Synthesis for defeating adversaries with limited capabilities

Reactive synthesis is a potent technique enabling the automatic generation of correct-by-construction implementations of systems based on formal specifications (Bloem et al.,2018; Ehlers et al., 2015; Majumdar et al., 2019). This approach ensures that the synthesized system satisfies its specifications, regardless of the environment’s behavior, making it a more robust alternative to planning. However, reactive synthesis may fail when no system can fulfill the specification against all potential environment behaviors, such as cases where the environment prevents the system from achieving its objectives (Kress-Gazit et al., 2018). To mitigate this issue, researchers often introduce assumptions to constrain the environment’s behavior, ensuring the synthesized system operates correctly when these assumptions hold. This method, however, introduces another challenge, as the synthesized implementations might be motivated to work against the satisfaction of these assumptions (Bloemet al., 2015; Majumdar et al., 2019). An alternative viewpoint treats the interaction between the environment and the system as a strategic game, where an equilibrium between both players’ strategies is computed to guarantee that neither has an incentive to deviate. However,this approach necessitates knowledge of the environment’s objectives to facilitate strategic reasoning. In traditional reactive synthesis, environments can exhibit arbitrary behavior within their limits, with observed behavior providing no useful information. This prompts the question of whether an alternative definition for the synthesis problem could enable the formal synthesis of a correct-by-construction system in environments with unknown behaviors. Drawing inspiration from real-world adversaries, we limit the environment’s behavior. Quantifying the environment’s capabilities is crucial for solving this problem effectively, as without such constraints, the environment could act antagonistically, as in classical reactive synthesis. Concurrently, we aim to develop a controller that consistently functions correctly against the environment’s simple behaviors. In this thesis, we address the issue by restricting the environment’s behavior through limitations on a) behavioral complexity, b) observational capability, or c) the ability to modify operational space.Computer Science

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 25th International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2022, which was held during April 4-6, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 23 regular papers presented in this volume were carefully reviewed and selected from 77 submissions. They deal with research on theories and methods to support the analysis, integration, synthesis, transformation, and verification of programs and software systems

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 25th International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2022, which was held during April 4-6, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 23 regular papers presented in this volume were carefully reviewed and selected from 77 submissions. They deal with research on theories and methods to support the analysis, integration, synthesis, transformation, and verification of programs and software systems

Decision-making for autonomous agents in adversarial or information-scarce settings

Autonomous agents often operate in adversarial or information-scarce settings. These settings exist due to various factors, such as the coexistence of non-cooperative agents, computation limitations, communication losses, and imperfect sensors. To ensure high performance in the presence of such factors, decision-making algorithms for autonomous agents must limit the amount of sensitive information leaked to adversaries and rely on minimal information about their environment. We consider a variety of problems where an autonomous agent operates in an adversarial or information-scarce setting, and present novel theory and decision-making algorithms for these problems. First, we focus on an adversarial setting where a malicious agent aims to deceive its supervisor in probabilistic supervisory control setting. We formulate the deception problem as an expected cost minimization problem in a Markov decision process (MDP) where the cost function is motivated by the results from hypothesis testing. We show the existence of an optimal stationary deceptive policy and provide algorithms for the synthesis of optimal deceptive policies. From the perspective of the supervisor, we prove the NP-hardness of synthesizing optimal reference policies that prevent deception. We also show that synthesizing optimal deceptive policies under partial observations is NP-hard and provide synthesis algorithms by considering special classes of policies and MDPs. Second, as a part of decision-making in information-scarce settings, we consider a multiagent decision-making problem where a group of agents cooperates under communication losses. We model this problem with a multiagent MDP, quantify the intrinsic dependencies between the agents induced by their joint policy, and develop a decentralized policy execution algorithm for communication losses. For a variety of communication loss models, we provide performance lower bounds that are functions of the dependencies between the agents. We develop an algorithm for the synthesis of minimally dependent policies that optimize these lower bounds and thereby remain performant under communication losses. Finally, we consider the problem of optimization under limited information since autonomous agents often perform optimization as a part of their operation. We develop optimization algorithms for smooth convex optimization using sub-zeroth-order oracles that provide less information than zeroth and first-order oracles. For the directional preference oracle that outputs the sign of the directional derivative at the query point and direction, we show a ̃(⁴) sample complexity upper bound where is the number of dimensions. For the comparator oracle that compares the function value at two query points and outputs a binary comparison value, we show a ̃(⁴) sample complexity upper bound. For the noisy value oracle, we develop an algorithm with ̃( [superscript 3.75] [superscript 0.75]) high probability regret bound where is the number of queries.Electrical and Computer Engineerin

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Cyber Law and Espionage Law as Communicating Vessels

Professor Lubin\u27s contribution is Cyber Law and Espionage Law as Communicating Vessels, pp. 203-225. Existing legal literature would have us assume that espionage operations and “below-the-threshold” cyber operations are doctrinally distinct. Whereas one is subject to the scant, amorphous, and under-developed legal framework of espionage law, the other is subject to an emerging, ever-evolving body of legal rules, known cumulatively as cyber law. This dichotomy, however, is erroneous and misleading. In practice, espionage and cyber law function as communicating vessels, and so are better conceived as two elements of a complex system, Information Warfare (IW). This paper therefore first draws attention to the similarities between the practices – the fact that the actors, technologies, and targets are interchangeable, as are the knee-jerk legal reactions of the international community. In light of the convergence between peacetime Low-Intensity Cyber Operations (LICOs) and peacetime Espionage Operations (EOs) the two should be subjected to a single regulatory framework, one which recognizes the role intelligence plays in our public world order and which adopts a contextual and consequential method of inquiry. The paper proceeds in the following order: Part 2 provides a descriptive account of the unique symbiotic relationship between espionage and cyber law, and further explains the reasons for this dynamic. Part 3 places the discussion surrounding this relationship within the broader discourse on IW, making the claim that the convergence between EOs and LICOs, as described in Part 2, could further be explained by an even larger convergence across all the various elements of the informational environment. Parts 2 and 3 then serve as the backdrop for Part 4, which details the attempt of the drafters of the Tallinn Manual 2.0 to compartmentalize espionage law and cyber law, and the deficits of their approach. The paper concludes by proposing an alternative holistic understanding of espionage law, grounded in general principles of law, which is more practically transferable to the cyber realmhttps://www.repository.law.indiana.edu/facbooks/1220/thumbnail.jp

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp