SybilComm: Sybil community detection using persuading function in IoT system

An analytical Survey of Attack Scenario Parameters on the Techniques of Attack Mitigation in WSN

“…Table 3 shows the topologies used by each proposal, whether the proposal makes an analysis or takes into account the detection of false positives, and also if the proposal detects and prevents the sybil attack. Ad-Hoc WSN No Yes Yes [111] Cluster/Tree Yes Yes No [52] Cluster/Tree Yes Yes No [62] VANET Yes Yes Yes [62] Cluster/Tree No Yes No [64] MANET No Yes Yes [42] Cluster/Tree No Yes Yes [9] VANET No Yes Yes [67] MANET Yes Yes Yes [94] Cluster/Tree Yes Yes No [79] MANET Yes Yes Yes [107] VANET No Yes Yes [109] VANET No Yes Yes [71] MANET No Yes Yes [102] Ad-Hoc WSN No Yes Yes [91] Cluster/Tree Yes Yes No [58] Ad-Hoc WSN No Yes No [61] Ad-Hoc WSN No Yes Yes [112] Ad-Hoc WSN Yes Yes No [80] Cluster/Tree No Yes No [93] Ad-Hoc WSN Yes Yes No [139] MANET No No Yes [32] VANET Yes Yes No [95] VANET No Yes Yes [134] VANET Yes Yes Yes [12] Cluster/Tree Yes Yes No [92] Cluster/Tree No Yes No [43] Ad-Hoc WSN No Yes Yes [110] MANET Yes Yes No Figure 9 summarizes Table II and quantifies the last 3 columns. The 91,2% of the proposals detect the sybil attack, the 41,2% include in their proposal the detection of false positives, and 50% prevents the sybil attack.…”