Meta-Review of Recent and Landmark Honeypot Research and Surveys

Ikuomenisan, Gbenga; Morgan, Yasser

doi:10.4236/jis.2022.134011

Cited by 4 publications

(4 citation statements)

References 32 publications

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“…Against this background, one notable trend, or lack thereof, noted previously by Zakaria and Kiah [15] was the lack of innovation stemming from introducing machine learning techniques and other automation methodologies into honeypots and honeynets. While exploring research trends in honeypot and honeynet development, Ikuomenisan and Morgan [3] found the same to be true.…”

Section: Honeypots and Honeynetsmentioning

confidence: 88%

“…While early honeypots and honeynets consisted of physical computing systems and networks [17], modern deception implementations are virtualized or containerized and cloud-capable [4]. Additionally, honeypot inspired deceptive systems have evolved in lockstep with emerging technologies such as software-defined networking, tokenized services, or as-a-service models [18,4,3].…”

Section: Honeypots and Honeynetsmentioning

confidence: 99%

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A green scheduling algorithm for cloud-based honeynets

Pittman¹,

Alaee²

2023

Front. Sustain.

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Modern businesses leverage cloud architecture to achieve agile and cost-effective technology services. Doing so comes at the expense of the environment though cloud technologies consume large quantities of energy. Cloud energy consumption is concerning in light of global climate trends and dwindling fossil fuel reserves. Consequently, increasing attention is given to sustainable and green cloud computing, which seeks to optimize compute-resource allocation and usage of virtualized systems and services. At the same time, progress toward sustainable and green cloud technology is impeded because as more enterprises deploy services into cloud architecture, cybersecurity threats follow. Unfortunately, cybersecurity technologies are optimized for maximum service overwatch without regard for compute resources and energy. This negates the energy reduction achieved in recent sustainable technology advancements. In this work, a generalized cybersecurity honeynet scheduling algorithm is proposed, in which power, CPU, and network overhead are operationalized to increase sustainability while balancing defensive mechanisms. The work describes both the mathematical foundation for the algorithm and a pseudocode proof of concept.

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Section: Honeypots and Honeynetsmentioning

confidence: 88%

Section: Honeypots and Honeynetsmentioning

confidence: 99%

A green scheduling algorithm for cloud-based honeynets

Pittman¹,

Alaee²

2023

Front. Sustain.

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“…To the best of our knowledge, we have not found the systematic survey and/or review articles evaluating visualization metrics, methods, and practices relating to attacks and intrusion detection in Honeypot cybersecurity research. Most re-G. Ikuomenisan, Y. Morgan DOI: 10.4236/jis.2022.134012 212 Journal of Information Security lated survey and/or review articles in the field of Honeypot did not follow systematic reviewing and reporting methods [10]. Most related literature surveys,…”

Section: Introductionmentioning

confidence: 99%

“…particularly in fields such as information visualization [2] [11], network anomaly detection [12], data preprocessing, and dimensionality reduction [13] [14] have not presented findings on how visualization methods are used in relation to Honeypot data analysis. Finally, there have been few Honeypot research contributions in the areas of Honeypot data analysis and visualization [10] and this paper hopes to fill this gap.…”

Section: Introductionmentioning

confidence: 99%

Systematic Review of Graphical Visual Methods in Honeypot Attack Data Analysis

Ikuomenisan¹,

Morgan²

2022

JIS

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Mitigating increasing cyberattack incidents may require strategies such as reinforcing organizations' networks with Honeypots and effectively analyzing attack traffic for detection of zero-day attacks and vulnerabilities. To effectively detect and mitigate cyberattacks, both computerized and visual analyses are typically required. However, most security analysts are not adequately trained in visualization principles and/or methods, which is required for effective visual perception of useful attack information hidden in attack data. Additionally, Honeypot has proven useful in cyberattack research, but no studies have comprehensively investigated visualization practices in the field. In this paper, we reviewed visualization practices and methods commonly used in the discovery and communication of attack patterns based on Honeypot network traffic data. Using the PRISMA methodology, we identified and screened 218 papers and evaluated only 37 papers having a high impact. Most Honeypot papers conducted summary statistics of Honeypot data based on static data metrics such as IP address, port, and packet size. They visually analyzed Honeypot attack data using simple graphical methods (such as line, bar, and pie charts) that tend to hide useful attack information. Furthermore, only a few papers conducted extended attack analysis, and commonly visualized attack data using scatter and linear plots. Papers rarely included simple yet sophisticated graphical methods, such as box plots and histograms, which allow for critical evaluation of analysis results. While a significant number of automated visualization tools have incorporated visualization standards by default, the construction of effective and expressive graphical methods for easy pattern discovery and explainable insights still requires applied knowledge and skill of visualization principles and tools, and occasionally, an interdisciplinary collaboration with peers. We, therefore, suggest the need, going forward, for non-classical graphical methods for visualizing attack patterns and communicating analysis results. We also recommend training investigators in How to cite this paper: Ikuomenisan, G.

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