From data to disruption

Duijn, Paul; Sloot, Peter M. A.

doi:10.1016/j.diin.2015.09.005

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…Miller et al (2014) proposed a cloud-based distributed processing platform called Forensicloud in an attempt to address the increasing volume and diversity of data in forensic examinations. Furthermore, Duijn & Sloot (2015) explore the use of big data and analytics to determine how organised crime groups operate and adapt over time. Analysts may be able to uncover patterns that are hidden or not obvious by analysing data from a diverse set of sources.…”

Section: Related Workmentioning

confidence: 99%

A Federated Distributed Digital Forensic Readiness Model for the Cloud

Koen,

Venter

2024

iccws

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Digital forensics in modern, cloud-based, microservice-based applications are complicated by multiple layers of abstraction, thereby making it difficult to accurately capture and correlate events that occur across these layers due to filtering caused by abstraction. The complexities linked to each layer of abstraction are primarily invisible to subsequent layers. Similarly, software services are often composed of one or more services provided by various service providers across the globe. Investigators are often faced with situations where breaches span over multiple service provider boundaries where not all digital forensic readiness evidence artefacts are captured by the service provider's forensic readiness processes. Instead, digital evidence artefacts are scattered across multiple service provider domains. This paper presents a novel, federated distributed digital forensic readiness model suitable for use in software-as-service, platform-as-service and infrastructure-as-service provider scenarios. The proposed model enables a service provider to capture and inspect forensic readiness artefacts in environments with various layers of abstraction. More importantly, the model also offers a way to share and access forensic readiness artefacts in a forensically sound manner to ultimately ensure that investigators can obtain a clear view of digital forensic events as they occur between amalgamated services provided by one or more separate service providers.

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Section: Related Workmentioning

confidence: 99%

A Federated Distributed Digital Forensic Readiness Model for the Cloud

Koen,

Venter

2024

iccws

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“…Intelligence data for computational models vary on scope and accuracy. 57 The scope of the data can be disaggregated based on resolution, agents, and strategy and tactics. 58 First, the resolution of the data determines the amount of information available about the conflict events at a specific scale.…”

Section: Implementation and Robustness Of Computational Modelsmentioning

confidence: 99%

Promises and pitfalls of computational modelling for insurgency conflicts

Zwet

Barros

Engers

et al. 2022

Journal of Defense Modeling & Simulation

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Insurgency conflicts pose significant challenges to societies globally. The increase of insurgency conflicts creates a need to understand how insurgencies arise, and to identify societal drivers of insurgencies or effective strategies to counter them. In this paper, we analyze the contributions of computational modeling methods for the analysis of insurgent conflicts. We formalize a specific literature-based analysis framework using the identified key factors and drivers, which enables the evaluation of specific models in this domain. Through a systematic literature search, we identify 64 computational models to apply our framework. We highlight the development and contributions of various methodologies through an in-depth analysis of 13 high-quality models. The evaluation of these computational models revealed promising directions and future topics to design specific simulation models for all identified factors. In addition, our analysis revealed specific pitfalls concerning validity issues for each of the modeling methods.

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“…Las redes del narcotráfico han sido exploradas con distintos alcances, en buena medida por lo complicado de tener datos confiables y las limitantes inherentes a los mismos. Aunque internacionalmente ya hay varios trabajos de investigación sobre estas redes (Agrestre et al, 2016;Duijn y Sloot, 2015;Bright y Delaney, 2013), donde se muestra la conveniencia de analizar estas redes desde una perspectiva más matemática. En el caso de México, la información es más limitada pero ya hay algunos primeros resultados (Espinal-Enríquez y Larralde, 2015;Dell, 2015).…”

Section: Redes: Notas Históricasunclassified

Redes de narcotráfico en México: ¿qué información nos pueden dar las matemáticas?

De la Peña

2019

TSUNAM

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El uso de redes para modelar algunos fenómenos, tales como el narcotráfico, desde el punto devista matemático, se ha extendido. Se han desarrollado investigaciones que han analizado este tipo de redes en distintas partes del mundo, incluyendo el caso mexicano. Es posible entender la operación de la economía del narcotráfico estudiando la estructura y la evolución de las redes sociales que apoyan sus actividades. Consideramos en detalle un modelo colombiano aplicado a la realidad mexicana.

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From data to disruption

Cited by 10 publications

References 20 publications

A Federated Distributed Digital Forensic Readiness Model for the Cloud

A Federated Distributed Digital Forensic Readiness Model for the Cloud

Promises and pitfalls of computational modelling for insurgency conflicts

Redes de narcotráfico en México: ¿qué información nos pueden dar las matemáticas?

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