Car accidents are one of the leading causes of human fatalities worldwide. Given the variation in capabilities of drivers in different driving conditions, a personalized safety-based routing - that considers the variation in driving skills - is a step towards minimizing drivers' individual and aggregate risk. In this paper, we propose iRouteSafe, a novel cloud-based route planner that utilizes drivers' individualized risk profiles in suggesting routing options based on drivers' personal skillfulness levels. Using graph theory concepts, the routing problem is formulated as a combinatorial multi-objective optimization problem where the objective is to find the optimal route that minimizes cost function composed of a route's travel time, expected risk, and the personal driver-specific risk in such driving routes. To highlight the significance of the proposed route planning, a case study is presented.