Cloud computing systems, in which clients rent and share computing resources of third party platforms, have gained widespread use in recent years. Furthermore, cloud computing for mobile systems (i.e., systems in which the clients are mobile devices) have too been receiving considerable attention in technical literature. We propose a new method of delegating computations of resource-constrained mobile clients, in which multiple servers interact to construct an encrypted program known as garbled circuit. Next, using garbled inputs from a mobile client, another server executes this garbled circuit and returns the resulting garbled outputs. Our system assures privacy of the mobile client's data, even if the executing server chooses to collude with all but one of the other servers. We adapt the garbled circuit design of Beaver et al. and the secure multiparty computation protocol of Goldreich et al. for the purpose of building a secure cloud computing for mobile systems. Our method incorporates the novel use of the cryptographically secure pseudo random number generator of Blum et al. that enables the mobile client to efficiently retrieve the result of the computation, as well as to verify that the evaluator actually performed the computation. We analyze the server-side and client-side complexity of our system. Using real-world data, we evaluate our system for a privacy preserving search application that locates the nearest bank/ATM from the mobile client. We also measure the time taken to construct and evaluate the garbled circuit for varying number of servers, demonstrating the feasibility of our secure and verifiable cloud computing for mobile systems.