriate modeling theory may allow one to unravel the complex interplay of stochastic single-cell and population processes and to predict the functionality of complex synthetic circuits in growing populations before the circuit is constructed. [ABSTRACT FROM AUTHOR]

Detailed maps of the molecular basis of the disease are powerful tools for interpreting data and building predictive models. Modularity and composability are considered necessary network features for large-scale collaborative efforts to build comprehensive molecular descriptions of disease mechanisms. An effective way to create and manage large systems is to compose multiple subsystems. Composable network components could effectively harness the contributions of many individuals and enable teams to seamlessly assemble many individual components into comprehensive maps. We examine manually built versions of the RAS–RAF–MEK–ERK cascade from the Atlas of Cancer Signalling Network, PANTHER and Reactome databases and review them in terms of their reusability and composability for assembling new disease models. We identify design principles for managing complex systems that could make it easier for investigators to share and reuse network components. We demonstrate the main challenges including incompatible levels of detail and ambiguous representation of complexes and highlight the need to address these challenges. [ABSTRACT FROM AUTHOR]

In a dynamic environment, a manufacturing system should be reconfigurable to make the products with lot size of one and a high product mix in mass customization. A manufacturing system is continuously evolved to make new products at different time scales and ensure uninterrupted productions when internal or external changes occur. System evolution relates to add, remove, upgrade components, and reconfigure the system at different levels and scopes. However, scientific methods and tools are lacking to support designers in reconfiguring a system subject to given changes. This becomes a big hurdle to adopt automated solutions in small- and medium-sized enterprises. To support system reconfiguration, we propose a generic framework and methods to assess the performance of heterogeneous robotic systems or components. The proposed methods can also help 1) designers to select components for an integrated solution based on the needs and 2) robot manufacturers to identify the weaknesses of their products. [ABSTRACT FROM AUTHOR]

Current simulation models are not only represented in the form of traditional data or formula for pure theory analysis but expanded to be simulation modeling assets that are featured with complicated structure, diverse behaviors, and abundant semantics. Semantic composability, therefore, receives a constantly growing attention in recent years. So far, one of the popular solutions to enhance semantic expressiveness is domain specific modeling based on general metamodeling (GMM) facilities. But for some particular domains, researchers identified the need of deeper semantic expressiveness therefore proposed domain specific metamodeling (DSMM). Hence, this paper aims to explore the underlying methodologies of DSMM for supporting deep semantic composability. Compared with several usual alternatives based on GMM, this paper applies the multi-level metamodeling architecture to create a set of metamodeling primitives using an example named SEvent. In fact, SEvent is a novel formalism that slightly extends Petri net to support continuous states transition and continuous event triggering. As a proof of concept, we concentrate on developing the textual syntax of SEvent and using it to represent torpedo's behaviors.

Refreshing algorithms are a critical ingredient for secure masking. They are instrumental in enabling sound composability properties for complex circuits, and their randomness requirements dominate the performance overheads in (very) high-order masking. In this paper, we improve a proposal of mask refreshing algorithms from EUROCRYPT 2017 that has excellent implementation properties in software and hardware, in two main directions. First, we provide a generic proof that this algorithm is secure at arbitrary orders—a problem that was left open so far. We introduce parametrized non-interference as a new technical ingredient for this purpose that may be of independent interest. Second, we use automated tools to further explore the design space of such algorithms and provide the best known parallel mask refreshing gadgets for concretely relevant security orders. Incidentally, we also prove the security of a recent proposal of mask refreshing with improved resistance against horizontal attacks from CHES 2017. [ABSTRACT FROM AUTHOR]

We improve the state-of-the-art masking schemes in two important directions. First, we propose a new masked multiplication algorithm that satisfies a recently introduced notion called Probe-Isolating Non-Interference (PINI). It captures a sufficient requirement for designing masked implementations in a trivial way, by combining PINI multiplications and linear operations performed share by share. Our improved algorithm has the best reported randomness complexity for large security orders (while the previous PINI multiplication was best for small orders). Second, we analyze the security of most existing multiplication algorithms in the literature against so-called horizontal attacks, which aim to reduce the noise of the actual leakages measured by an adversary, by combining the information of multiple target intermediate values. For this purpose, we leave the (abstract) probing model and consider a specialization of the (more realistic) noisy leakage / random probing models. Our (still partially heuristic but quantitative) analysis allows confirming the improved security of an algorithm by Battistello et al. from CHES 2016 in this setting. We then use it to propose new improved algorithms, leading to better tradeoffs between randomness complexity and noise rate, and suggesting the possibility to design efficient masked multiplication algorithms with constant noise rate in F2.

