Real-Time Multi Fractal Trust Evaluation Model for Efficient Intrusion Detection in Cloud

Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks.To address such threats towards cloud services,numerous techniques exist that mitigate the service threats according to different metrics.The rule-based approaches are unsuitable for new threats,whereas trust-based systems estimate trust value based on behavior,flow,and other features.However,the methods suffer from mitigating intrusion attacks at a higher rate.This article presents a novel Multi Fractal Trust Evaluation Model(MFTEM)to overcome these deficiencies.The method involves analyzing service growth,network growth,and quality of service growth.The process estimates the user’s trust in various ways and the support of the user in achieving higher service performance by calculating Trusted Service Support(TSS).Also,the user’s trust in supporting network stream by computing Trusted Network Support(TNS).Similarly,the user’s trust in achieving higher throughput is analyzed by computing Trusted QoS Support(TQS).Using all these measures,the method adds the Trust User Score(TUS)value to decide on the clearance of user requests.The proposed MFTEM model improves intrusion detection accuracy with higher performance.

Grid Services Trusted Authentication Algorithm Based on Image Trusted Root in Scale Space

A new authentication algorithm for grid identity trusted computing unlimited by hardware is presented;the trusted root is made as an image data.The grid entity is trusted in the soft platform when its feature of image root is entirely matched with that from the other entities＇ feature database in a scale space process.To recognize and detect the stable image root feature,the non-homogeneous linear expandable scale space is proposed.Focusing on relations between the scale parameter of the inhomogeneous Gaussian function terms and the space evolution of thermal diffusion homogeneous equations,three space evolution operators are constructed to exact and mark the feature from image root.Analysis and verification are carried on the new scale space,operators and the core of making decisions for grid entities certifications.

BCSE:Blockchain-Based Trusted Service Evaluation Model over Big Data

The blockchain,with its key characteristics of decentralization,persistence,anonymity,and auditability,has become a solution to overcome the overdependence and lack of trust for a traditional public key infrastructure on third-party institutions.Because of these characteristics,the blockchain is suitable for solving certain open problems in the service-oriented social network,where the unreliability of submitted reviews of service vendors can cause serious security problems.To solve the unreliability problems of submitted reviews,this paper first proposes a blockchain-based identity authentication scheme and a new trusted service evaluation model by introducing the scheme into a service evaluation model.The new trusted service evaluation model consists of the blockchain-based identity authentication scheme,evaluation submission module,and evaluation publicity module.In the proposed evaluation model,only users who have successfully been authenticated can submit reviews to service vendors.The registration and authentication records of users’identity and the reviews for service vendors are all stored in the blockchain network.The security analysis shows that this model can ensure the credibility of users’reviews for service vendors,and other users can obtain credible reviews of service vendors via the review publicity module.The experimental results also show that the proposed model has a lower review submission delay than other models.