Cryptographic algorithms are widely used to protect data privacy in many aspects of daily lives from smart card to cyber-physical systems. Unfortunately, programs implementing cryptographic algorithms may be vulnerable to practical power side-channel attacks, which may infer private data via statistical analysis of the correlation between power consumptions of an electronic device and private data. To thwart these attacks, several masking schemes have been proposed. However, programs that rely on secure masking schemes are not secure a priori. Although some techniques have been proposed for formally verifying masking countermeasures and for quantifying masking strength, they are currently limited to Boolean programs and suffer from low accuracy. In this work, we propose an approach for formally verifying masking countermeasures of arithmetic programs. Our approach is more accurate for arithmetic programs and more scalable for Boolean programs comparing to the existing approaches. We have implemented our methods in a verification tool QMVerif which has been extensively evaluated on cryptographic benchmarks including full AES, DES and MAC-Keccak. The experimental results demonstrate the effectiveness and efficiency of our approach, especially for compositional reasoning.