FSopt_k: Finding the Optimal Anonymization Level for a Social Network Graph

k-degree anonymity is known as one of the best models for anonymizing social network graphs. Although recent works have tried to address privacy challenges graphs, levels are considered be independent features graph degree sequence. In other words, optimal value k not graph, leading increasing information loss. Additionally, may need a high level. addition, determining in advance big problem data owner. Therefore, this paper, we present technique named FSopt_k that able find each graph. This algorithm uses an efficient partition nodes choose value. It considers structure determine way, there will balance between and loss anonymized Furthermore, low possible. The evaluation results depict can short time well preserve graph’s utility.