3,268 research outputs found

    Rule-Based Synthesis of Chains of Security Functions for Software-Defined Networks

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    Software-defined networks (SDN) offer a high degree of programmability for handling and forwarding packets. In particular, they allow network administrators to combine different security functions, such as firewalls, intrusion detection systems, and external services, into security chains designed to prevent or mitigate attacks against end user applications.These chains can benefit from formal techniques for their automated construction and verification. We propose in this paper a rule-based system for automating the composition and configuration of such chains for Android applications. Given the network characterization of an application and the set of permissions it requires, our rules construct an abstract representation of a custom security chain. This representation is then translated into a concrete implementation of the chain in pyretic, a domain-specific language for programming SDN controllers. We prove that the chains produced by our rules satisfy a number of correctness properties such as the absence of black holes or loops, and shadowing freedom, and that they are coherent with the underlying security policy

    Lightweight IPv6 network probing detection framework

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    Conflict-Aware Active Automata Learning

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    Active automata learning algorithms cannot easily handle conflict in the observation data (different outputs observed for the same inputs). This inherent inability to recover after a conflict impairs their effective applicability in scenarios where noise is present or the system under learning is mutating. We propose the Conflict-Aware Active Automata Learning (C AL) framework to enable handling conflicting information during the learning process. The core idea is to consider the so-called observation tree as a first-class citizen in the learning process. Though this idea is explored in recent work, we take it to its full effect by enabling its use with any existing learner and minimizing the number of tests performed on the system under learning, specially in the face of conflicts. We evaluate C AL in a large set of benchmarks, covering over 30 different realistic targets, and over 18,000 different scenarios. The results of the evaluation show that C AL is a suitable alternative framework for closed-box learning that can better handle noise and mutations

    Family-Based Fingerprint Analysis: A Position Paper

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    Thousands of vulnerabilities are reported on a monthly basis to security repositories, such as the National Vulnerability Database. Among these vulnerabilities, software misconfiguration is one of the top 10 security risks for web applications. With this large influx of vulnerability reports, software fingerprinting has become a highly desired capability to discover distinctive and efficient signatures and recognize reportedly vulnerable software implementations. Due to the exponential worst-case complexity of fingerprint matching, designing more efficient methods for fingerprinting becomes highly desirable, especially for variability-intensive systems where optional features add another exponential factor to its analysis. This position paper presents our vision of a framework that lifts model learning and family-based analysis principles to software fingerprinting. In this framework, we propose unifying databases of signatures into a featured finite state machine and using presence conditions to specify whether and in which circumstances a given input-output trace is observed. We believe feature-based signatures can aid performance improvements by reducing the size of fingerprints under analysis.Comment: Paper published in the Proceedings A Journey from Process Algebra via Timed Automata to Model Learning: Essays Dedicated to Frits Vaandrager on the Occasion of His 60th Birthday 202

    The DS-Pnet modeling formalism for cyber-physical system development

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    This work presents the DS-Pnet modeling formalism (Dataflow, Signals and Petri nets), designed for the development of cyber-physical systems, combining the characteristics of Petri nets and dataflows to support the modeling of mixed systems containing both reactive parts and data processing operations. Inheriting the features of the parent IOPT Petri net class, including an external interface composed of input and output signals and events, the addition of dataflow operations brings enhanced modeling capabilities to specify mathematical data transformations and graphically express the dependencies between signals. Data-centric systems, that do not require reactive controllers, are designed using pure dataflow models. Component based model composition enables reusing existing components, create libraries of previously tested components and hierarchically decompose complex systems into smaller sub-systems. A precise execution semantics was defined, considering the relationship between dataflow and Petri net nodes, providing an abstraction to define the interface between reactive controllers and input and output signals, including analog sensors and actuators. The new formalism is supported by the IOPT-Flow Web based tool framework, offering tools to design and edit models, simulate model execution on the Web browser, plus model-checking and software/hardware automatic code generation tools to implement controllers running on embedded devices (C,VHDL and JavaScript). A new communication protocol was created to permit the automatic implementation of distributed cyber-physical systems composed of networks of remote components communicating over the Internet. The editor tool connects directly to remote embedded devices running DS-Pnet models and may import remote components into new models, contributing to simplify the creation of distributed cyber-physical applications, where the communication between distributed components is specified just by drawing arcs. Several application examples were designed to validate the proposed formalism and the associated framework, ranging from hardware solutions, industrial applications to distributed software applications
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