Debating Cybersecurity or Securing a Debate?

Martinelli, Fabio; Santini, Francesco

doi:10.1007/978-3-319-17040-4_15

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…In [18], some of the authors of this paper propose how arguments can support the decision making process: the aim is to help the system security administrator to react (or not) to possible ongoing attacks. For instance, a decision can be taken either to disable traffic through port 80 or not to disable it.…”

Section: Related Workmentioning

confidence: 99%

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Network security supported by arguments

Martinelli

Santini

Yautsiukhin

2015

2015 13th Annual Conference on Privacy, Security and Trust (PST)

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Argumentation has been proved as a simple yet powerful approach to manage conflicts in reasoning with the purpose to find subsets of "surviving" arguments. Our intent is to exploit such form of resolution to support the administration of security in complex systems, e.g., in case threat countermeasures are in conflict with non-functional requirements. The proposed formalisation is able to find the required security controls and explicitly provide arguments supporting this selection. Therefore, an explanation automatically comes as part of the suggested solution, facilitating human comprehension.

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Section: Related Workmentioning

confidence: 99%

“…For instance, a decision can be taken either to disable traffic through port 80 or not to disable it. The work in [18] represents a first step along the line presented here; however, it does not consider the topology of a network.…”

Section: Related Workmentioning

confidence: 99%

Network security supported by arguments

Martinelli

Santini

Yautsiukhin

2015

2015 13th Annual Conference on Privacy, Security and Trust (PST)

Self Cite

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“…And, as in many others fields, there is some degree of conflicting information with different possible causes and solutions for a specific problem. It has been noted [11], however, that argumentation-based decisions can be manipulated by attacking key arguments to overturn the solution. In the same way, we are currently studying how to extend the user-based model to detect users that have deliberately manipulated a debate by means of their influence degree [3] and, possibly, other measures.…”

Section: Introductionmentioning

confidence: 99%

Discovering Dominant Users’ Opinions in Reddit

Alsinet¹,

Argelich²,

Béjar³

et al. 2021

Frontiers in Artificial Intelligence and Applications

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Reddit is a social news aggregation and discussion website. Users submit content to the site such as links to news, which are then voted up or down by other members who in turn, can comment on others’ posts to continue the conversation. In this work, we are interested in modeling how users interact with each other in Reddit debates, to discover the most dominant opinions in a debate. To this end, we introduce a user-based model for analysis of Reddit debates. In this model, comments by users are grouped per user, describing their opinion in relation to the root comment of the debate, and users are represented with a single node in a weighted graph, where node’s weights represent relevance of user’s opinions and edges represent agreement or disagreement relationships between users throughout the debate. In this model, agreement or disagreement between the opinions of two users is defined by aggregating the set of single interactions that have occurred between them during the debate. In this work we present a skeptical aggregation model for this task. For measuring the relevance of user’s opinions, we consider two models: one based on the score of all the user’s comments and other based on the user’s karma, as computed by the Reddit platform. We characterize the set of most dominant opinions with an argumentative-based model, using the information of disagreement between opinions and relevance of opinions.

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Hypergraph‐driven mitigation of cyberattacks

González-Granadillo

Doynikova

Kotenko

et al. 2018

Internet Technology Letters

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We extend a mitigation model that evaluates individual and combined countermeasures against multistep cyberattack scenarios. The goal is to anticipate the actions of an attacker that wants to disrupt a given system (eg, an information system). The process is driven by a hypergraph formalism, enforced with a stateful return on response investment metric that optimally evaluates, ranks, and selects appropriate countermeasures to handle ongoing and potential attacks. KEYWORDSattack graphs, countermeasure selection, mitigation, network security, return on security investment, security metrics INTRODUCTIONQuantitative financial metrics are useful in cybersecurity to evaluate mitigation plans and select the best countermeasures to handle attack scenarios. 1 The main drawback is the management of stateful meta-data, for example, how countermeasures deployed at time t−1 shall be considered when evaluating a new group of countermeasures at time t. We argue that a plausible solution is the combination of quantitative financial metrics together with attack graph formalisms. (2,3) The challenge is data management, effective processing, and visual perception when dealing with huge size attack graphs. An application of the hypergraphs allows us to reduce the size of processed attack graph by combining multiple links within 1 node. 4 In this letter, we propose to integrate a stateful quantitative financial metric, based on return on investment (ROI)-like concepts, together with a hypergraph model, in order to evaluate, rank, and select optimal countermeasures based on financial and threat impact assessment functions. The resulting solution is evaluated at each state of the system while considering the already deployed countermeasures and the effects of adding or suppressing other security actions. Section 2 and 3 provide the background and review some related work. Section 4 proposes our solution. Section 5 describes the hypergraph-driven reduction of our attack graph model. Section 6 discusses limitations and advantages of our proposal. Section 7 concludes the paper. BACKGROUNDThe return on response investment (RORI) metric proposed in Reference 1 is extended toward a new stateful return on response investment metric (hereinafter denoted as StRORI). We assume a dynamic security monitoring process, where detection tools are permanently inspecting system and network events, in order to identify attack instances. To ease the presentation of the StRORI metric, we assume a discrete monitoring system based on temporal snapshots. Each snapshot provides a list with the different nodes affected in the attack scenario, as well as all the remainder security parameters. We propose to use attack graph Internet Technology Letters. 2018;1:e38.wileyonlinelibrary.com/journal/itl2

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Debating Cybersecurity or Securing a Debate?

Cited by 6 publications

References 6 publications

Network security supported by arguments

Network security supported by arguments

Discovering Dominant Users’ Opinions in Reddit

Hypergraph‐driven mitigation of cyberattacks

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