We study a network interdiction problem arising out of illicit human trafficking in the U.S. Southwest. Motivated by the significant amount of trafficking data shared with us by a large metropolitan police department, we modeled the interdiction problem as a Repeated One-Sum Game where, day after day, the Human Traffickers (HT) attempt to transport victims from one city to another and Law Enforcement Agencies (LEA) attempt to thwart the HT effort. Since the data indicated that most of the trafficking is taking place through road transportation, we built a network from the U.S. Interstate Highway System and called it U.S. Interstate Highway Network. If LEAs are successful, they win otherwise HTs win. If a HT wishes to transport victims from a city \(C_i\) to another city \(C_j\) , the strategy set for the HT is the set of paths going from \(C_i\) to \(C_j\) . Since a LEA can set up a check point on any segment of any path, the strategy set for the LEA is the union of all the path segments of all the paths connecting \(C_i\) to \(C_j\) . The path segments are the edges of the graph. If a HT selects a path \(P_k\) for transportation, a LEA can thwart that attempt only if a checkpoint is set up on at least one of the edges of \(P_k\) . If the total number of edges is \(E = \{e_1, \ldots , e_r\}\) , the LEA is interested in finding the probability vector \(P = [p_1, p_2, \ldots , p_r]\) that maximizes the expected payoff of the LEA, if the edge \(e_i\) is interdicted with probability \(p_i\) for all \(i, 1 \le i \le r\) . We show how to compute this probability vector P. Our extensive experimentation support our analytical results.