隨著世界演變、科技的蓬勃發展以及社會的變遷，行動上網裝置已被人類開始廣泛地使用。這些趨勢導致越來越多的使用者加入隨意網路，但可想而知，伴隨而來的將是一連串安全性的問題。事實上，資訊安全問題確實一直是隨意網路一個很大的隱憂。而隨著使用者的增加，傳統的解決方法，無法直接應用在隨意網路上。人們需要的將是一個全面、強健的安全系統，來防止隨意網路受到惡意性的攻擊。
近年來，信任值管理這個領域，已經吸引許多學者相繼投入做研究。主要的原因是，信任值管理提供了一個高層次的安全管理系統，廣泛地應用在異常節點偵測、路由協定，甚至延伸到電子商務、資料聚集以及研究隨意網路的潛在威脅。信任值管理需要參考、吸收其他節點的意見來增進整個系統的強健性，然而週期性的發佈自己觀察到的資訊給其他節點，可能會導致消耗太多頻寬，甚至使整個網路產生阻塞的現象。反之，若捨棄了參考、吸收其他節點的意見，那這個系統可能會變得不夠客觀，並且降低了異常行為節點的偵測率。
在這篇論文，我們提出了一個在隨意網路環境下有效率的信任值收集法，被動式的迅速蒐集二手資訊。一開始使用者節點會根據鄰居節點各自所觀察到的節點密度，把它們做一個簡單的排序，然後根據密度特徵，把鄰居節點分為k群。最後，從一個特定的群組中，找出一個繼承節點，接替往後的工作。在模擬方面，我們考慮了三種影響隨意網路的要素，實驗結果顯示，我們的方法非常適合用在高密度的隨意網路中，而且將成為協助節點取得有用資訊的強大工具。

As the world modernizes nowadays, change of the society, and the popular use of mobile internet device by almost every human being. Consequently, there are more and more user nodes take part in mobile ad hoc networks. On the other hand, the security problems of mobile ad hoc networks have been suffering from a severe challenge. However, security methods used to deal with traditional problems can not directly be used on MANETs environment. It is obviously that people need a robust system to guard networks against wicked attacks. Then, how to build trust among nodes is the key to prevent the adversary from launching a successful attack.
In recent years, trust management framework has drawn many researchers’ attentions to this field. Trust management framework provides a high-level consideration of security policy and management, and this framework is used comprehensively for misbehavior detection, secure routing protocol, and key management and extends to access control, e-commerce, data aggregation, and even researching potential threats in mobile ad hoc networks. In trust management framework, node requires absorbing the other nodes’ opinions to improve the robustness of this framework. However, nodes periodically exchange their direct observation to each others, which consumes more bandwidth even generates a traffic jam. Whereas, it is not objective when node only adopts its neighbors’ direct observation, and narrows the detection rate of misbehaved nodes.
In this thesis, we present a new method called virtual cluster data collection method (VCDC) for reactive collecting second-hand information rapidly in trust management framework. At first, user node sorts neighbor nodes according to the node density they observed with a common ways. Next, calculate covariance value between two nodes in the sorting order, then according to covariance value, dividing neighbor nodes into k groups. Last, choose an inheritor from a specific group to take over the following works. We also conduct simulations based on three key factors, and it shows that our method is very suitable for high-density mobile ad hoc networks and will be a powerful tool to assist nodes gathering useful information.

[1] Young-Bae Ko and Nitin H. Vaidya, “Location-aided routing (LAR) in mobile ad hoc networks,” journal of Wireless Networks, vol. 6, no. 4, pp. 307-321, 2000.
[2] Raymond Pickholtz, Sajal K. Das, Ramon Caceres, and J. J. Garcia-Luna-Aceves, “Mitigating routing misbehavior in mobile ad hoc networks,” Proceedings of the 6th annual international conference on Mobile computing and networking, Boston, MA, USA, pp. 255-265, 2000.
