Combining behavioural types with security analysis

Today's software systems are highly distributed and interconnected, and they increasingly rely on communication to achieve their goals; due to their societal importance, security and trustworthiness are crucial aspects for the correctness of these systems. Behavioural types, which extend data types by describing also the structured behaviour of programs, are a widely studied approach to the enforcement of correctness properties in communicating systems. This paper offers a unified overview of proposals based on behavioural types which are aimed at the analysis of security properties

Advancements in the Elicitation and Aggregation of Private Information

There are many situations where one might be interested in eliciting and aggregating the private information of a group of agents. For example, a recommendation system might suggest recommendations based on the aggregate opinions of a group of like-minded agents, or a decision maker might take a decision based on the aggregate forecasts from a group of experts. When agents are self-interested, they are not necessarily honest when reporting their private information. For example, agents who have a reputation to protect might tend to produce forecasts near the most likely group consensus, whereas agents who have a reputation to build might tend to overstate the probabilities of outcomes they feel will be understated in a possible consensus. Therefore, economic incentives are necessary to incentivize self-interested agents to honestly report their private information. Our first contribution in this thesis is a scoring method to induce honest reporting of an answer to a multiple-choice question. We formally show that, in the presence of social projection, one can induce honest reporting in this setting by comparing reported answers and rewarding agreements. Our experimental results show that the act of encouraging honest reporting through the proposed scoring method results in more accurate answers than when agents have no direct incentives for expressing their true answers. Our second contribution is about how to incentivize honest reporting when private information are subjective probabilities (beliefs). Proper scoring rules are traditional scoring methods that incentivize honest reporting of subjective probabilities, where the expected score received by an agent is maximized when that agent reports his true belief. An implicit assumption behind proper scoring rules is that agents are risk neutral. In an experiment involving proper scoring rules, we find that human beings fail to be risk neutral. We then start our discussion on how to adapt proper scoring rules to cumulative prospect theory, a modern theory of choice under uncertainty. We explain why a property called comonotonicity is a sufficient condition for proper scoring rules to be indeed proper under cumulative prospect theory. Moreover, we show how to construct a comonotonic proper scoring rule from any traditional proper scoring rule. We also propose a new approach that uses non-deterministic payments based on proper scoring rules to elicit an agent's true belief when the components that drive the agent's attitude towards uncertainty are unknown. After agents report their private information, there is still the question on how to aggregate the reported information. Our third contribution in this thesis is an empirical study on the influence of the number of agents on the quality of the aggregate information in a crowdsourcing setting. We find that both the expected error in the aggregate information as well as the risk of a poor combination of agents decrease as the number of agents increases. Moreover, we find that the top-performing agents are consistent across multiple tasks, whereas worst-performing agents tend to be inconsistent. Our final contribution in this thesis is a pooling method to aggregate reported beliefs. Intuitively, the proposed method works as if the agents were continuously updating their beliefs in order to accommodate the expertise of others. Each updated belief takes the form of a linear opinion pool, where the weight that an agent assigns to a peer's belief is inversely related to the distance between their beliefs. In other words, agents are assumed to prefer beliefs that are close to their own beliefs. We prove that such an updating process leads to consensus, i.e., the agents all converge towards the same belief. Further, we show that if risk-neutral agents are rewarded using the quadratic scoring rule, then the assumption that they prefer beliefs that are close to their own beliefs follows naturally. We empirically demonstrate the effectiveness of the proposed method using real-world data. In particular, the results of our experiment show that the proposed method outperforms the traditional unweighted average approach and another distance-based method when measured in terms of both overall accuracy and absolute error

How many crowdsourced workers should a requester hire?

Recent years have seen an increased interest in crowdsourcing as a way of obtaining information from a potentially large group of workers at a reduced cost. The crowdsourcing process, as we consider in this paper, is as follows: a requester hires a number of workers to work on a set of similar tasks. After completing the tasks, each worker reports back outputs. The requester then aggregates the reported outputs to obtain aggregate outputs. A crucial question that arises during this process is: how many crowd workers should a requester hire? In this paper, we investigate from an empirical perspective the optimal number of workers a requester should hire when crowdsourcing tasks, with a particular focus on the crowdsourcing platform Amazon Mechanical Turk. Specifically, we report the results of three studies involving different tasks and payment schemes. We find that both the expected error in the aggregate outputs as well as the risk of a poor combination of workers decrease as the number of workers increases. Surprisingly, we find that the optimal number of workers a requester should hire for each task is around 10 to 11, no matter the underlying task and payment scheme. To derive such a result, we employ a principled analysis based on bootstrapping and segmented linear regression. Besides the above result, we also find that overall top-performing workers are more consistent across multiple tasks than other workers. Our results thus contribute to a better understanding of, and provide new insights into, how to design more effective crowdsourcing processes

