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Future Internet
Special Issues
Security in Cloud Computing and Big Data
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Security in Cloud Computing and Big Data

A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (15 January 2016) | Viewed by 51615

Special Issue Editors

Prof. Dr. Eduardo Fernández-Medina Patón

E-Mail Website
Guest Editor
GSyA Research Group. University of Castilla-La Mancha, Paseo de la Universidad, 4-13071 Ciudad Real, Spain
Interests: security metrics; secure MDA; secure Datawarehouses; security requirements; security engineering; security in cloud computing and big data; secure information systems
Dr. David G. Rosado

E-Mail Website
Guest Editor
GSyA Research Group, University of Castilla–La Mancha, 13700 Ciudad Real, Spain
Interests: security patterns; security engineering; security in cloud computing and big data; secure information systems; security technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Although there are many benefits to adopting Cloud Computing (collaboration, agility, scalability, availability, ability cost reduction, efficient computing), there are also some significant barriers to adoption. One of the most significant barriers to adoption is security, followed by issues regarding compliance, privacy, and legal matters.
Big Data technologies describe a new generation of technologies and architectures, designed so organizations like yours can economically extract value from very large volumes of a wide variety of data by enabling high-velocity capture, discovery, and/or analysis. This new technology raises new risks due to more volume and variety of data. Issues related to data security and privacy are one of the main concern in today’s era of “big data.” It is necessary to know before of involving in big data, which are the most important security needs, requirements, and aspects to assure a high security level in our applications, transactions, data processing, and decision management.

Prof. Dr. Eduardo Fernández-Medina Patón
Dr. David G. Rosado
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. Future Internet 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

  • security, integrity and privacy for cloud computing
  • secure cloud architectures and services
  • secure cloud development
  • secure cloud migration
  • emerging technologies and trends in big data and cloud security
  • big data security and privacy
  • big data analytics for security applications
  • design, implementation, evaluation and services related to secure big data
  • big data in the cloud

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Published Papers (5 papers)

