Biblio
With the rapid increase in the use of mobile devices in people's daily lives, mobile data traffic is exploding in recent years. In the edge computing environment where edge servers are deployed around mobile users, caching popular data on edge servers can ensure mobile users' fast access to those data and reduce the data traffic between mobile users and the centralized cloud. Existing studies consider the data cache problem with a focus on the reduction of network delay and the improvement of mobile devices' energy efficiency. In this paper, we attack the data caching problem in the edge computing environment from the service providers' perspective, who would like to maximize their venues of caching their data. This problem is complicated because data caching produces benefits at a cost and there usually is a trade-off in-between. In this paper, we formulate the data caching problem as an integer programming problem, and maximizes the revenue of the service provider while satisfying a constraint for data access latency. Extensive experiments are conducted on a real-world dataset that contains the locations of edge servers and mobile users, and the results reveal that our approach significantly outperform the baseline approaches.
Due to the increasing concerns of securing private information, context-aware Internet of Things (IoT) applications are in dire need of supporting data privacy preservation for users. In the past years, game theory has been widely applied to design secure and privacy-preserving protocols for users to counter various attacks, and most of the existing work is based on a two-player game model, i.e., a user/defender-attacker game. In this paper, we consider a more practical scenario which involves three players: a user, an attacker, and a service provider, and such a complicated system renders any two-player model inapplicable. To capture the complex interactions between the service provider, the user, and the attacker, we propose a hierarchical two-layer three-player game framework. Finally, we carry out a comprehensive numerical study to validate our proposed game framework and theoretical analysis.
Subscriber Identity Module (SIM) is the backbone of modern mobile communication. SIM can be used to store a number of user sensitive information such as user contacts, SMS, banking information (some banking applications store user credentials on the SIM) etc. Unfortunately, the current SIM model has a major weakness. When the mobile device is lost, an adversary can simply steal a user's SIM and use it. He/she can then extract the user's sensitive information stored on the SIM. Moreover, The adversary can then pose as the user and communicate with the contacts stored on the SIM. This opens up the avenue to a large number of social engineering techniques. Additionally, if the user has provided his/her number as a recovery option for some accounts, the adversary can get access to them. The current methodology to deal with a stolen SIM is to contact your particular service provider and report a theft. The service provider then blocks the services on your SIM, but the adversary still has access to the data which is stored on the SIM. Therefore, a secure scheme is required to ensure that only legal users are able to access and utilize their SIM.
Recently, cloud computing has been spotlighted as a new paradigm of database management system. In this environment, databases are outsourced and deployed on a service provider in order to reduce cost for data storage and maintenance. However, the service provider might be untrusted so that the two issues of data security, including data confidentiality and query result integrity, become major concerns for users. Existing bucket-based data authentication methods have problem that the original spatial data distribution can be disclosed from data authentication index due to the unsophisticated data grouping strategies. In addition, the transmission overhead of verification object is high. In this paper, we propose a privacy-aware query authentication which guarantees data confidentiality and query result integrity for users. A periodic function-based data grouping scheme is designed to privately partition a spatial database into small groups for generating a signature of each group. The group signature is used to check the correctness and completeness of outsourced data when answering a range query to users. Through performance evaluation, it is shown that proposed method outperforms the existing method in terms of range query processing time up to 3 times.
Recently, cloud computing has been spotlighted as a new paradigm of database management system. In this environment, databases are outsourced and deployed on a service provider in order to reduce cost for data storage and maintenance. However, the service provider might be untrusted so that the two issues of data security, including data confidentiality and query result integrity, become major concerns for users. Existing bucket-based data authentication methods have problem that the original spatial data distribution can be disclosed from data authentication index due to the unsophisticated data grouping strategies. In addition, the transmission overhead of verification object is high. In this paper, we propose a privacy-aware query authentication which guarantees data confidentiality and query result integrity for users. A periodic function-based data grouping scheme is designed to privately partition a spatial database into small groups for generating a signature of each group. The group signature is used to check the correctness and completeness of outsourced data when answering a range query to users. Through performance evaluation, it is shown that proposed method outperforms the existing method in terms of range query processing time up to 3 times.
When a user accesses a resource, the accounting process at the server side does the job of keeping track of the resource usage so as to charge the user. In cloud computing, a user may use more than one service provider and need two independent service providers to work together. In this user-centric context, the user is the owner of the information and has the right to authorize to a third party application to access the protected resource on the user's behalf. Therefore, the user also needs to monitor the authorized resource usage he granted to third party applications. However, the existing accounting protocols were proposed to monitor the resource usage in terms of how the user uses the resource from the service provider. This paper proposed the user-centric accounting model called AccAuth which designs an accounting layer to an OAuth protocol. Then the prototype was implemented, and the proposed model was evaluated against the standard requirements. The result showed that AccAuth passed all the requirements.
Recently, cloud computing has been spotlighted as a new paradigm of database management system. In this environment, databases are outsourced and deployed on a service provider in order to reduce cost for data storage and maintenance. However, the service provider might be untrusted so that the two issues of data security, including data confidentiality and query result integrity, become major concerns for users. Existing bucket-based data authentication methods have problem that the original spatial data distribution can be disclosed from data authentication index due to the unsophisticated data grouping strategies. In addition, the transmission overhead of verification object is high. In this paper, we propose a privacy-aware query authentication which guarantees data confidentiality and query result integrity for users. A periodic function-based data grouping scheme is designed to privately partition a spatial database into small groups for generating a signature of each group. The group signature is used to check the correctness and completeness of outsourced data when answering a range query to users. Through performance evaluation, it is shown that proposed method outperforms the existing method in terms of range query processing time up to 3 times.
Anonymous communications networks, such as Tor, help to solve the real and important problem of enabling users to communicate privately over the Internet. However, in doing so, anonymous communications networks introduce an entirely new problem for the service providers - such as websites, IRC networks or mail servers - with which these users interact, in particular, since all anonymous users look alike, there is no way for the service providers to hold individual misbehaving anonymous users accountable for their actions. Recent research efforts have focused on using anonymous blacklisting systems (which are sometimes called anonymous revocation systems) to empower service providers with the ability to revoke access from abusive anonymous users. In contrast to revocable anonymity systems, which enable some trusted third party to deanonymize users, anonymous blacklisting systems provide users with a way to authenticate anonymously with a service provider, while enabling the service provider to revoke access from any users that misbehave, without revealing their identities. In this paper, we introduce the anonymous blacklisting problem and survey the literature on anonymous blacklisting systems, comparing and contrasting the architecture of various existing schemes, and discussing the tradeoffs inherent with each design. The literature on anonymous blacklisting systems lacks a unified set of definitions, each scheme operates under different trust assumptions and provides different security and privacy guarantees. Therefore, before we discuss the existing approaches in detail, we first propose a formal definition for anonymous blacklisting systems, and a set of security and privacy properties that these systems should possess. We also outline a set of new performance requirements that anonymous blacklisting systems should satisfy to maximize their potential for real-world adoption, and give formal definitions for several optional features already supported by some sche- - mes in the literature.