Security and privacy of Fog

Cloud Computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. By data outsourcing, users can be relieved from the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the possibly large size of outsourced data makes the data integrity protection in Cloud Computing a very challenging and potentially formidable task, especially for users with constrained computing resources and capabilities. Thus, enabling public auditability for cloud data storage security is of critical importance so that users can resort to an external audit party to check the integrity of outsourced data when needed. To securely introduce an effective third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should bring in no new vulnerabilities towards user data privacy. In this paper, we utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis shows the proposed schemes are provably secure and highly efficient. Read More ›

While the general definition of the Internet of Things (IoT) is almost mature, roughly defining it as an information network connecting virtual and physical objects, there is a consistent lack of consensus around technical and regulatory solutions. There is no doubt, though, that the new paradigm will bring forward a completely new host of issues because of its deep impact on all aspects of human life. In this work, the authors outline the current technological and technical trends and their impacts on the security, privacy, and governance. The work is split into short- and long-term analysis where the former is focused on already or soon available technology, while the latter is based on vision concepts. Also, an overview of the vision of the European Commission on this topic will be provided. Read More ›

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Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. We propose a different approach for securing data in the cloud using offensive decoy technology. We monitor data access in the cloud and detect abnormal data access patterns. When unauthorized access is suspected and then verified using challenge questions, we launch a disinformation attack by returning large amounts of decoy information to the attacker. This protects against the misuse of the user's real data. Experiments conducted in a local file setting provide evidence that this approach may provide unprecedented levels of user data security in a Cloud environment. Read More ›

This paper considers current paradigms in computing and outlines the most important aspects concerning their reliability. The Fog computing paradigm as a non-trivial extension of the Cloud is considered and the reliability of the networks of smart devices are discussed. Combining the reliability requirements of grid and cloud paradigms with the reliability requirements of networks of sensor and actuators it follows that designing a reliable Fog computing platform is feasible. Read More ›

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The localization abilities of smartphones have provided a huge boost to the popularity of geosocial applications, which facilitate social interaction between users geographically close to each other. However, today’s geosocial applications raise privacy concerns due to application providers storing large amounts of information about users (e.g., profile information) and locations (e.g., users present at a location). We propose Zerosquare, a privacy-friendly location hub that encourages the development of privacy-preserving geosocial applications. Our primary goal is to store information such that no entity can link a user’s identity to her location. Other goals include decoupling storing data from manipulating data for social networking purposes, designing an architecture flexible enough to support a wide range of use cases, and limiting client-side computation. Zerosquare consists of two separate server components for storing information about users and about locations, respectively, and optional cloud components for supporting applications. We describe the design of the API exposed by the server components and demonstrate how it can be used to build several sample geosocial applications. We provide a proof-of-concept implementation using Python for the server components and the Android platform for the mobile devices and build several realworld geosocial applications on top of Zerosquare. Finally, we present experimental results that demonstrate the practicality of Zerosquare. Read More ›