Efficient Keyword-aware Representative Travel Route Recommendation
With the popularity of social media (e.g., Facebook and Flicker), users can easily share their check-in records and photos during their trips. In view of the huge number of user historical mobility records in social media, we aim to discover travel experiences to facilitate trip planning. When planning a trip, users always have specific preferences regarding their trips. Instead of restricting users to limited query options such as locations, activities or time periods, we consider arbitrary text descriptions as keywords about personalized requirements. Moreover, a diverse and representative set of recommended travel routes is needed. Prior works have elaborated on mining and ranking existing routes from check-in data. To meet the need for automatic trip organization, we claim that more features of Places of Interest (POIs) should be extracted. Therefore, in this paper, we propose an efficient Keyword-aware Representative Travel Route framework that uses knowledge extraction from users’ historical mobility records and social interactions. Explicitly, we have designed a keyword extraction module to classify the POI-related tags, for effective matching with query keywords. We have further designed a route reconstruction algorithm to construct route candidates that fulfill the requirements. To provide befitting query results, we explore Representative Skyline concepts, that is, the Skyline routes which best describe the trade-offs among different POI features. To evaluate the effectiveness and efficiency of the proposed algorithms, we have conducted extensive experiments on real location-based social network datasets, and the experiment results show that our methods do indeed demonstrate good performance compared to state-of-the-art works.
Reference IEEE paper:
“Efficient Keyword-aware Representative Travel Route Recommendation”, IEEE Transactions on Knowledge and Data Engineering, 2017.
Unique ID -SBI1035
Domain – DATA MINING
Book your project Now. Checkout other projects here
A Lightweight Secure Data Sharing Scheme for Mobile Cloud Computing
With the popularity of cloud computing, mobile devices can store/retrieve personal data from anywhere at any time. Consequently, the data security problem in mobile cloud becomes more and more severe and prevents further development of mobile cloud. There are substantial studies that have been conducted to improve the cloud security. However, most of them are not applicable for mobile cloud since mobile devices only have limited computing resources and power. Solutions with low computational overhead are in great need for mobile cloud applications. In this paper, we propose a lightweight data sharing scheme (LDSS) for mobile cloud computing. It adopts CP-ABE, an access control technology used in normal cloud environment, but changes the structure of access control tree to make it suitable for mobile cloud environments. LDSS moves a large portion of the computational intensive access control tree transformation in CP-ABE from mobile devices to external proxy servers. Furthermore, to reduce the user revocation cost, it introduces attribute description fields to implement lazy-revocation, which is a thorny issue in program based CP-ABE systems. The experimental results show that LDSS can effectively reduce the overhead on the mobile device side when users are sharing data in mobile cloud environments.
Reference IEEE paper :
“A Lightweight Secure Data Sharing Scheme for Mobile Cloud Computing”, IEEE Transactions on Cloud Computing, 2017.
Unique ID -SBI1002
Domain – CLOUD COMPUTING
Book your project Now. Checkout other projects here
Cross tenant access control model for cloud computing. Sharing of resources on the cloud can be achieved on a large scale since it is cost effective and location independent. Despite the hype surrounding cloud computing, organizations are still reluctant to deploy their businesses in the cloud computing environment due to concerns in secure resource sharing. In this paper, we propose a cloud resource mediation service offered by cloud service providers, which plays the role of trusted third party among its different tenants. This paper formally specifies the resource sharing mechanism between two different tenants in the presence of our proposed cloud resource mediation service. The correctness of permission activation and delegation mechanism among different tenants using four distinct algorithms (Activation, Delegation, Forward Revocation and Backward Revocation) is also demonstrated using formal verification. The performance analysis suggest that sharing of resources can be performed securely and efficiently across different tenants of the cloud.
Cross tenant access control model for cloud computing
- Zhao et al. propose a cross-domain single sign on authentication protocol for cloud users, whose security was also proven mathematically. In the approach, the CSP is responsible for verifying the user’s identity and making access control decisions.
- As computing resources are being shared between tenants and used in an on-demand manner, both known and zeroday system security vulnerabilities could be exploited by the attackers (e.g. using side-channel and timing attacks).
- In existing, a fine grained data-level access control model (FDACM) designed to provide role-based and data-based access control for multi-tenant applications was presented. Relatively lightweight expressions were used to represent complex policy rules.
DISADVANTAGES OF EXISTING SYSTEM:
- Traditional access control models, such as role based access control, are generally unable to adequately deal with cross-tenant resource access requests.
- Specification level security is difficult to achieve at the user and provider ends.
- The security of the approach was not provided.
- We use model checking to exhaustively explore the system and verify the finite state concurrent systems. Specifically, we use High Level Petri Nets (HLPN) and Z language for the modeling and analysis of the CTAC model.
- We present a CTAC model for collaboration, and the CRMS to facilitate resource sharing amongst various tenants and their users.
- We also present four different algorithms in the CTAC model, namely: activation, delegation, forward revocation and backward revocation.
- We then provide a detailed presentation of modeling, analysis and automated verification of the CTAC model using the Bounded Model Checking technique with SMTLIB and Z3 solver, in order to demonstrate the correctness and security of the CTAC model.
ADVANTAGES OF PROPOSED SYSTEM:
- HLPN provides graphical and mathematical representations of the system, which facilitates the analysis of its reactions to a given input. Therefore, we are able to understand the links between different system entities and how information is processed.
- We then verify the model by translating the HLPN using bounded model checking. For this purpose, we use Satisfiability Modulo Theories Library (SMT-Lib) and solver. We remark that such formal verification has previously been used to evaluate security protocols
System : Pentium Dual Core.
Hard Disk : 120 GB.
Monitor : 15” LED
Input Devices : Keyboard, Mouse
Ram : 1 GB
Operating system : Windows 7.
Coding Language : JAVA/J2EE
Tool : Netbeans 7.2.1
Database : MYSQL
Book your project Now.
Checkout other projects here