Bio-Inspired Formal Model for Space/Time Virtual Machine Randomization and Diversification

Ahmed, Noor; Bhargava, Bharat

doi:10.1109/tcc.2020.2969353

Cited by 9 publications

(5 citation statements)

References 24 publications

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“…based on l = 100 simulations per defense. 2 In each plot, the upper and lower boxes depict the top and bottom quartiles, representing the 25% of values above and below the median. The horizontal line that separates top and bottom quartile along the notch, is the median.…”

Section: Resultsmentioning

confidence: 99%

“…Yet, only looking at rmax does not capture cases where a defense cannot prevent an attack, but slows it down. Many proposed MTD techniques do not claim to fully prevent attacks, but making them more costly in terms of required effort and time [2,3,5]. This is what ravg j is for.…”

Section: Metricsmentioning

confidence: 99%

“…In existing MTD literature, a lot of work focuses on developing a theoretical foundation to analyzing MTD techniques, with many approaches based on game theory [1,2,27,36]. Yet, these mostly intend to optimize attack and defense strategies or find equilibria in the presence of actors of certain capability.…”

Section: Introductionmentioning

confidence: 99%

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Automated benchmark network diversification for realistic attack simulation with application to moving target defense

Bajic

Becker²

2021

Int. J. Inf. Secur.

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With numbers of exploitable vulnerabilities and attacks on networks constantly increasing, it is important to employ defensive techniques to protect one’s systems. A wide range of defenses are available and new paradigms such as Moving Target Defense (MTD) rise in popularity. But to make informed decisions on which defenses to implement, it is necessary to evaluate their effectiveness first. In many cases, the full impact these techniques have on security is not well understood yet. In this paper we propose network defense evaluation based on detailed attack simulation. Using a flexible modeling language, networks, attacks, and defenses are described in high detail, yielding a fine-grained scenario definition. Based on this, an automated instantiator generates a wide range of realistic benchmark networks. These serve to perform simulations, allowing to evaluate the security impact of different defenses, both quantitatively and qualitatively. A case study based on a mid-sized corporate network scenario and different Moving Target Defenses illustrates the usefulness of this approach. Results show that virtual machine migration, a frequently suggested MTD technique, more often degrades than improves security. Hence, we argue that evaluation based on realistic attack simulation is a qualified approach to examine and verify claims of newly proposed defense techniques.

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Section: Resultsmentioning

confidence: 99%

Section: Metricsmentioning

confidence: 99%

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Automated benchmark network diversification for realistic attack simulation with application to moving target defense

Bajic

Becker²

2021

Int. J. Inf. Secur.

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show abstract

“…Pre-prepare, prepare, and commit are the steps in this process; client requests can be atomically broadcast to replicas. Replicas are responsible for completing all requests in the order specified by the primary and returning the results to clients [9]. F+1 answers from distinct duplicates with the same effect and time stamp are waited for by the client.…”

Section: A the Quorum's Replicamentioning

confidence: 99%

Dynamic Protocol Blockchain for Practical Byzantine Fault Tolerance Consensus

Sarfraz,

Ye,

Zhao

et al. 2023

International Journal of Scientific Advances

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This work details the byzantine fault-tolerant protocols that dynamically allow replicas to join and exit. Byzantine fault-tolerant (BFT) protocols and the blockchain now play an essential role in achieving consensus. There are numerous drawbacks to PBFT, despite its multiple positives. The first thing to note is that it runs in an environment completely isolated from the rest of the world. The entire system must be shut down before any nodes can be added or removed. Second, it ensures liveness and safety if no more than (n-1)/3 out of total n replicas, PBFT takes no action to cope with ineffective or malicious counterparts. This is bad for the system and will lead to its eventual failure. These flaws have far-reaching consequences in real life. The Randomization PBFT is an alternative way of dealing with these issues. In recent decades, as computer technology has advanced, so has our reliance on the products, services, and capabilities that computers provide.

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“…AIOps aims to improve and automate all tasks of the software operation phase by employing Artificial Intelligence techniques. As we have analyzed throughout this study, it is clear that the self-learning capabilities of bio-inspired computation techniques have a lot to say in this research direction, given that they are widely used in the development of key tasks of the operationalization process, such as optimization tasks [219] and resource planning [220]. Furthermore, the versatility of bio-inspired algorithms can solve complex problems for highly configurable systems [221], as is the case of the Big Data technology stack specialized in analysis and deployment in Cloud Computing infrastructure.…”

Section: Towards a Bio-inspired Operationalization Of Big Data Pipelinesmentioning

confidence: 99%

Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions

Torre-Bastida

Díaz-de-Arcaya

Osaba

et al. 2021

Neural Comput & Applic

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This overview gravitates on research achievements that have recently emerged from the confluence between Big Data technologies and bio-inspired computation. A manifold of reasons can be identified for the profitable synergy between these two paradigms, all rooted on the adaptability, intelligence and robustness that biologically inspired principles can provide to technologies aimed to manage, retrieve, fuse and process Big Data efficiently. We delve into this research field by first analyzing in depth the existing literature, with a focus on advances reported in the last few years. This prior literature analysis is complemented by an identification of the new trends and open challenges in Big Data that remain unsolved to date, and that can be effectively addressed by bio-inspired algorithms. As a second contribution, this work elaborates on how bio-inspired algorithms need to be adapted for their use in a Big Data context, in which data fusion becomes crucial as a previous step to allow processing and mining several and potentially heterogeneous data sources. This analysis allows exploring and comparing the scope and efficiency of existing approaches across different problems and domains, with the purpose of identifying new potential applications and research niches. Finally, this survey highlights open issues that remain unsolved to date in this research avenue, alongside a prescription of recommendations for future research.

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Bio-Inspired Formal Model for Space/Time Virtual Machine Randomization and Diversification

Cited by 9 publications

References 24 publications

Automated benchmark network diversification for realistic attack simulation with application to moving target defense

Automated benchmark network diversification for realistic attack simulation with application to moving target defense

Dynamic Protocol Blockchain for Practical Byzantine Fault Tolerance Consensus

Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions

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