DocumentCode :
651717
Title :
Internet of Things Forensics: Challenges and approaches
Author :
Oriwoh, Edewede ; Jazani, D. ; Epiphaniou, G. ; Sant, Paul
Author_Institution :
Dept. of Comput. Sci. & Technol., Univ. of Bedfordshire, Luton, UK
fYear :
2013
fDate :
20-23 Oct. 2013
Firstpage :
608
Lastpage :
615
Abstract :
The scope of this paper is two-fold: firstly it proposes the application of a 1-2-3 Zones approach to Internet of Things (IoT)-related Digital Forensics (DF) investigations. Secondly, it introduces a Next-Best-Thing Triage (NBT) Model for use in conjunction with the 1-2-3 Zones approach where necessary and vice versa. These two `approaches´ are essential for the DF process from an IoT perspective: the atypical nature of IoT sources of evidence (i.e. Objects of Forensic Interest - OOFI), the pervasiveness of the IoT environment and its other unique attributes - and the combination of these attributes - dictate the necessity for a systematic DF approach to incidents. The two approaches proposed are designed to serve as a beacon to incident responders, increasing the efficiency and effectiveness of their IoT-related investigations by maximizing the use of the available time and ensuring relevant evidence identification and acquisition. The approaches can also be applied in conjunction with existing, recognised DF models, methodologies and frameworks.
Keywords :
Internet of Things; digital forensics; 1-2-3 Zones approach; Internet of things forensics; IoT; NBT model; OOFI; digital forensics; evidence acquisition; evidence identification; next-best-thing triage model; object of forensic interest; systematic DF approach; Digital forensics; Educational institutions; Hospitals; Internet; Mobile handsets; Sensors; Internet of Things; digital forensics; model; security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Collaborative Computing: Networking, Applications and Worksharing (Collaboratecom), 2013 9th International Conference Conference on
Conference_Location :
Austin, TX
Type :
conf
Filename :
6680032
Link To Document :
بازگشت