Abstract Reaction Systems (RSs) are a qualitative model inspired by biochemical processes, where the dynamics of complex systems is modelled by a collection of local reactions. Each reaction comprises a set of reactants that triggers a set of products unless hindered by the presence of some inhibitors. The use of inhibitors introduces non-monotonic behaviours that are difficult to analyze. This work focuses on the explainability of local phenomena, like the production of certain products or the reachability of certain attractors, by separating the causes responsible for reaching them from the irrelevant elements of a possibly much larger, global statespace. The main novelty of our approach is the ability to derive sufficient conditions that combine positive dependencies (e.g., requesting the presence of some entities at a certain stage, as already done in the literature) with negative ones (e.g., requesting the absence of some entities). This is achieved by combining and extending previous “static” constructions, like the transformation to Positive RSs and the minimization of RSs with “dynamic” techniques, like the process algebraic evolution of RSs, the slicing of computation and the on-the-fly generation of negative dependencies. We compare many different combinations of the above approaches, discussing their respective benefits and trade-offs in order to identify the most convenient analysis. We demonstrate our methodology on a case study involving T cell protein interactions, showing how it can reveal critical stimulus combinations and pinpoint potential drug targets by explaining phenotype emergence. Our analysis offers new insights and greater explanatory power than existing approaches.

Abstract Reaction systems (RSs) are a computational framework inspired by biochemical mechanisms. A RS defines a finite set of reactions over a finite set of entities. Typically each reaction has a local scope, because it is concerned with a small set of entities, but complex models can involve a large number of reactions and entities, and their computation can manifest unforeseen emerging behaviours. When a deviation is detected, like the unexpected production of some entities, it is often difficult to establish its causes, e.g., which entities were directly responsible or if some reaction was misconceived. Slicing is a well-known technique for debugging, which can point out the program lines containing the faulty code. In this paper, we define the first dynamic slicer for RSs and show that it can help to detect the causes of erroneous behaviour and highlight the involved reactions for a closer inspection. To fully automate the debugging process, we propose to distil monitors for starting the slicing whenever a violation from a safety specification is detected. We have integrated our slicer in BioResolve, written in Prolog which provides many useful features for the formal analysis of RSs. We define the slicing algorithm for basic RSs and then enhance it for dealing with quantitative extensions of RSs, where timed processes and linear processes can be represented. Our framework is shown at work on suitable biologically inspired RS models.

Abstract Cause/effect analysis of complex systems is instrumental in better understanding many natural phenomena. Moreover, formal analysis requires the availability of suitable abstract computational models that somehow preserve the features of interest. Our contribution focuses on the analysis of Reaction Systems (RSs), a qualitative computational formalism inspired by biochemical reactions in living cells. The primary challenge lies in dealing with inhibition mechanisms. On the one hand, inhibitors enhance the expressiveness of the computational abstraction; on the other hand, they can introduce nonmonotonic behaviors that can be computationally hard to deal with in the analysis. We propose an encoding of RSs into an equivalent formulation without inhibitors (called Positive RSs, PRSs for short) that is easier to handle, because PRSs exhibit monotonic behaviors. The effectiveness of our transformation is witnessed by its impact on two different techniques for cause/effect analysis. The first, called slicing, allows detecting the causes of some unforeseen phenomenon by reasoning backward along a given computation. Here, PRSs can be exploited to improve the quality of the analysis. The second technique, predictor analysis, is addressed by introducing a novel tool called MuMa, which is based on must/maybe sets, whence the tool name, an original abstraction for approximating ancestor formulas. MuMa exploits PRSs to improve the performance of the analysis.

Abstract Reaction systems (RSs) are a successful natural computing framework inspired by chemical reaction networks. A RS consists of a set of entities and a set of reactions. Entities can enable or inhibit each reaction and are produced by reactions or provided by the environment. In this paper, we define two quantitative variants of RSs: the first one is along the time dimension, to specify delays for making available reactions products and durations to protract their permanency, while the second deals with the possibility to specify different concentration levels of a substance in order to enable or inhibit a reaction. Technically, both extensions are obtained by modifying in a modular way the Structural Operational Semantics (SOS) for RSs that was already defined in the literature. Our approach maintains several advantages of the original semantics definition that were: (1) providing a formal specification of the RS dynamics that enables the reuse of many formal analysis techniques and favours the implementation of tools, and (2) making the RS framework extensible, by adding or changing some of the SOS rules in a compositional way. We provide a prototype logic programming implementation and apply our tool to three different case studies: the tumour growth, the Th cell differentiation in the immune system and neural communication.

