针对现有的信任模型对节点行为改变的动态适应能力和对反馈信息的有效聚合能力支持不足,提出一个基于时间帧的动态信任模型DyTrust,使用时间帧标示出经验和推荐的时间特性,引入近期信任、长期信任、累积滥用信任和反馈可信度4个参数来计算节点信任度,并通过反馈控制机制动态调节上述参数,提高了信任模型的动态适应能力.仿真实验表明,与已有的信任模型相比,DyTrust具有更好的动态适应能力和反馈信息有效聚合能力,能够有效处理动态恶意节点策略性的行为改变和不诚实反馈对系统的攻击.
An important challenge regarding peer's trust valuation in P2P systems is how to cope with strategically altering behaviors and dishonest feedbacks of malicious peers efficiently. However, the trust models employed by the existing systems do not provide adequate support to coping with quick changes in peers' behavior and aggregating feedback information, so the authors present a time-frame based dynamic trust model DyTrust. After incorporating time dimension using time-frame, which captures experience and recommendation's time-sensitivity, the authors also introduce four trust parameters in computing trustworthiness of peers, namely, short time trust, long time trust, misusing trust accumulation and feedback credibility. Together, these parameters are adjusted in time to reflect the dynamics of the trust environment using feedback control mechanism, thus, the trust evaluation has better adaptability to the dynamics of trust. Theoretical analysis and simulation show that DyTrust has advantages in modeling dynamic trust relationship and aggregating feedback information over the existing trust metrics. It is highly effective in countering malicious peers regarding strategic altering behavior and dishonest feedbacks of malicious peers.