# Research on Secure Community Opportunity Network Based on Trust Model
###### Abstract  
With the innovation of wireless communication technology and the surge of data in mobile networks, traditional routing strategies need to be improved. Given the shortcomings of existing opportunistic routing strategies in transmission performance and security, this paper proposes a community opportunistic routing decision-making method based on the trust model. This algorithm calculates the node's trust value through the node's historical forwarding behavior and then calculates the node's trust value based on the trust model. Thresholds and trust attenuation divide dynamic security communities. For message forwarding, nodes in the security community are prioritized as next-hop relay nodes, thus ensuring that message delivery is always in a safe and reliable environment. On this basis, better relay nodes are further selected for message forwarding based on the node centrality, remaining cache space, and remaining energy, effectively improving the message forwarding efficiency. Through node trust value and community cooperation, safe and efficient data transmission is achieved, thereby improving the transmission performance and security of the network. Through comparison of simulation and opportunistic network routing algorithms, compared with traditional methods, this strategy has the highest transmission success rate of 81% with slightly increased routing overhead, and this algorithm has the lowest average transmission delay. trust model; community opportunity routing; historical information; security community +
Footnote †: journal:  
0000-0001-1999-2299-2299-2999  
efficient next-hop relay nodes, thereby enhancing the network's transmission capabilities. However, these investigations tend to overlook the perilous influence of malicious and selfish nodes on the network's integrity [12; 13]. Given the reliance of opportunistic networks on the proactive engagement of all nodes for data transmission [14], they are particularly prone to security breaches. This underscores the necessity of not only choosing nodes based on their transmission efficacy but also ensuring the security credentials of these next-hop relay nodes. Moreover, the prevailing approach within opportunistic network research is to prioritize nodes with the highest transmission efficiency for relay purposes to achieve optimal local transmission outcomes [15]. This strategy neglects the potential strain on central nodes, which, when overly relied upon for data forwarding, face considerable storage pressure [16]. This, in turn, can lead to data congestion and the rapid depletion of node energy, necessitating further exploration into opportunistic network data transmission strategies. Opportunistic network forwarding requires nodes to cache data until an encounter with the destination node occurs [17]. Nonetheless, the mobile devices comprising these networks are typically constrained by limited computational power, storage capacity, and energy, frequently resulting in buffer overflows and data loss [18]. Particularly, flooding-based routing algorithms are prone to causing network congestion, node depletion, and delays in data transmission [19]. Thus, identifying strategies to alleviate backbone network transmission pressures and prolong network longevity, while ensuring the selection of efficient and secure relay nodes, presents a novel challenge in the realm of opportunistic networks. In response to the aforementioned challenges, this paper proposes a secure community algorithm based on the trust model. The algorithm computes node trust values based on historical interaction records, reflecting node performance within the opportunistic network. These records facilitate the prediction of subsequent node forwarding behavior. Subsequently, dynamic security communities are delineated using trust thresholds and decay. During message forwarding, nodes prioritize relay nodes within security communities, considering node centrality, remaining cache space, and energy levels.