Cloud Storage Forensics: Analysis of Data Remnants on SpiderOak, JustCloud, and pCloud
June 25, 2017 Β· Declared Dead Β· π Contemporary Digital Forensic Investigations of Cloud and Mobile Applications
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
SeyedHossein Mohtasebi, Ali Dehghantanha, Kim-Kwang Raymond Choo
arXiv ID
1706.08042
Category
cs.CR: Cryptography & Security
Citations
50
Venue
Contemporary Digital Forensic Investigations of Cloud and Mobile Applications
Last Checked
5 months ago
Abstract
STorage as a Service (STaaS) cloud platforms benefits such as getting access to data anywhere, anytime, on a wide range of devices made them very popular among businesses and individuals. As such forensics investigators are increasingly facing cases that involve investigation of STaaS platforms. Therefore, it is essential for cyber investigators to know how to collect, preserve, and analyse evidences of these platforms. In this paper, we describe investigation of three STaaS platforms namely SpiderOak, JustCloud, and pCloud on Windows 8.1 and iOS 8.1.1 devices. Moreover, possible changes on uploaded and downloaded files metadata on these platforms would be tracked and their forensics value would be investigated.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Cryptography & Security
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
The Limitations of Deep Learning in Adversarial Settings
R.I.P.
π»
Ghosted
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
R.I.P.
π»
Ghosted
Spectre Attacks: Exploiting Speculative Execution
R.I.P.
π»
Ghosted
How To Backdoor Federated Learning
R.I.P.
π»
Ghosted
Evasion Attacks against Machine Learning at Test Time
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted