지각된 유용성(Perceived Usefulness)의 영향분석

Intelligent cryptography approach for secure distributed big data storage in cloud computing

http://homepages.mcs.vuw.ac.nz/~kris/publications/JPDC-2014.pdf

Reputation systems

Cloud computing offers a new way of services and has become a popular service platform. Storing user data at a cloud data center greatly releases storage burden of user devices and brings access convenience. Due to distrust in cloud service providers, users generally store their crucial data in an encrypted form. But in many cases, the data need to be accessed by other entities for fulfilling an expected service, e.g., an eHealth service. How to control personal data access at cloud is a critical issue. Various application scenarios request flexible control on cloud data access based on data owner policies and application demands. Either data owners or some trusted third parties or both should flexibly participate in this control. However, existing work hasn't yet investigated an effective and flexible solution to satisfy this demand. On the other hand, trust plays an important role in data sharing. It helps overcoming uncertainty and avoiding potential risks. But literature still lacks a practical solution to control cloud data access based on trust and reputation. In this paper, we propose a scheme to control data access in cloud computing based on trust evaluated by the data owner and/or reputations generated by a number of reputation centers in a flexible manner by applying Attribue-Based Encryption and Proxy Re-Encryption. We integrate the concept of context-aware trust and reputation evaluation into a cryptographic system in order to support various control scenarios and strategies. The security and performance of our scheme are evaluated and justified through extensive analysis, security proof, comparison and implementation. The results show the efficiency, flexibility and effectiveness of our scheme for data access control in cloud computing.

Flexible Data Access Control Based on Trust and Reputation in Cloud Computing

The outstanding advances of mobile devices stimulate their wide usage. Since mobile devices are coupled with third-party applications, lots of security and privacy problems are induced. However, current mobile malware detection and analysis technologies are still imperfect, ineffective, and incomprehensive. Due to the specific characteristics of mobile devices such as limited resources, constant network connectivity, user activities and location sensing, and local communication capability, mobile malware detection faces new challenges, especially on dynamic runtime malware detection. Many intrusions or attacks could happen after a mobile app is installed or executed. The literature still expects practical and effective dynamic malware detection approaches. In this paper, we give a thorough survey on dynamic mobile malware detection. We first introduce the definition, evolution, classification, and security threats of mobile malware. Then, we summarize a number of criteria and performance evaluation measures of mobile malware detection. Furthermore, we compare, analyze, and comment on existing mobile malware detection methods proposed in recent years based on evaluation criteria and measures. Finally, we figure out open issues in this research field and motivate future research directions.

A survey on dynamic mobile malware detection

A practical reputation system for pervasive social chatting

Social network has extended its popularity from the Internet to mobile domain. Personal mobile devices can be self-organized and communicate with each other for instant social activities at any time and in any places to achieve pervasive social networking (PSN). In such a network, various content information flows. To which extent should mobile users trust it, whilst user privacy can also be preserved? Existing work has not yet seriously considered trust and reputation management, although trust plays an important role in PSN. In this paper, we propose PerContRep, a practical reputation system for pervasive content services that can assist trustworthy content selection and consumption in a pervasive manner. We develop a hybrid trust and reputation management model to evaluate node recommendation trust and content reputation in the context of frequent change of node pseudonyms. Simulations show the advantages of PerContRep in assisting user decisions and its effectiveness with regard to unfair rating attack, collaborative unfair rating attack, on-off attack and conflict behavior attack. A prototype system achieves positive user feedback on its usability and social acceptance.

PerContRep: a practical reputation system for pervasive content services

Analysis on the acceptance of Global Trust Management for unwanted traffic control based on game theory

The Internet has dramatically changed our daily life. But it is also bogged down by unwanted traffic, which is malicious, harmful or unexpected for its receivers. In order to control the unwanted traffic over the Internet, especially the mobile Internet, in this paper, we propose a generic unwanted traffic control (UTC) solution through trust management. It can control unwanted traffic from its source to destinations in a personalized manner according to trust evaluation at a Global Trust Operator, traffic and behavior analysis at hosts and traffic observation in the Internet. Thus, it can conduct UTC by integrating distributed and centralized functions and supporting both defensive and offensive approaches. Simulation based evaluation shows that the solution is effective with regard to accuracy and efficiency for botnet intrusion and DDoS intrusion via reflectors. It is also robust against a number of malicious system attacks, such as hide evidence attack, bad mouthing attack, on-off attack, malicious at...

A generic solution for unwanted traffic control through trust management

At the same time as the Internet provides a lot of social value, it is bogged down by unwanted traffic, which is malicious, harmful or unexpected for its receiver. This paper proposes an unwanted traffic control solution through hybrid trust management. It can control unwanted traffic from its source to destinations according to trust evaluation at a Global Trust Operator and traffic and behavior analysis at hosts. Thus, it can support unwanted traffic control in both a distributed and centralized manner and in both a defensive and offensive way. Simulation based evaluation shows that the solution is effective with regard to botnet intrusion, malicious attack of ISP and DDoS intrusion via reflectors.

Unwanted Traffic Control via Hybrid Trust Management

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