Towards the autonomous provision of self-protection capabilities in 5G networks

Celdrán, Alberto Huertas; Pérez, Manuel Gil; Clemente, Félix J. García; Pérez, Gregorio Martínez

doi:10.1007/s12652-018-0848-6

Cited by 17 publications

(10 citation statements)

References 26 publications

(24 reference statements)

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“…In this sense, the number and frequency of newly-discovered vulnerabilities are constantly increasing, posing a complex challenge to the CSIRT (Computer Security Incident Response Teams). Such growth is mainly due to the sophistication of modern assets but also to the high demand for new market-ready functionalities [1].…”

Section: A Rationalementioning

confidence: 99%

“…Nevertheless, B(cm i ) is shifted to reside in the interval [1,10] by adding ω in Equation 10 to preserve the compatibility with other security scoring systems. Consequently, if the enforcement of a certain atomic countermeasure does not worsen the security attributes of the assets, then B > 1.…”

Section: B Countermeasure Benefitmentioning

confidence: 99%

“…The modern era brought a technological revolution never seen before. Human beings rely every day more on the services offered by powerful and responsive machines that significantly increase the quality of their lives [1]. In this direction, ICT infrastructures play an essential role in developing this modern society.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the efficacy of the presented model is demonstrated by developing a prototype in a real use case scenario, using the attack graph modeling. Notably, the Common Vulnerabilities and Exposures (CVE) 1 and Common Attack Pattern Enumeration and Classification (CAPEC) 2 are leveraged as standard knowledge bases of vulnerabilities and attacks, respectively, to support their claims.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Bio-Inspired Reaction Against Cyberattacks: AIS-Powered Optimal Countermeasures Selection

2021

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Nowadays, Information and Communication Technology (ICT) infrastructures play a crucial role for human beings, providing essential services at astonishing speed. Nevertheless, such a centrality of those infrastructures attracts the interest of ill-motivated actors that target such infrastructures with cyberattacks that are every day more sophisticated and more disruptive. In this alarming context, selecting the optimal set of countermeasures represents a primary need to react against the appearance of potentially dangerous threats effectively. With the motivation to contribute to developing faster and more effective response capabilities against them, the paper at hand introduces a novel cybersecurity reaction methodology based on Artificial Immune Systems (AIS), for which the evolutionary computing paradigm has been adopted. By leveraging the outstanding properties of these bio-inspired techniques, the selected countermeasures to defeat cyberthreats through cloning and mutation phases in an effort to improve the quality of the solution from a quantitative perspective, being able to adjust the risk to which the assets of the protected system are exposed. Exhaustive experiments demonstrate the feasibility of the proposed approach, reducing the risk in a more than acceptable time lapse.

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Section: A Rationalementioning

confidence: 99%

Section: B Countermeasure Benefitmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Bio-Inspired Reaction Against Cyberattacks: AIS-Powered Optimal Countermeasures Selection

2021

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“…Today, most research on self protecting systems mainly proposed solutions for self response and mitigation, e.g. [7], [8]. Only a few work has focused on self-vulnerability assessment and remediation [9].…”

Section: A Literature Reviewmentioning

confidence: 99%

Normalization of Severity Rating for Automated Context-aware Vulnerability Risk Management

Ahmadi

Arlos

Casalicchio

2020

2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

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In the last three years, the unprecedented increase in discovered vulnerabilities ranked with critical and high severity raise new challenges in Vulnerability Risk Management (VRM). Indeed, identifying, analyzing and remediating this high rate of vulnerabilities is labour intensive, especially for enterprises dealing with complex computing infrastructures such as Infrastructure-as-a-Service providers. Hence there is a demand for new criteria to prioritize vulnerabilities remediation and new automated/autonomic approaches to VRM. In this paper, we address the above challenge proposing an Automated Context-aware Vulnerability Risk Management (AC-VRM) methodology that aims: to reduce the labour intensive tasks of security experts; to prioritize vulnerability remediation on the basis of the organization context rather than risk severity only. The proposed solution considers multiple vulnerabilities databases to have a great coverage on known vulnerabilities and to determine the vulnerability rank. After the description of the new VRM methodology, we focus on the problem of obtaining a single vulnerability score by normalization and fusion of ranks obtained from multiple vulnerabilities databases. Our solution is a parametric normalization that accounts for organization needs/specifications.

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A botnets control strategy based on variable forgetting rate of control commands

Wang

Elahi

et al. 2020

Concurrency and Computation

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Botnets take advantage of the vulnerabilities in the device-to-device (D2D) communication in the Internet of Things (IoT) systems. The infect devices may become part of the command and control mechanism of Botnets. These infected devices may forget control commands to remain undetected. State-of-the-art control models for botnets based on how devices are infected and patched in IoT systems while dealing with Botnets assume that the rate at which IoT devices forget the control commands (forgetting rate) is constant and known. These control models ignore the possible variability of the forgetting rate, which may enable bots to operate without being detected. This research fills this gap by proposing a modeling-based strategy that considers the changes in equipment states and repair speed when the forgetting rate is variable. In this regard, first, based on the state-of-the-art botnets control model, the effect of variation in the forgetting rate is analyzed. After that, an improved strategy is proposed for the botnets control model when the forgetting rate is unknown. Finally, the experimental evaluation of the proposed strategy is performed that proves the correctness of the proposed control strategy.

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Towards the autonomous provision of self-protection capabilities in 5G networks

Cited by 17 publications

References 26 publications

A Bio-Inspired Reaction Against Cyberattacks: AIS-Powered Optimal Countermeasures Selection

A Bio-Inspired Reaction Against Cyberattacks: AIS-Powered Optimal Countermeasures Selection

Normalization of Severity Rating for Automated Context-aware Vulnerability Risk Management

A botnets control strategy based on variable forgetting rate of control commands

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