Lorina Negreanu

SymNet: Scalable symbolic execution for modern networks

We present SymNet, a network static analysis tool based on symbolic execution. SymNet injects symbolic packets and tracks their evolution through the network. Our key novelty is SEFL, a language we designed for expressing data plane processing in a symbolic-execution friendly manner. SymNet statically analyzes an abstract data plane model that consists of the SEFL code for every node and the links between nodes. SymNet can check networks containing routers with hundreds of thousands of prefixes and NATs in seconds, while verifying packet header memory-safety and covering network functionality such as dynamic tunneling, stateful processing and encryption. We used SymNet to debug mid- dlebox interactions from the literature, to check properties of our department’s network and the Stanford backbone. Modeling network functionality is not easy. To aid users we have developed parsers that automatically generate SEFL models from router and switch tables, firewall configura- tions and arbitrary Click modular router configurations. The parsers rely on prebuilt models that are exact and fast to an- alyze. Finally, we have built an automated testing tool that combines symbolic execution and testing to check whether the model is an accurate representation of the real code.

SymNet: static checking for stateful networks

Todays networks deploy many stateful procesing boxes ranging from NATs to firewalls and application optimizers: these boxes operate on packet flows, rather than individual packets. As more and more middleboxes are deployed, understanding their composition is becoming increasingly difficult. Static checking of network configurations is a promising approach to help understand whether a network is configured properly, but existing tools are limited as they only support stateless processing. We propose to use symbolic execution---a technique prevalent in compilers---to check network properties more general than basic reachability. The key idea is to track the possible values for specified fields in the packet as it travels through a network. Each middlebox or router will impose constraints on certain fields of the packet via forwarding actions, packet modifications and filtering. The symbolic approach also allows us to model middlebox per-flow state in a scalable way. We have implemented this technique in a tool we call SymNet and conducted preliminary evaluation. Early results show SymNet scales well and models basic stateful middleboxes, opening the possibility of analyzing complex stateful middlebox behaviours.

An Ontology-Based Dynamic Service Composition Framework for Intelligent Houses

In order to improve users ability to interact with devices in an intelligent house, we propose a platform for intelligent device composition, based on Service Oriented Architecture. In such an environment, devices can be controlled and monitored using Service invocations, or they can interoperate in order to fulfil complex tasks, using Service composition. As part of our platform, we define a language for dynamic service composition, called MetaBPEL. It extends the WS-BPEL 2.0 language with semantic information, and acts as an abstract workflow definition mechanism. Unlike BPEL and other conventional composition languages, MetaBPEL does not bind to actual service implementations, but merely describes capabilities that services must have, in order to participate in a workflow. This feature allows both workflow migration between different environments as well as service replacement without modifying the composition scheme. In the article, we describe the MetaBPEL structure and the associated creation, generalization and instantiation mechanisms.

A Multi-Agent System for Service Acquiring in Smart Environments

This paper proposes a multi-agent system architecture for a service acquiring system. The proposed system is integrated in an ambient intelligent system, AmIHomCare, a smart house who supervises elderly people in their homes and also helps people during their daily activities. The service acquiring system is specified and validated using a formal specification method - Event B.

Genetic Algorithms Viewed as Anticipatory Systems

This paper proposes a new version of genetic algorithms—the anticipatory genetic algorithm AGA. The performance evaluation included in the paper shows that AGA is superior to traditional genetic algorithm from both speed and accuracy points of view. The paper also presents how this algorithm can be applied to solve a complex problem: image annotation, intended to be used in content based image retrieval systems.

A modeling method and declarative language for temporal reasoning based on fluid qualities

Current knowledge representation mechanisms focus more on providing a static description of a modeled universe and less on capturing evolution. Ontology modeling languages, such as OWL, have no inherent means for describing time or time-dependent properties. In such settings, time is usually represented along with other applicationdependent concepts, yielding complex models that are difficult to maintain, extend, and reason about. On the other hand, in imperative languages that allow the definition of time-dependent behavior and interactions such as WS-BPEL, the emphasis is on specifying the control flow in a service-oriented environment. In contrast, we argue that a declarative approach is more suitable. We propose a modeling method and a declarative language, designed for representing and reasoning about time-dependent properties. The method is applicable in areas such as ubiquitous computing, allowing the specification of intelligent device behaviour.

Strategic Behaviour in Multi-Agent Systems Able to Perform Temporal Reasoning

Temporal reasoning and strategic behaviour are important abilities of Multi-Agent Systems. We introduce a method suitable for modelling agents which can store and reason about the evolution of an environment, and which can reason strategically, that is, make a rational and self-interested choice, in an environment where all other agents will behave in the same way. We introduce a game-theoretic formal framework, and provide with a computational characterisation of our solution concepts, which suggests that our method can easily be put into practice.

Modeling Ontologies for Time-Dependent Applications

The typical approach for declaratively reasoning about phenomena that evolves in time is to use a cognitive system centered on the given problem domain ontology as a vehicle for knowledge representation and processing. Current ontological-based approaches are successful only for the static structural description of a given domain of discourse. We present a modeling approach suitable for building and processingontologies for applications where time-dependent evolution is of crucial importance. We also present the underlying concepts that form the basis of our modeling method and describe the temporal graph used for linking these concepts in order to encode the model evolution. That graph can be inspected in order to analyze the current and past events that a model generates, and their effects, and can be used for predicting he future model behavior. We present results on the capability of the modeling method to correctly describe temporal knowledge.

Debugging P4 programs with vera

We present Vera, a tool that verifies P4 programs using symbolic execution. Vera automatically uncovers a number of common bugs including parsing/deparsing errors, invalid memory accesses, loops and tunneling errors, among others. Vera can also be used to verify user-specified properties in a novel language we call NetCTL. To enable scalable, exhaustive verification of P4 program snapshots, Vera automatically generates all valid header layouts and uses a novel data-structure for match-action processing optimized for verification. These techniques allow Vera to scale very well: it only takes between 5s-15s to track the execution of a purely symbolic packet in the largest P4 program currently available (6KLOC) and can compute SEFL model updates in milliseconds. Vera can also explore multiple concrete dataplanes at once by allowing the programmer to insert symbolic table entries; the resulting verification highlights possible control plane errors. We have used Vera to analyze many P4 programs including the P4 tutorials, P4 programs in the research literature and the switch code from https://p4.org. Vera has found several bugs in each of them in seconds/minutes.

Modeling Non-starvation in Multi-agent Systems

Event-B is a formal method which uses first-order logic and set theory as the underlying mathematical notation for specifying and reasoning about discrete systems. Rod in is an Eclipse plug-in that offers a good tool support for Event-B. The aim of this paper consists in applying Event-B and Rod in to prove the non-starvation property of satisfying requests for services in a multi-agent system.