A lack of consistent data, reliable analysis techniques, and user-friendly tools is inhibiting decision makers' abilities to assess and evaluate the sustainability performance of manufacturing processes and systems. Recent integration of information technology with advanced manufacturing technologies has led to a new paradigm, termed smart manufacturing or Industry 4.0. To leverage this paradigm shift for the advancement of sustainable manufacturing, efforts have been made to characterize unit manufacturing processes (UMPs) for sustainability assessment and to develop frameworks, methodologies, and standards utilizing information modeling approaches. This paper proposes a grey box object-oriented software framework for sustainability assessment of complex manufacturing systems, utilizing the multiple inheritance principle for composition of UMP models. Information modeling guidelines based on the framework are provided for UMP model developers and UMP performance analysts to construct and analyze system models. To demonstrate the usefulness of the framework and guidelines, a prototype information model is developed for a hybrid manufacturing system composed of fused deposition modeling (an additive process) and CNC milling (a subtractive process). [ABSTRACT FROM AUTHOR]

We present a round-efficient black-box construction of a general multi-party computation (MPC) protocol that satisfies composability in the plain model. The security of our protocol is proven in the angel-based UC framework [Prabhakaran and Sahai, STOC'04] under the minimal assumption of the existence of semi-honest oblivious transfer protocols. The round complexity of our protocol is max(O~(log2n),O(ROT)) when the round complexity of the underlying oblivious transfer protocol is ROT. Since constant-round semi-honest oblivious transfer protocols can be constructed under standard assumptions (such as the existence of enhanced trapdoor permutations), our result gives a O~(log2n)-round protocol under these assumptions. Previously, only an O(max(nϵ,ROT))-round protocol was shown, where ϵ>0 is an arbitrary constant. We obtain our MPC protocol by constructing a O~(log2n)-round CCA-secure commitment scheme in a black-box way under the assumption of the existence of one-way functions. [ABSTRACT FROM AUTHOR]

Many-core platforms are rapidly expanding in various embedded areas as they provide the scalable computational power required to meet the ever-growing performance demands of embedded applications and systems. However, the huge design space of possible task mappings, the unpredictable workload dynamism, and the numerous non-functional requirements of applications in terms of timing, reliability, safety, and so forth. impose significant challenges when designing many-core systems. Hybrid Application Mapping (HAM) is an emerging class of design methodologies for many-core systems which address these challenges via an incremental (per-application) mapping scheme: The mapping process is divided into (i) a design-time Design Space Exploration (DSE) step per application to obtain a set of high-quality mapping options and (ii) a run-time system management step in which applications are launched dynamically (on demand) using the precomputed mappings. This paper provides an overview of HAM and the design methodologies developed in line with it. We introduce the basics of HAM and elaborate on the way it addresses the major challenges of application mapping in many-core systems. We provide an overview of the main challenges encountered when employing HAM and survey a collection of state-of-the-art techniques and methodologies proposed to address these challenges. We finally present an overview of open topics and challenges in HAM, provide a summary of emerging trends for addressing them particularly using machine learning, and outline possible future directions. While there exists a large body of HAM methodologies, the techniques studied in this paper are developed, to a large extent, within the scope of invasive computing. Invasive computing introduces resource awareness into applications and employs explicit resource reservation to enable incremental application mapping and dynamic system management.

Composability and robustness against physical defaults (e.g., glitches) are two highly desirable properties for secure implementations of masking schemes. While tools exist to guarantee them separately, no current formalism enables their joint investigation. In this paper, we solve this issue by introducing a new model, the robust probing model, that is naturally suited to capture the combination of these properties. We first motivate this formalism by analyzing the excellent robustness and low randomness requirements of first-order threshold implementations, and highlighting the difficulty to extend them to higher orders. Next, and most importantly, we use our theory to design and prove the first higher-order secure, robust and composable multiplication gadgets. While admittedly inspired by existing approaches to masking (e.g., Ishai-Sahai-Wagner-like, threshold, domain-oriented), these gadgets exhibit subtle implementation differences with these state-of-the-art solutions (none of which being provably composable and robust). Hence, our results illustrate how sound theoretical models can guide practically-relevant implementations.