The limited channel capacity and the varying propagation conditions of radio signals have motivated research for boosting the achievable throughput in wireless networks. Among the effective optimization strategies is to dynamically adjust the packet size either to better suit the channel conditions or to minimize the number of overhead bits in the individual packets. However, multi-levels of security requirements impose constraints on the data mix in the packet payload and may diminish the gains achievable by contemporary packet-size optimization schemes. This paper presents a novel bandwidth optimization algorithm for wireless data acquisition networks where strict confidentiality requirements and access restriction policies have to be observed. The algorithm exploits the classification of data in minimizing the number of packet transmissions as well as the overhead within the individual packets. The idea is to combine the transmission of packets based on the time sensitivity and security attributes of the data in the payload. The performance of the proposed algorithm is validated through mathematical analysis and through simulation. The simulation results confirm the effectiveness of the algorithm in boosting data throughput in the network.