1,566 research outputs found

    Analysis of the Impact of Data Normalization on Cyber Event Correlation Query Performance

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    A critical capability required in the operation of cyberspace is the ability to maintain situational awareness of the status of the infrastructure elements that constitute cyberspace. Event logs from cyber devices can yield significant information, and when properly utilized they can provide timely situational awareness about the state of the cyber infrastructure. In addition, proper Information Assurance requires the validation and verification of the integrity of results generated by a commercial log analysis tool. Event log analysis can be performed using relational databases. To enhance database query performance, previous literatures affirm denormalization of databases. Yet database normalization can also increase query performance. Database normalization improved the majority of the queries performed using very large data sets of router events. In addition, queries performed faster on normalized tables when all the necessary data were contained in the normalized tables. Database normalization improves table organization and maintains better data consistency than a lack of normalization. Nonetheless, there are some tradeoffs when normalizing a database, such as additional preprocessing time and extra storage requirements. But overall, normalization improved query performance and must be considered an option when analyzing event logs using relational databases. There are three primary research questions addressed in this thesis: (1) What standards exist for the generation, transport, storage, and analysis of event log data for security analysis?; (2) How does database normalization impact query performance when using very large data sets (over 30 million) of router events?; and (3) What are the tradeoffs between using a normalized versus non-normalized database in terms of preprocessing time, query performance, storage requirements, and database consistency

    Statically-analyzed stream monitoring for cyber-physical Systems

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    Cyber-physical systems are digital systems interacting with the physical world. Even though this induces an inherent complexity, they are responsible for safety-critical tasks like governing nuclear power plants or controlling autonomous vehicles. To preserve trust into the safety of such systems, this thesis presents a runtime verification approach designed to generate trustworthy monitors from a formal specification. These monitors are responsible for observing the cyber-physical system during runtime and ensuring its safety. As underlying language, I present the asynchronous real-time specification language RTLola. It contains primitives for arithmetic properties and grants precise control over the timing of the monitor. With this, it enables specifiers to express properties relevant to cyber-physical systems. The thesis further presents a static analysis that identifies inconsistencies in the specification and provides insights into the dynamic behavior of the monitor. As a result, the resource consumption of the monitor becomes predictable. The generation of the monitor produces either a hardware description synthesizable onto programmable hardware, or Rust code with verification annotation. These annotations allow for proving the correctness of the monitor with respect to the semantics of RTLola. Last, I present the construction of a conservative hybrid model of the underlying system using information extracted from the specification. This model enables further verification steps.Cyber-physische Systeme sind digitale Systeme, die mit der physischen Welt interagieren. Obwohl das zu einer inhärenten Komplexität führt, sind sie verantwortlich für sicherheitskritische Aufgaben wie der Steuerung von Kernkraftwerken oder autonomen Fahrzeugen. Umdas Vertrauen in deren Sicherheit zu wahren, präsentiert diese Doktorarbeit einen Ansatz zur Laufzeitverifikation, konzipiert, um vertrauenswürdige Monitore aus einer formalen Spezifikation zu generieren. Diese Monitore sind dafür verantwortlich, das cyber-physische System zur Laufzeit zu überwachen und dessen Sicherheit zu gewährleisten. Als zugrundeliegende Sprache präsentiere ich die asynchrone Echtzeit-Spezifikationssprache RTLola. Sie enthält Primitiven für arithmetische Eigenschaften und gewährt präzise Kontrolle über das Timing des Monitors. Damit wird es Spezifizierenden ermöglicht Eigenschaften auszudrücken, die für Cyber-physische Systeme relevant sind. Weiterhin präsentiert diese Doktorarbeit eine statische Analyse, die Unstimmigkeiten in der Spezifikation identifiziert und Einblicke in das dynamische Verhalten des Monitors liefert. Aufgrund dessen wird der Ressourcenverbrauch des Monitors vorhersehbar. Die Generierung des Monitors erzeugt entweder eine Hardwarebeschreibung, die auf programmierbarer Hardware synthetisiert werden kann, oder Rust Code mit Verifikationsannotationen. Diese Annotationen erlauben es, die Korrektheit des Monitors bezogen auf die Semantik von RTLola zu beweisen. Abschließend präsentiere ich die Konstruktion von einem konservativen hybriden Modell des zugrundeliegenden Systems anhand von Informationen, die aus der Spezifikation gewonnen wurden. Dieses Modell ermöglicht weitere Verifikationsschritte