The Core Network Algebra (CNA) is a model for concurrency that extends the point-to-point communication discipline of Milner’s CCS with multiparty interactions. Links are used to build chains describing how information flows among the different agents participating in a multiparty interaction. The inherent non-determinism in deciding both the number of participants in an interaction, and how they synchronize, makes it difficult to devise verification techniques for this language. We propose a symbolic semantics and a symbolic bisimulation for CNA which are more amenable for automating reasoning. Unlike the operational semantics of CNA, the symbolic semantics is finitely branching and it represents, compactly, a possibly infinite number of transitions. We give necessary and sufficient conditions to efficiently check the validity of symbolic configurations. We also propose the Symbolic Link Modal Logic, a seamless extension of the Hennessy-Milner logic which is able to characterize the (symbolic) transitions of CNA processes. Finally, we specify both the symbolic semantics and the modal logic as an executable rewriting theory. We thus obtain several verification procedures to analyze CNA processes.

We present the link-calculus, an extension of π-calculus, that models interactions that are multiparty, i.e. that may involve more than two processes, mutually exchanging data. Communications are seen as chains of suitably combined links (which record the source and the target ends of each hop of interactions), each contributed by one party. Values are exchanged by means of message tuples, still provided by each party. We develop semantic theories and proof techniques for link-calculus and apply them in reasoning about complex distributing computing scenarios, where more than two participants need to synchronise in order to perform a task. In particular, we introduce the notion of linked bisimilarity in analogy with the early bisimilarity of the π-calculus. Differently from the π-calculus case, we can show that it is a congruence with respect to all the link-calculus operators and that is also closed under name substitution.

We investigate the expressiveness of two classical distributed paradigms by defining the first encoding of the pure mobile ambient calculus into the synchronous π-calculus. Our encoding, whose correctness has been proved by relying on the notion of operational correspondence, shows how the hierarchical ambient structure can be reformulated within a flat channel interconnection amongst independent processes, without centralised control. To easily handle the computation for simulating a capability, we introduce the notions of simulating trace (representing the computation that a π-calculus process has to execute to mimic a capability) and of aborting trace (representing the computation that a π-calculus process executes when the simulation of a capability cannot succeed). Thus, the encoding may introduce loops, but, as it will be shown, the number of steps of any trace, therefore of any aborting trace, is limited, and the number of states of the transition system of the encoding processes still remains finite. In particular, an aborting trace makes a sort of backtracking, leaving the involved sub-processes in the same starting configurations. We also discuss two run-time support methods to make these loops harmless at execution time. Our work defines a relatively simple, direct, and precise translation that reproduces the ambient structure by means of channel links, and keeps track of the dissolving of an ambient.

A type flaw attack on a security protocol is an attack where an honest principal is cheated on interpreting a field in a message as the one with a type other than the intended one. In this paper, we shall present an extension of the LYSA calculus to cope with types, by using tags to represent the i ntended types of terms. We develop a Control Flow Analysis for this calculus which soundly over-approximates all the possible behaviour of a protocol and, in particular, is able to capture any type confusion that may occur during the protocol execution. The analysis acts in a descriptive way: it describes which violations may occur. In the same setting, our approach also offers a prescriptive usage: we can impose a type discipline, by forcing some data to be of the expected types. At this point, the analysis may statically check that type violations are not possible any longer. In other words, we instrument the code with the only checks necessary to enforce type security. Finally, we apply our framework to a multi-protocol setting, where the risk of having type flaw attacks is higher. Our analysis has been implemented and successfully applied to a number of security protocols, showing it is able to capture type flaw attacks. The implementation complexity of the analysis is low polynomial.

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.

This paper develops and demonstrates an original approach to face-image analysis based on identifying distinctive areas of each individual's face by its comparison to others in the population. The method differs from most others—that we refer as unary —where salient regions are defined by analyzing only images of the same individual. We extract a set of multiscale patches from each face image before projecting them into a common feature space. The degree of “distinctiveness” of any patch depends on its distance in feature space from patches mapped from other individuals. First a pairwise analysis is developed and then a simple generalization to the multiple-face case is proposed. A perceptual experiment, involving 45 observers, indicates the method to be fairly compatible with how humans mark faces as distinct. A quantitative example of face authentication is also performed in order to show the essential role played by the distinctive information. A comparative analysis shows that performance of our n-ary approach is as good as several contemporary unary, or binary, methods, while tapping a complementary source of information. Furthermore, we show it can also provide a useful degree of illumination invariance.