Memory analysis is a technique which uses the RAM image of the affected computer to detect suspicious process running in memory. Though, several tools for memory analysis exist in literature, the drawback is that, manual analysis has to be done to identify suspicious process which is time consuming. Thus it is proposed to design a computationally intelligent tool that identifies the suspicious processes in the memory. The drawbacks of the existing approaches to identify multiple instances of processes in memory is that the computational complexity is high. This chapter proposes an Ant Colony Optimization-based approach to identify suspicious process (ACOISP) algorithm to identify suspicious process based on the instance count of processes. The advantage of this approach is that the computational complexity of the algorithm is less when compared to the existing methods.