本文選題：分布式協(xié)作頻譜感知 + 拜占庭攻擊　； 參考：《南京郵電大學(xué)》2017年碩士論文

【摘要】：協(xié)作頻譜感知是認(rèn)知無線電網(wǎng)絡(luò)中的重要技術(shù)之一。在存在陰影與衰落的感知環(huán)境中,可以極大地提高頻譜感知精度。然而,協(xié)作頻譜感知固有的協(xié)作性與分布特性,使其極易受到惡意用戶的攻擊,從而導(dǎo)致感知系統(tǒng)的不穩(wěn)定。在本文中,針對分布式協(xié)作頻譜感知場景中的拜占庭攻擊進(jìn)行了相關(guān)的防御方案設(shè)計(jì),具體內(nèi)容如下:首先,敘述了頻譜感知技術(shù)的相關(guān)理論參數(shù),介紹了在集中式與分布式場景下,協(xié)作頻譜感知中常用的數(shù)據(jù)融合算法。并探討了協(xié)作頻譜感知場景中存在的拜占庭攻擊類型及相應(yīng)的安全防御機(jī)制。其次,研究了在分布式協(xié)作頻譜感知場景中常見的幾種拜占庭攻擊方式,并提出了一種將效用模型引入到共識算法中的惡意攻擊防御方案。在該方案中,認(rèn)知用戶在頻譜感知過程中,被認(rèn)為是智能的,有能力去計(jì)算自身的效用值,并追求自身利益最大化。通過懲罰與獎勵(lì)機(jī)制,在不識別出惡意用戶的情況下,使其主動放棄惡意攻擊,最終使全網(wǎng)達(dá)成收斂一致。理論分析與仿真結(jié)果表明,本文所提方案可以有效防御多種拜占庭攻擊方式。與現(xiàn)有的幾種防御方案相比,本方案具有更好的安全性能。最后,針對認(rèn)知無線電網(wǎng)絡(luò)中惡意用戶實(shí)時(shí)多變的特點(diǎn),提出了一種在分布式協(xié)作頻譜感知場景下,將信譽(yù)模型與強(qiáng)化學(xué)習(xí)結(jié)合的智能安全機(jī)制。在本方案中,每個(gè)認(rèn)知用戶被看成是一個(gè)智能體,通過強(qiáng)化學(xué)習(xí)從鄰居用戶中選取合作用戶,并使用信譽(yù)值的形式來懲罰與獎勵(lì)合作認(rèn)知用戶,使認(rèn)知用戶通過不斷學(xué)習(xí),可發(fā)現(xiàn)潛在的惡意用戶,最終通過一致性融合算法使全網(wǎng)達(dá)成共識。通過數(shù)值仿真,證明了本方案可有效的甄別出惡意用戶,并隨著學(xué)習(xí)過程的深入,系統(tǒng)的安全性能會得到有效加強(qiáng)。
[Abstract]:Cooperative spectrum sensing is one of the most important technologies in cognitive radio networks. The spectral sensing accuracy can be greatly improved in the perceptual environment with shadow and fading. However, the inherent cooperative and distributed characteristics of cooperative spectrum sensing make it vulnerable to attack by malicious users, which leads to the instability of the sensing system. In this paper, the defense scheme of Byzantine attack in distributed cooperative spectrum sensing scene is designed. The specific contents are as follows: firstly, the related theoretical parameters of spectrum sensing technology are described. In this paper, the common data fusion algorithms in cooperative spectrum sensing in centralized and distributed scenarios are introduced. The types of Byzantine attacks in the cooperative spectrum sensing scene and the corresponding security defense mechanisms are discussed. Secondly, several common Byzantine attack methods in distributed cooperative spectrum sensing scene are studied, and a malicious attack defense scheme which introduces utility model into consensus algorithm is proposed. In this scheme, cognitive users are considered intelligent and able to calculate their own utility value and pursue the maximum of their own benefits in the process of spectrum sensing. Through the mechanism of punishment and reward, the malicious users are not identified, and the malicious attacks are given up voluntarily, so that the whole network can converge. Theoretical analysis and simulation results show that the proposed scheme can effectively defend against various Byzantine attacks. Compared with several existing defense schemes, this scheme has better security performance. Finally, in view of the real-time variability of malicious users in cognitive radio networks, an intelligent security mechanism combining reputation model with reinforcement learning is proposed in the distributed cooperative spectrum sensing scenario. In this scheme, each cognitive user is regarded as an agent. Through intensive learning, the cooperative user is selected from the neighbor user, and the credit value is used to punish and reward the cooperative cognitive user, so that the cognitive user can learn continuously. Potential malicious users can be found, and the consensus of the whole network can be reached through the consistency fusion algorithm. Through numerical simulation, it is proved that this scheme can effectively identify malicious users, and with the deepening of learning process, the security performance of the system will be effectively enhanced.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN925

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1 張凱;李鷗;楊白薇;;基于Q-learning的機(jī)會頻譜接入信道選擇算法[J];計(jì)算機(jī)應(yīng)用研究;2013年05期

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本文編號：1802171