云计算平台下恶意软件动态自适应自主防护算法设计研究

云计算平台较为复杂,当前恶意软件防护算法容易受到复杂环境的影响,导致误防护或防护效果不佳。为此,提出一种新的云计算平台下恶意软件动态自适应自主防护算法,引入时间衰减因子确定信任评价权重,依据云计算平台软件的多个属性对软件的直接信任值进行计算。利用用户评价相似度对推荐者的推荐权重进行计算,从而实现软件推荐信任云计算。通过直接信任云与推荐信任云获取综合信任云,比较综合信任云和不同标准信任云,求出相应信任综合评判结果。将信任值低于阈值的软件看作恶意软件,列入恶意软件列表中。令云计算平台中所有用户共同维护恶意软件列表,在恶意软件执行前将其删除,从而实现自主防护。实验结果表明,所提算法能有效防护恶意软件,且耗电量少。

Research on the design of dynamic adaptive autonomous protection algorithm for malware based on cloud computing platform

Cloud computing platform is more complex, the current malware protection algorithm is vulnerable to the impact of complex environment, resulting in poor protection or poor protection. Therefore, this platform malware dynamic adaptive autonomous protection of a new algorithm for cloud computing, introducing the time attenuation factor to determine the trust weights, direct trust multiple attributes according to cloud computing platform software for the software to calculate the value of. The user"s evaluation similarity is used to calculate the recommendation weight of the recommender. Through the direct trust cloud and the recommendation of the trust cloud to obtain a comprehensive trust cloud, more comprehensive trust cloud and different standards of trust cloud, find out the results of the comprehensive evaluation of the corresponding trust. The trust value below the threshold of the software as a malicious software, included in the list of malicious software. So that all users in the cloud computing platform to maintain a list of malicious software, before the malicious software to delete it, so as to achieve independent protection. The experimental results show that the proposed algorithm can effectively protect the malicious software, and less power consumption.