With the rapid development of mobile Internet and the emergence of massive big data， information security risks are increasingly prominent， so the construction and improvement of a scientific and objective security risk assessment system have great theoretical and practical significance. However， the existing assessment methods face challenges such as the representation of uncertain information， the objective quantification of expert and attribute weights， and the fusion of uncertain information. To address these challenges， an information security risk assessment model based on multi-objective programming and evidential reasoning theory was proposed. First， interval-valued intuitionistic fuzzy numbers were used to represent uncertain information， and three basic operational laws were defined. Second， expert and attribute weights were quantified objectively based on multi-objective programming. Third， evidential reasoning fusion rules in the interval-valued intuitionistic fuzzy environment were introduced to solve the fusion problem of uncertain information. Finally， the ideal solution approaching method TOPSIS （Technique for Order Preference by Similarity to Ideal Solution） was referenced for comprehensive information security assessment. Experimental results verify the effectiveness and feasibility of the proposed model in information representation， weight quantification， and risk assessment.