Trust　evaluation　is　a　key　issue　in　the　interaction　between　network　entities　in　open　networks.　The　attacks　of　malicious　entities　have　become　a　major　obstacle　to　the　development　of　open　networks.　Few　traditional　trust　models　have　considered　incorporating　incentive　mechanisms　to　reduce　the　influence　of　recommendation　values　from　malicious　entities　in　trust　evaluation.　This　paper　proposed　a　dynamic　evaluation　of　recommendation　trust　model,　considering　the　interaction　procedure　between　entities,　introducing　reward-punishment　factor　and　evaluation　reliability　factor.　The　function　of　reward-punishment　factor　is　to　reward　honest　interactions　between　entities　while　punishing　fraudulent　interactions.　The　evaluation　reliability　factor　is　used　to　decide　whether　to　accept　the　recommendations　from　the　recommending　entities.　Simulation　results　show　that　the　model　could　effectively　reduce　the　influence　of　malicious　entities　in　trust　evaluation.　The　proposed　model　could　accurately　and　reliably　identify　the　access　behaviour　of　malicious　entities,　and　adopt　appropriate　processing　countermeasure　to　ensure　the　accuracy　and　fault　tolerance　of　calculation.