The Security and Digital Forensics of Cloud Computing

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 10911

Special Issue Editors

University of Southampton, Southampton SO17 1BJ, United Kingdom
Interests: security; big data; knowledge management; cloud computing; games
Special Issues, Collections and Topics in MDPI journals
University of Southampton, Southampton SO17 1BJ, United Kingdom
Interests: parallel computing; digital forensics; cloud forensics; cloud security; Internet of Things (IoT) forensics; IoT security, blockchain and big data
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cloud computing is one of the fastest growing technologies in the field of computing. It is becoming more and more prevalent. Cloud computing has radically changed the way in which information technologies can be delivered. Although cloud computing has brought countless benefits to its consumers, these benefits can be misused for malicious purposes.

While the literature in cloud computing in general is not scarce, a number of related topics are still rich areas for research, some of which are cloud security and forensics. Many of the challenges in the field of cloud security and forensics need further investigation. This special issue is aimed to contribute to this research on topics related to cloud security and forensics. Topics of interest for submission include, but are not limited to:

Cloud Security

  • Cloud security readiness
  • Security-as-a-Service
  • Controlling access for cloud services
  • Trust as a Service
  • Cloud Governance
  • Cloud Security monitoring
  • Regulatory compliance
  • Security and Risks Management
  • Security challenges in cloud service models
  • Case studies related to cloud security
  • Current and future trends in cloud security

Cloud Forensics

  • Forensics-as-a-Service
  • Cloud application forensics
  • Cloud Forensics readiness
  • Digital evidence search and seizure in the cloud
  • Cloud forensics analysis
  • Incident handling in cloud computing
  • Investigative methodologies
  • Tools and practices in cloud forensics
  • Challenges of cloud forensics
  • Cybercrime investigation in cloud computing
  • Legal aspect of cloud investigations
  • Case studies related to cloud forensics
  • Current and future trends in cloud forensics

Dr. Gary Wills
Dr. Ahmed Alenezi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Digital Forensics
  • Digital Investigations
  • Cloud Computing
  • Cloud Forensics
  • Cloud Security

Published Papers (3 papers)

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Research

13 pages, 1402 KiB  
Article
Game Analysis of Access Control Based on User Behavior Trust
by Yan Wang, Liqin Tian and Zhenguo Chen
Information 2019, 10(4), 132; https://doi.org/10.3390/info10040132 - 09 Apr 2019
Cited by 10 | Viewed by 3659
Abstract
Due to the dynamics and uncertainty of the current network environment, access control is one of the most important factors in guaranteeing network information security. How to construct a scientific and accurate access control model is a current research focus. In actual access [...] Read more.
Due to the dynamics and uncertainty of the current network environment, access control is one of the most important factors in guaranteeing network information security. How to construct a scientific and accurate access control model is a current research focus. In actual access control mechanisms, users with high trust values bring better benefits, but the losses will also be greater once cheating access is adopted. A general access control game model that can reflect both trust and risk is established in this paper. First, we construct an access control game model with user behavior trust between the user and the service provider, in which the benefits and losses are quantified by using adaptive regulatory factors and the user’s trust level, which enhances the rationality of the policy making. Meanwhile, we present two kinds of solutions for the prisoner’s dilemma in the traditional access control game model without user behavior trust. Then, due to the vulnerability of trust, the user’s trust value is updated according to the interaction situation in the previous stage, which ensures that the updating of the user’s trust value can satisfy the “slow rising-fast falling” principle. Theoretical analysis and the simulation experiment both show that this model has a better performance than a traditional game model and can guarantee scientific decision-making in the access control mechanism. Full article
(This article belongs to the Special Issue The Security and Digital Forensics of Cloud Computing)
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20 pages, 10174 KiB  
Article
An Efficient Robust Multiple Watermarking Algorithm for Vector Geographic Data
by Yingying Wang, Chengsong Yang, Changqing Zhu and Kaimeng Ding
Information 2018, 9(12), 296; https://doi.org/10.3390/info9120296 - 24 Nov 2018
Cited by 6 | Viewed by 2700
Abstract
Vector geographic data play an important role in location information services. Digital watermarking has been widely used in protecting vector geographic data from being easily duplicated by digital forensics. Because the production and application of vector geographic data refer to many units and [...] Read more.
Vector geographic data play an important role in location information services. Digital watermarking has been widely used in protecting vector geographic data from being easily duplicated by digital forensics. Because the production and application of vector geographic data refer to many units and departments, the demand for multiple watermarking technology is increasing. However, multiple watermarking algorithm for vector geographic data draw less attention, and there are many urgent problems to be solved. Therefore, an efficient robust multiple watermark algorithm for vector geographic data is proposed in this paper. The coordinates in vector geographic data are first randomly divided into non-repetitive sets. The multiple watermarks are then embedded into the different sets. In watermark detection correlation, the Lindeberg theory is used to build a detection model and to confirm the detection threshold. Finally, experiments are made in order to demonstrate the detection algorithm, and to test its robustness against common attacks, especially against cropping attacks. The experimental results show that the proposed algorithm is robust against the deletion of vertices, addition of vertices, compression, and cropping attacks. Moreover, the proposed detection algorithm is compatible with single watermarking detection algorithms, and it has good performance in terms of detection efficiency. Full article
(This article belongs to the Special Issue The Security and Digital Forensics of Cloud Computing)
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17 pages, 4639 KiB  
Article
Perceptual Hashing Based Forensics Scheme for the Integrity Authentication of High Resolution Remote Sensing Image
by Kaimeng Ding, Fan Meng, Yueming Liu, Nan Xu and Wenjun Chen
Information 2018, 9(9), 229; https://doi.org/10.3390/info9090229 - 07 Sep 2018
Cited by 10 | Viewed by 3935
Abstract
High resolution remote sensing (HRRS) images are widely used in many sensitive fields, and their security should be protected thoroughly. Integrity authentication is one of their major security problems, while the traditional techniques cannot fully meet the requirements. In this paper, a perceptual [...] Read more.
High resolution remote sensing (HRRS) images are widely used in many sensitive fields, and their security should be protected thoroughly. Integrity authentication is one of their major security problems, while the traditional techniques cannot fully meet the requirements. In this paper, a perceptual hashing based forensics scheme is proposed for the integrity authentication of a HRRS image. The proposed scheme firstly partitions the HRRS image into grids and adaptively pretreats the grid cells according to the entropy. Secondly, the multi-scale edge features of the grid cells are extracted by the edge chains based on the adaptive strategy. Thirdly, principal component analysis (PCA) is applied on the extracted edge feature to get robust feature, which is then normalized and encrypted with secret key set by the user to receive the perceptual hash sequence. The integrity authentication procedure is achieved via the comparison between the recomputed perceptual hash sequence and the original one. Experimental results have shown that the proposed scheme has good robustness to normal content-preserving manipulations, has good sensitivity to detect local subtle and illegal tampering of the HRRS image, and has the ability to locate the tampering area. Full article
(This article belongs to the Special Issue The Security and Digital Forensics of Cloud Computing)
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