Lack of spatial segregation in the representation of pheromones and kairomones in the mouse medial amygdala

The nervous system is organized to detect, internally represent and process sensory information to generate appropriate behaviors. Despite the crucial importance of odors that elicit instinctive behaviors, such as pheromones and kairomones, their neural representation remains little characterized in the mammalian brain. Here we used expression of the immediate early gene product c-Fos as a marker of neuronal activity to find that a wide range of pheromones and kairomones produces activation in the medial nucleus of the amygdala, a brain area anatomically connected with the olfactory sensory organs. We see that activity in this nucleus depends on vomeronasal organ input, and that distinct vomeronasal stimuli activate a dispersed ensemble of cells, without any apparent spatial segregation. This activity pattern does not reflect the chemical category of the stimuli, their valence or the induced behaviors. These findings will help build a complete understanding of how odor information is processed in the brain to generate instinctive behaviors.9FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP09/00473-

The Cellular Context of Estradiol Regulation in the Zebra Finch Auditory Forebrain

Estradiol, traditionally known as a hormone that communicates with distant cells in the body, is also synthesized locally in the brain to act as a neuromodulator. Neuromodulators differ from neurotransmitters in that they simultaneously affect a population of neurons and their actions are not limited to the synapse. One of the many effects of estradiol signaling is rapid modulation of auditory processing in response to external stimuli. The enzyme required for estradiol synthesis, aromatase, is highly expressed in the regions that are involved in higher-order processing of sounds in humans and songbirds. Since zebra finches, a type of songbird, are one of the few laboratory animals that communicate via complex learned vocalization, they are commonly used as a model for vocal learning and auditory processing. Although many aspects of the actions of estradiol in the zebra finch forebrain have been revealed, little is known regarding how estradiol levels are regulated via aromatase activity. First, this dissertation describes the procedure for in vivo microdialysis, a method that allows local estradiol detection in freely moving animals. Second, using in vivo microdialysis, we investigated whether another neuromodulator, norepinephrine, regulates global estradiol levels within a secondary auditory region, caudomedial nidopallium (NCM). The results showed no evidence that norepinephrine has a major role in controlling estradiol levels in the NCM. However, in vivo electrophysiological vi recordings from the NCM revealed that norepinephrine has a similar role in auditory processing as estradiol but acts via a different mechanism. Finally, the dissertation examined the identities and organization of aromatase-expressing neurons and found that the heterogeneity of aromatase cells was different between different aromatase-positive regions. Aromatase-expressing cell bodies were found to be more prominent in regions with low expression of a transmembrane G-protein coupled estrogen receptor, GPER1, while high pre-synaptic aromatase-expressing regions expressed high amounts of GPER1. Moreover, aromatase-expressing cells were found in somato-somatic clusters. Preliminary data injecting dyes in clustered cells indicate that the neurons in clusters may be communicating with one another through gap junctions. Overall, this dissertation provides new knowledge for understanding the relationship between neuronal interactions and aromatase signaling in the context of auditory processing

IST Austria Thesis

Mosaic genetic analysis has been widely used in different model organisms such as the fruit fly to study gene-function in a cell-autonomous or tissue-specific fashion. More recently, and less easily conducted, mosaic genetic analysis in mice has also been enabled with the ambition to shed light on human gene function and disease. These genetic tools are of particular interest, but not restricted to, the study of the brain. Notably, the MADM technology offers a genetic approach in mice to visualize and concomitantly manipulate small subsets of genetically defined cells at a clonal level and single cell resolution. MADM-based analysis has already advanced the study of genetic mechanisms regulating brain development and is expected that further MADM-based analysis of genetic alterations will continue to reveal important insights on the fundamental principles of development and disease to potentially assist in the development of new therapies or treatments. In summary, this work completed and characterized the necessary genome-wide genetic tools to perform MADM-based analysis at single cell level of the vast majority of mouse genes in virtually any cell type and provided a protocol to perform lineage tracing using the novel MADM resource. Importantly, this work also explored and revealed novel aspects of biologically relevant events in an in vivo context, such as the chromosome-specific bias of chromatid sister segregation pattern, the generation of cell-type diversity in the cerebral cortex and in the cerebellum and finally, the relevance of the interplay between the cell-autonomous gene function and cell-non-autonomous (community) effects in radial glial progenitor lineage progression. This work provides a foundation and opens the door to further elucidating the molecular mechanisms underlying neuronal diversity and astrocyte generation

Behavioural Types: from Theory to Tools

This book presents research produced by members of COST Action IC1201: Behavioural Types for Reliable Large-Scale Software Systems (BETTY), a European research network that was funded from October 2012 to October 2016. The technical theme of BETTY was the use of behavioural type systems in programming languages, to specify and verify properties of programs beyond the traditional use of type systems to describe data processing. A significant area within behavioural types is session types, which concerns the use of type-theoretic techniques to describe communication protocols so that static typechecking or dynamic monitoring can verify that protocols are implemented correctly. This is closely related to the topic of choreography, in which system design starts from a description of the overall communication flows. Another area is behavioural contracts, which describe the obligations of interacting agents in a way that enables blame to be attributed to the agent responsible for failed interaction. Type-theoretic techniques can also be used to analyse potential deadlocks due to cyclic dependencies between inter-process interactions. BETTY was organised into four Working Groups: (1) Foundations; (2) Security; (3) Programming Languages; (4) Tools and Applications. Working Groups 1–3 produced “state-of-the-art reports”, which originally intended to take snapshots of the field at the time the network started, but grew into substantial survey articles including much research carried out during the network [1–3]. The situation for Working Group 4 was different. When the network started, the community had produced relatively few implementations of programming languages or tools. One of the aims of the network was to encourage more implementation work, and this was a great success. The community as a whole has developed a greater interest in putting theoretical ideas into practice. The sixteen chapters in this book describe systems that were either completely developed, or substantially extended, during BETTY. The total of 41 co-authors represents a significant proportion of the active participants in the network (around 120 people who attended at least one meeting). The book is a report on the new state of the art created by BETTY in xv xvi Preface the area of Working Group 4, and the title “Behavioural Types: from Theory to Tools” summarises the trajectory of the community during the last four years. The book begins with two tutorials by Atzei et al. on contract-oriented design of distributed systems. Chapter 1 introduces the CO2 contract specifi- cation language and the Diogenes toolchain. Chapter 2 describes how timing constraints can be incorporated into the framework and checked with the CO2 middleware. Part of the CO2 middleware is a monitoring system, and the theme of monitoring continues in the next two chapters. In Chapter 3, Attard et al. present detectEr, a runtime monitoring tool for Erlang programs that allows correctness properties to be expressed in Hennessy-Milner logic. In Chapter 4, which is the first chapter about session types, Neykova and Yoshida describe a runtime verification framework for Python programs. Communication protocols are specified in the Scribble language, which is based on multiparty session types. The next three chapters deal with choreographic programming. In Chap- ter 5, Debois and Hildebrandt present a toolset for working with dynamic condition response (DCR) graphs, which are a graphical formalism for choreography. Chapter 6, by Lange et al., continues the graphical theme with ChorGram, a tool for synthesising global graphical choreographies from collections of communicating finite-state automata. Giallorenzo et al., in Chapter 7, consider runtime adaptation. They describe AIOCJ, a choreographic programming language in which runtime adaptation is supported with a guarantee that it doesn’t introduce deadlocks or races. Deadlock analysis is important in other settings too, and there are two more chapters about it. In Chapter 8, Padovani describes the Hypha tool, which uses a type-based approach to check deadlock-freedom and lock-freedom of systems modelled in a form of pi-calculus. In Chapter 9, Garcia and Laneve present a tool for analysing deadlocks in Java programs; this tool, called JaDA, is based on a behavioural type system. The next three chapters report on projects that have added session types to functional programming languages in order to support typechecking of communication-based code. In Chapter 10, Orchard and Yoshida describe an implementation of session types in Haskell, and survey several approaches to typechecking the linearity conditions required for safe session implemen- tation. In Chapter 11, Melgratti and Padovani describe an implementation of session types in OCaml. Their system uses runtime linearity checking. In Chapter 12, Lindley and Morris describe an extension of the web programming language Links with session types; their work contrasts with the previous two chapters in being less constrained by an existing language design. Continuing the theme of session types in programming languages, the next two chapters describe two approaches based on Java. Hu’s work, presented in Chapter 13, starts with the Scribble description of a multiparty session type and generates an API in the form of a collection of Java classes, each class containing the communication methods that are available in a particular state of the protocol. Dardha et al., in Chapter 14, also start with a Scribble specification. Their StMungo tool generates an API as a single class with an associated typestate specification to constrain sequences of method calls. Code that uses the API can be checked for correctness with the Mungo typechecker. Finally, there are two chapters about programming with the MPI libraries. Chapter 15, by Ng and Yoshida, uses an extension of Scribble, called Pabble, to describe protocols that parametric in the number of runtime roles. From a Pabble specification they generate C code that uses MPI for communication and is guaranteed correct by construction. Chapter 16, by Ng et al., describes the ParTypes framework for analysing existing C+MPI programs with respect to protocols defined in an extension of Scribble. We hope that the book will serve a useful purpose as a report on the activities of COST Action IC1201 and as a survey of programming languages and tools based on behavioural types