IoT era and its ubiquitous sensing raise serious security challenges such as wormhole attacks. Given that these attacks may affect the location determination of the employed sensors, security can be seriously compromised. The most common and severe attack is the single wormhole one, which is the focus of this paper. One of the most employed algorithms to approach the sensor location determination is the Distance Vector Hop (DV-Hop) algorithm, which can still be seriously affected from wormhole attacks. To overcome the challenges of this algorithm, this article proposes a novel secure DV-Hop localization algorithm against wormhole attack (ANDV-Hop), where beacon nodes delegate their attacked neighboring nodes to broadcast data messages, and the intersection of communication range of these neighboring nodes does include wormhole nodes. For implicit attacks, close nodes to the wormhole node are selected in order to broadcast data messages, whilst the nodes within the attack range remove beacon nodes at the other end of the link from the neighboring list. For explicit wormhole attack, the algorithm employs a trust model that calculates the comprehensive trust value obtained via a selection reward/punish coefficient. The selected ones within the intersection zone are considered rewarded, whilst the ones to be removed are classified as punished. Experimental results show that the proposed algorithm improves detection success rate, reduces relative localization error and energy loss, showing effectiveness and reliability.

物联网时代及其无处不在的传感带来了严重的安全挑战，例如虫洞攻击。鉴于这些攻击可能会影响所使用传感器的位置确定，安全性可能会受到严重损害。最常见和最严重的攻击是单虫洞攻击，这是本文的重点。接近传感器位置确定的最常用算法之一是距离向量跳 (DV-Hop) 算法，它仍然会受到虫洞攻击的严重影响。为了克服该算法的挑战，本文提出了一种新颖的针对虫洞攻击的安全DV-Hop定位算法（ANDV-Hop），其中信标节点委托其被攻击的相邻节点广播数据消息，并且这些相邻节点的通信范围的交集节点确实包括虫洞节点。对于隐式攻击，选择靠近虫洞节点的节点以广播数据消息，而攻击范围内的节点从相邻列表中删除链路另一端的信标节点。对于显式虫洞攻击，该算法采用信任模型，计算通过选择奖励/惩罚系数获得的综合信任值。在交叉区域内被选中的被认为是奖励的，而被删除的被归类为惩罚。实验结果表明，该算法提高了检测成功率，减少了相对定位误差和能量损失，显示出有效性和可靠性。而攻击范围内的节点从邻居列表中删除链路另一端的信标节点。对于显式虫洞攻击，该算法采用信任模型，计算通过选择奖励/惩罚系数获得的综合信任值。在交叉区域内被选中的被认为是奖励的，而被删除的被归类为惩罚。实验结果表明，该算法提高了检测成功率，减少了相对定位误差和能量损失，显示出有效性和可靠性。而攻击范围内的节点从邻居列表中删除链路另一端的信标节点。对于显式虫洞攻击，该算法采用信任模型，计算通过选择奖励/惩罚系数获得的综合信任值。在交叉区域内被选中的被认为是奖励的，而被删除的被归类为惩罚。实验结果表明，该算法提高了检测成功率，减少了相对定位误差和能量损失，显示出有效性和可靠性。在交叉区域内被选中的被认为是奖励的，而被删除的被归类为惩罚。实验结果表明，该算法提高了检测成功率，减少了相对定位误差和能量损失，显示出有效性和可靠性。在交叉区域内被选中的被认为是奖励的，而被删除的被归类为惩罚。实验结果表明，该算法提高了检测成功率，减少了相对定位误差和能量损失，显示出有效性和可靠性。