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2322 KiB  
Article
Main Issues in Big Data Security
by Julio Moreno, Manuel A. Serrano and Eduardo Fernández-Medina
Future Internet 2016, 8(3), 44; https://doi.org/10.3390/fi8030044 - 1 Sep 2016
Cited by 42 | Viewed by 17559
Abstract
Data is currently one of the most important assets for companies in every field. The continuous growth in the importance and volume of data has created a new problem: it cannot be handled by traditional analysis techniques. This problem was, therefore, solved through [...] Read more.
Data is currently one of the most important assets for companies in every field. The continuous growth in the importance and volume of data has created a new problem: it cannot be handled by traditional analysis techniques. This problem was, therefore, solved through the creation of a new paradigm: Big Data. However, Big Data originated new issues related not only to the volume or the variety of the data, but also to data security and privacy. In order to obtain a full perspective of the problem, we decided to carry out an investigation with the objective of highlighting the main issues regarding Big Data security, and also the solutions proposed by the scientific community to solve them. In this paper, we explain the results obtained after applying a systematic mapping study to security in the Big Data ecosystem. It is almost impossible to carry out detailed research into the entire topic of security, and the outcome of this research is, therefore, a big picture of the main problems related to security in a Big Data system, along with the principal solutions to them proposed by the research community. Full article
(This article belongs to the Special Issue Security in Cloud Computing and Big Data)
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925 KiB  
Article
Substring Position Search over Encrypted Cloud Data Supporting Efficient Multi-User Setup
by Mikhail Strizhov, Zachary Osman and Indrajit Ray
Future Internet 2016, 8(3), 28; https://doi.org/10.3390/fi8030028 - 4 Jul 2016
Cited by 11 | Viewed by 6108
Abstract
Existing Searchable Encryption (SE) solutions are able to handle simple Boolean search queries, such as single or multi-keyword queries, but cannot handle substring search queries over encrypted data that also involve identifying the position of the substring within the document. These types of [...] Read more.
Existing Searchable Encryption (SE) solutions are able to handle simple Boolean search queries, such as single or multi-keyword queries, but cannot handle substring search queries over encrypted data that also involve identifying the position of the substring within the document. These types of queries are relevant in areas such as searching DNA data. In this paper, we propose a tree-based Substring Position Searchable Symmetric Encryption (SSP-SSE) to overcome the existing gap. Our solution efficiently finds occurrences of a given substring over encrypted cloud data. Specifically, our construction uses the position heap tree data structure and achieves asymptotic efficiency comparable to that of an unencrypted position heap tree. Our encryption takes O ( k n ) time, and the resulting ciphertext is of size O ( k n ) , where k is a security parameter and n is the size of stored data. The search takes O ( m 2 + o c c ) time and three rounds of communication, where m is the length of the queried substring and o c c is the number of occurrences of the substring in the document collection. We prove that the proposed scheme is secure against chosen-query attacks that involve an adaptive adversary. Finally, we extend SSP-SSE to the multi-user setting where an arbitrary group of cloud users can submit substring queries to search the encrypted data. Full article
(This article belongs to the Special Issue Security in Cloud Computing and Big Data)
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1930 KiB  
Article
Supporting Privacy of Computations in Mobile Big Data Systems
by Sriram Nandha Premnath and Zygmunt J. Haas
Future Internet 2016, 8(2), 17; https://doi.org/10.3390/fi8020017 - 10 May 2016
Cited by 1 | Viewed by 6422
Abstract
Cloud computing systems enable clients to rent and share computing resources of third party platforms, and have gained widespread use in recent years. Numerous varieties of mobile, small-scale devices such as smartphones, red e-health devices, etc., across users, are connected to one [...] Read more.
Cloud computing systems enable clients to rent and share computing resources of third party platforms, and have gained widespread use in recent years. Numerous varieties of mobile, small-scale devices such as smartphones, red e-health devices, etc., across users, are connected to one another through the massive internetwork of vastly powerful servers on the cloud. While mobile devices store “private information” of users such as location, payment, health data, etc., they may also contribute “semi-public information” (which may include crowdsourced data such as transit, traffic, nearby points of interests, etc.) for data analytics. In such a scenario, a mobile device may seek to obtain the result of a computation, which may depend on its private inputs, crowdsourced data from other mobile devices, and/or any “public inputs” from other servers on the Internet. We demonstrate a new method of delegating real-world computations of resource-constrained mobile clients using an encrypted program known as the garbled circuit. Using the garbled version of a mobile client’s inputs, a server in the cloud executes the garbled circuit and returns the resulting garbled outputs. Our system assures privacy of the mobile client’s input data and output of the computation, and also enables the client to verify that the evaluator actually performed the computation. We analyze the complexity of our system. We measure the time taken to construct the garbled circuit as well as evaluate it for varying number of servers. Using real-world data, we evaluate our system for a practical, privacy preserving search application that locates the nearest point of interest for the mobile client to demonstrate feasibility. Full article
(This article belongs to the Special Issue Security in Cloud Computing and Big Data)
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4082 KiB  
Article
Modeling and Security in Cloud Ecosystems
by Eduardo B. Fernandez, Nobukazu Yoshioka, Hironori Washizaki and Madiha H. Syed
Future Internet 2016, 8(2), 13; https://doi.org/10.3390/fi8020013 - 20 Apr 2016
Cited by 26 | Viewed by 9692
Abstract
Clouds do not work in isolation but interact with other clouds and with a variety of systems either developed by the same provider or by external entities with the purpose to interact with them; forming then an ecosystem. A software ecosystem is a [...] Read more.
Clouds do not work in isolation but interact with other clouds and with a variety of systems either developed by the same provider or by external entities with the purpose to interact with them; forming then an ecosystem. A software ecosystem is a collection of software systems that have been developed to coexist and evolve together. The stakeholders of such a system need a variety of models to give them a perspective of the possibilities of the system, to evaluate specific quality attributes, and to extend the system. A powerful representation when building or using software ecosystems is the use of architectural models, which describe the structural aspects of such a system. These models have value for security and compliance, are useful to build new systems, can be used to define service contracts, find where quality factors can be monitored, and to plan further expansion. We have described a cloud ecosystem in the form of a pattern diagram where its components are patterns and reference architectures. A pattern is an encapsulated solution to a recurrent problem. We have recently expanded these models to cover fog systems and containers. Fog Computing is a highly-virtualized platform that provides compute, storage, and networking services between end devices and Cloud Computing Data Centers; a Software Container provides an execution environment for applications sharing a host operating system, binaries, and libraries with other containers. We intend to use this architecture to answer a variety of questions about the security of this system as well as a reference to design interacting combinations of heterogeneous components. We defined a metamodel to relate security concepts which is being expanded. Full article
(This article belongs to the Special Issue Security in Cloud Computing and Big Data)
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1585 KiB  
Article
A Framework for Security Transparency in Cloud Computing
by Umar Mukhtar Ismail, Shareeful Islam, Moussa Ouedraogo and Edgar Weippl
Future Internet 2016, 8(1), 5; https://doi.org/10.3390/fi8010005 - 17 Feb 2016
Cited by 18 | Viewed by 10714
Abstract
Individuals and corporate users are persistently considering cloud adoption due to its significant benefits compared to traditional computing environments. The data and applications in the cloud are stored in an environment that is separated, managed and maintained externally to the organisation. Therefore, it [...] Read more.
Individuals and corporate users are persistently considering cloud adoption due to its significant benefits compared to traditional computing environments. The data and applications in the cloud are stored in an environment that is separated, managed and maintained externally to the organisation. Therefore, it is essential for cloud providers to demonstrate and implement adequate security practices to protect the data and processes put under their stewardship. Security transparency in the cloud is likely to become the core theme that underpins the systematic disclosure of security designs and practices that enhance customer confidence in using cloud service and deployment models. In this paper, we present a framework that enables a detailed analysis of security transparency for cloud based systems. In particular, we consider security transparency from three different levels of abstraction, i.e., conceptual, organisation and technical levels, and identify the relevant concepts within these levels. This allows us to provide an elaboration of the essential concepts at the core of transparency and analyse the means for implementing them from a technical perspective. Finally, an example from a real world migration context is given to provide a solid discussion on the applicability of the proposed framework. Full article
(This article belongs to the Special Issue Security in Cloud Computing and Big Data)
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