[3] Yu-Chee Tseng, Sze-Yao Ni, Yuh-Shyan Chen, and Jang-Ping Sheu, “The broadcast storm problem in a mobile ad hoc network,” journal of Wireless Networks, vol. 8, no. 2-3, pp. 153-167, 2002.
[4] S. Buchegger and J.-Y. Le Boudec, “A robust reputation system for p2p and mobile ad-hoc networks,” Proceedings of P2PEcon, Harvard Univ., Cambridge, MA, 2004.
[5] D. Cokuslu, K. Erciyes, O. Dagdeviren, “A dominating set based clustering algorithm for mobile ad hoc networks,” Proceedings of the 6th International Conference of Computational Science, Reading, UK, pp. 571-578, 2006.
[6] A.B. MaDonald, T.F. Znati, “A mobility-based framework for adaptive clustering in wireless ad hoc networks,” IEEE Journal on Selected Areas in Communications, vol. 17, pp. 1466-1487, 1999.
[7] I.I. ER, Winston K.G. Seah, “Mobility-based d-hop clustering algorithm for mobile ad hoc networks,” Proceedings of the Wireless Communications and Networking Conference (WCNC04), vol. 4, pp. 2359-2364, 2004.
[8] C. Konstantopoulos, D. Gavalas, G. Pantziou, “A mobility aware technique for clustering on mobile ad-hoc networks,” Proceedings of the 8th International Conference on Distributed Computing and Networking (ICDCN06), Guwahati, India, pp. 397-408, 2006.
[9] Josh Broch, David A. Maltz, David B. Johnson, Yih-Chun Hu and Jorjeta Jetcheva, “A performance comparison of multi-hop wireless ad hoc network routing protocols,” Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking, Dallas, Texas, United States, pp. 85-97, 1998.
[10] S. Corson and J. Macker, “Mobile Ad Hoc Networking (MANET): Routing Protocol Performance Issues and Evaluation Considerations,” RFC 2501, 1999.
[11] David B. Johnson and David A. Maltz, “Dynamic Source Routing in Ad Hoc Wireless Networks,” Mobile Computing, vol. 353, pp. 153-181, 1996
[12] C. Perkins, E. Belding-Royer, and S. Das., “Ad-hoc on-demand distance vector routing,” Proceedings of Mobile Computing Systems and Applications. Second IEEE Workshop on, New Orleans, L.A., USA, pp. 90-100, 1999.
[13] Sergio Marti, T. J. Giuli, Kevin Lai, and Mary Baker, “Mitigating routing misbehavior in mobile ad hoc networks,” Proceedings of the 6th annual international conference on Mobile computing and networking, Boston, MA, USA, pp. 255-265, 2000.
[14] Djamel Djenouri and Nadjib Badache, “On eliminating packet droppers in MANET: A modular solution,” Ad Hoc Networks, vol. 7, no. 6, pp. 1243-1258, 2009.
[15] Charikleia Zouridaki, Brian L. Mark, Marek Hejmo, and Roshan K. Thomas, “E-Hermes: A robust cooperative trust establishment scheme for mobile ad hoc networks,” Ad Hoc Networks, vol. 7, no. 6, pp. 1156-1168, 2009.
[16] Jie Li, Ruidong Li, and Jien Kato, “Future trust management framework for mobile ad hoc networks,” Communications Magazine, IEEE, vol. 46, no. 4, pp. 108-114, 2008.
[17] Yan Lindsay Sun, Zhu Han, and K. J. Ray Liu, “Defense of trust management vulnerabilities in distributed networks,” Communications Magazine, IEEE, vol. 46, no. 2, pp. 112-119, 2008.
[18] George Theodorakopoulos and John S. Baras, “On trust models and trust evaluation metrics for ad hoc networks,” IEEE Journal on Selected Areas in Communications, vol. 24, no. 2, pp. 318-328, 2006.
[19] Mohamed Elhoucine Elhdhili, Lamia Ben Azzouz, and Farouk Kamoun, “CASAN: Clustering algorithm for security in ad hoc networks,” Journal of Computer Communications, vol. 31, no. 13, pp. 2972-2980, 2008.