    CPSDebug: Automatic failure explanation in CPS models

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    AbstractDebugging cyber-physical system (CPS) models is a cumbersome and costly activity. CPS models combine continuous and discrete dynamics—a fault in a physical component manifests itself in a very different way than a fault in a state machine. Furthermore, faults can propagate both in time and space before they can be detected at the observable interface of the model. As a consequence, explaining the reason of an observed failure is challenging and often requires domain-specific knowledge. In this paper, we propose approach, a novel CPSDebug that combines testing, specification mining, and failure analysis, to automatically explain failures in Simulink/Stateflow models. In particular, we address the hybrid nature of CPS models by using different methods to infer properties from continuous and discrete state variables of the model. We evaluate CPSDebug on two case studies, involving two main scenarios and several classes of faults, demonstrating the potential value of our approach

    Undetectable GPS-Spoofing Attack on Time Series Phasor Measurement Unit Data

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    The Phasor Measurement Unit (PMU) is an important metering device for smart grid. Like any other Intelligent Electronic Device (IED), PMUs are prone to various types of cyberattacks. However, one form of attack is unique to the PMU, the GPS-spoofing attack, where the time and /or the one second pulse (1 PPS) that enables time synchronization are modified and the measurements are computed using the modified time reference. This article exploits the vulnerability of PMUs in their GPS time synchronization signal. At first, the paper proposes an undetectable gradual GPS-spoofing attack with small incremental angle deviation over time. The angle deviation changes power flow calculation through the branches of the grids, without alerting the System Operator (SO) during off-peak hour. The attacker keeps instigating slow incremental variation in power flow calculation caused by GPS-spoofing relentlessly over a long period of time, with a goal of causing the power flow calculation breach the MVA limit of the branch at peak-hour. The attack is applied by solving a convex optimization criterion at regular time interval, so that after a specific time period the attack vector incurs a significant change in the angle measurements transmitted by the PMU. Secondly, while the attack modifies the angle measurements with GPS-spoofing attack, it ensures the undetectibility of phase angle variation by keeping the attack vector less than attack detection threshold. The proposed attack model is tested with Weighted Least Squared Error (WLSE), Kalman Filtering, and Hankel-matrix based GPS-spoofing attack detection models. Finally, we have proposed a gradient of low-rank approximation of Hankel-matrix based detection method to detect such relentless small incremental GPS-spoofing attack

    MAKE-IT—A Lightweight Mutual Authentication and Key Exchange Protocol for Industrial Internet of Things

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    Continuous development of the Industrial Internet of Things (IIoT) has opened up enormous opportunities for the engineers to enhance the efficiency of the machines. Despite the development, many industry administrators still fear to use Internet for operating their machines due to untrusted nature of the communication channel. The utilization of internet for managing industrial operations can be widespread adopted if the authentication of the entities are performed and trust is ensured. The traditional schemes with their inherent security issues and other complexities, cannot be directly deployed to resource constrained network devices. Therefore, we have proposed a strong mutual authentication and secret key exchange protocol to address the vulnerabilities of the existing schemes. We have used various cryptography operations such as hashing, ciphering, and so forth, for providing secure mutual authentication and secret key exchange between different entities to restrict unauthorized access. Performance and security analysis clearly demonstrates that the proposed work is energy efficient (computation and communication inexpensive) and more robust against the attacks in comparison to the traditional scheme
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