Biblio

Export results:
Author Title Type [ Year(Asc)]
Filters: Keyword is IoT-Forensics  [Clear All Filters]
A. Nieto, "Becoming JUDAS: Correlating Users and Devices during a Digital Investigation",
IEEE Transactions on Information Forensics & Security, vol. 15, IEEE, pp. 3325-3334, 17/04/2020. DOI (I.F.: 6.013)More..

Abstract

One of the biggest challenges in IoT-forensics is the analysis and correlation of heterogeneous digital evidence, to enable an effective understanding of complex scenarios. This paper defines a methodology for extracting unique objects (e.g., representing users or devices) from the files of a case, defining the context of the digital investigation and increasing the knowledge progressively, using additional files from the case (e.g. network captures). The solution includes external searches using open source intelligence (OSINT) sources when needed. In order to illustrate this approach, the proposed methodology is implemented in the JSON Users and Devices analysis (JUDAS) tool, which is able to generate the context from JSON files, complete it, and show the whole context using dynamic graphs. The approach is validated using the files in an IoT-Forensic digital investigation where an important set of potential digital evidence extracted from Amazon’s Alexa Cloud is analysed.

Impact Factor: 6.013
Journal Citation Reports® Science Edition (Thomson Reuters, 2019)

PDF icon JUDAS2020.pdf (9.25 MB)
A. Nieto, R. Rios, and J. Lopez, "IoT-Forensics meets Privacy: Towards Cooperative Digital Investigations",
Sensors, vol. 18, issue 2, no. 492, MDPI, 02/2018. DOI (I.F.: 3.031)More..

Abstract

IoT-Forensics is a novel paradigm for the acquisition of electronic evidence whose operation is conditioned by the peculiarities of the Internet of Things (IoT) context. As a branch of computer forensics, this discipline respects the most basic forensic principles of preservation, traceability, documentation, and authorization. The digital witness approach also promotes such principles in the context of the IoT while allowing personal devices to cooperate in digital investigations by voluntarily providing electronic evidence to the authorities. However, this solution is highly dependent on the willingness of citizens to collaborate and they may be reluctant to do so if the sensitive information within their personal devices is not sufficiently protected when shared with the investigators. In this paper, we provide the digital witness approach with a methodology that enables citizens to share their data with some privacy guarantees. We apply the PRoFIT methodology, originally defined for IoT-Forensics environments, to the digital witness approach in order to unleash its full potential. Finally, we show the feasibility of a PRoFIT-compliant digital witness with two use cases.

Impact Factor: 3.031
Journal Citation Reports® Science Edition (Thomson Reuters, 2018)

PDF icon nrlSensors2018.pdf (14.4 MB)
A. Nieto, R. Roman, and J. Lopez, "Digital Witness: Safeguarding Digital Evidence by using Secure Architectures in Personal Devices",
IEEE Network, IEEE Communications Society, pp. 12-19, 2016. DOI (I.F.: 7.230)More..

Abstract

Personal devices contain electronic evidence associated with the behaviour of their owners and other devices in their environment, which can help clarify the facts of a cyber-crime scene. These devices are usually analysed as containers of proof. However, it is possible to harness the boom of personal devices to define the concept of digital witnesses, where personal devices are able to actively acquire, store, and transmit digital evidence to an authorised entity, reliably and securely. This article introduces this novel concept, providing a preliminary analysis on the management of digital evidence and the technologies that can be used to implement it with security guarantees in IoT environments. Moreover, the basic building blocks of a digital witness are defined.

Impact Factor: 7.230
Journal Citation Reports® Science Edition (Thomson Reuters, 2016)

PDF icon ieeenet16-nrl.pdf (1002.02 KB)
Modify or remove your filters and try again.