6,284 research outputs found

    Toward optimal multi-objective models of network security: Survey

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    Information security is an important aspect of a successful business today. However, financial difficulties and budget cuts create a problem of selecting appropriate security measures and keeping networked systems up and running. Economic models proposed in the literature do not address the challenging problem of security countermeasure selection. We have made a classification of security models, which can be used to harden a system in a cost effective manner based on the methodologies used. In addition, we have specified the challenges of the simplified risk assessment approaches used in the economic models and have made recommendations how the challenges can be addressed in order to support decision makers

    Towards optimal multi-objective models of network security: survey

    Get PDF
    Information security is an important aspect of a successful business today. However, financial difficulties and budget cuts create a problem of selecting appropriate security measures and keeping networked systems up and running. Economic models proposed in the literature do not address the challenging problem of security countermeasure selection. We have made a classification of security models, which can be used to harden a system in a cost effective manner based on the methodologies used. In addition, we have specified the challenges of the simplified risk assessment approaches used in the economic models and have made recommendations how the challenges can be addressed in order to support decision makers

    Identifying Security-Critical Cyber-Physical Components in Industrial Control Systems

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    In recent years, Industrial Control Systems (ICS) have become an appealing target for cyber attacks, having massive destructive consequences. Security metrics are therefore essential to assess their security posture. In this paper, we present a novel ICS security metric based on AND/OR graphs that represent cyber-physical dependencies among network components. Our metric is able to efficiently identify sets of critical cyber-physical components, with minimal cost for an attacker, such that if compromised, the system would enter into a non-operational state. We address this problem by efficiently transforming the input AND/OR graph-based model into a weighted logical formula that is then used to build and solve a Weighted Partial MAX-SAT problem. Our tool, META4ICS, leverages state-of-the-art techniques from the field of logical satisfiability optimisation in order to achieve efficient computation times. Our experimental results indicate that the proposed security metric can efficiently scale to networks with thousands of nodes and be computed in seconds. In addition, we present a case study where we have used our system to analyse the security posture of a realistic water transport network. We discuss our findings on the plant as well as further security applications of our metric.Comment: Keywords: Security metrics, industrial control systems, cyber-physical systems, AND-OR graphs, MAX-SAT resolutio

    Reinforcement learning for efficient network penetration testing

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    Penetration testing (also known as pentesting or PT) is a common practice for actively assessing the defenses of a computer network by planning and executing all possible attacks to discover and exploit existing vulnerabilities. Current penetration testing methods are increasingly becoming non-standard, composite and resource-consuming despite the use of evolving tools. In this paper, we propose and evaluate an AI-based pentesting system which makes use of machine learning techniques, namely reinforcement learning (RL) to learn and reproduce average and complex pentesting activities. The proposed system is named Intelligent Automated Penetration Testing System (IAPTS) consisting of a module that integrates with industrial PT frameworks to enable them to capture information, learn from experience, and reproduce tests in future similar testing cases. IAPTS aims to save human resources while producing much-enhanced results in terms of time consumption, reliability and frequency of testing. IAPTS takes the approach of modeling PT environments and tasks as a partially observed Markov decision process (POMDP) problem which is solved by POMDP-solver. Although the scope of this paper is limited to network infrastructures PT planning and not the entire practice, the obtained results support the hypothesis that RL can enhance PT beyond the capabilities of any human PT expert in terms of time consumed, covered attacking vectors, accuracy and reliability of the outputs. In addition, this work tackles the complex problem of expertise capturing and re-use by allowing the IAPTS learning module to store and re-use PT policies in the same way that a human PT expert would learn but in a more efficient way

    Herding Vulnerable Cats: A Statistical Approach to Disentangle Joint Responsibility for Web Security in Shared Hosting

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    Hosting providers play a key role in fighting web compromise, but their ability to prevent abuse is constrained by the security practices of their own customers. {\em Shared} hosting, offers a unique perspective since customers operate under restricted privileges and providers retain more control over configurations. We present the first empirical analysis of the distribution of web security features and software patching practices in shared hosting providers, the influence of providers on these security practices, and their impact on web compromise rates. We construct provider-level features on the global market for shared hosting -- containing 1,259 providers -- by gathering indicators from 442,684 domains. Exploratory factor analysis of 15 indicators identifies four main latent factors that capture security efforts: content security, webmaster security, web infrastructure security and web application security. We confirm, via a fixed-effect regression model, that providers exert significant influence over the latter two factors, which are both related to the software stack in their hosting environment. Finally, by means of GLM regression analysis of these factors on phishing and malware abuse, we show that the four security and software patching factors explain between 10\% and 19\% of the variance in abuse at providers, after controlling for size. For web-application security for instance, we found that when a provider moves from the bottom 10\% to the best-performing 10\%, it would experience 4 times fewer phishing incidents. We show that providers have influence over patch levels--even higher in the stack, where CMSes can run as client-side software--and that this influence is tied to a substantial reduction in abuse levels

    SecCo: Automated Services to Secure Containers in the DevOps Paradigm

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    Containers are core building blocks for creating applications based on the microservice paradigm. However, assessing their security is complex, especially when deployed in distributed and heterogeneous scenarios. Moreover, developers and IT operators should only focus on integration and delivery processes without dealing with tasks to guarantee securing requirements. To overcome such issues, in this paper, we introduce the ideas at the basis of Project SecCo (Securing Containers), i.e., an architecture for extending and improving current security assessment methodologies into the continuous integration and continuous delivery DevOps pipeline. To this end, SecCo proposes a framework able to orchestrate new automatic security services to prevent and reduce security vulnerabilities in the design, implementation, and deployment phases, and to identify and mitigate, at runtime, attempts to exploit them. The paper also showcases the main research challenges to be addressed for pursuing the vision of SecCo

    A novel approach for analysis of attack graph

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    ANCHOR: logically-centralized security for Software-Defined Networks

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    While the centralization of SDN brought advantages such as a faster pace of innovation, it also disrupted some of the natural defenses of traditional architectures against different threats. The literature on SDN has mostly been concerned with the functional side, despite some specific works concerning non-functional properties like 'security' or 'dependability'. Though addressing the latter in an ad-hoc, piecemeal way, may work, it will most likely lead to efficiency and effectiveness problems. We claim that the enforcement of non-functional properties as a pillar of SDN robustness calls for a systemic approach. As a general concept, we propose ANCHOR, a subsystem architecture that promotes the logical centralization of non-functional properties. To show the effectiveness of the concept, we focus on 'security' in this paper: we identify the current security gaps in SDNs and we populate the architecture middleware with the appropriate security mechanisms, in a global and consistent manner. Essential security mechanisms provided by anchor include reliable entropy and resilient pseudo-random generators, and protocols for secure registration and association of SDN devices. We claim and justify in the paper that centralizing such mechanisms is key for their effectiveness, by allowing us to: define and enforce global policies for those properties; reduce the complexity of controllers and forwarding devices; ensure higher levels of robustness for critical services; foster interoperability of the non-functional property enforcement mechanisms; and promote the security and resilience of the architecture itself. We discuss design and implementation aspects, and we prove and evaluate our algorithms and mechanisms, including the formalisation of the main protocols and the verification of their core security properties using the Tamarin prover.Comment: 42 pages, 4 figures, 3 tables, 5 algorithms, 139 reference
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