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Repairing Faulty Nodes and Locating a Dynamically Spawned Black Hole Search Using Tokens

机译:修复故障节点并使用令牌定位动态生成的黑洞搜索

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In a distributed cloud, it is crucial to detect and eliminate faulty network entities in order to protect network assets and mitigate the risks associated with constantly arising attacks. Much research has been conducted on locating a single static black hole, which is defined as a network site whose existence is known a priori and that disposes of any incoming data without leaving any trace of this occurrence. In this paper, we introduce a specific attack model that involves multiple faulty nodes that can be repaired by mobile software agents, as well as what we call a gray virus that can infect a previously repaired faulty node and turn it into a black hole. The Faulty Node Repair and Dynamically Spawned Black Hole Search (FNR-DSBHS) problem that proceeds from this model is much more complex and realistic than the traditional Black Hole Search problem. We first explain why existing algorithms addressing the latter do not work under this new attack model. We then distinguish between a one-stop gray virus that, after infecting a faulty node that has been repaired, can no longer travel to other nodes; and a multi-stop gray virus. We observe that, in an asynchronous network, a solution to the FNR-DSBHS problem is possible only when dealing with a single one-stop gray virus. In that specific context, we present a solution for an asynchronous ring network using a token model, that is, a ring in which a constant number of tokens is the only means of communication between the team of agents. We claim that, in such a ring, b + 9 agents can repair all faulty nodes as well as locate the black hole that is infected by this single one-stop gray virus. We prove the correctness of the proposed solution and analyze its complexity in terms of number of mobile agents used and total number of moves performed by these agents. We show that in the worst case, within O(kn2) moves, b + 9 agents suffice to repair b faulty nodes and report the location of the black hole that is infected, at any arbitrary point in time, by the one-stop gray virus.
机译:在分布式云中,至关重要的是检测并消除故障的网络实体,以保护网络资产并减轻与不断发生的攻击相关的风险。已经对定位单个静态黑洞进行了大量研究,该静态黑洞被定义为先验已知存在的网络站点,该站点可以处理任何传入数据,而不会留下任何这种情况的痕迹。在本文中,我们介绍了一种特定的攻击模型,其中涉及可通过移动软件代理修复的多个故障节点,以及所谓的灰色病毒,该病毒可感染先前修复的故障节点并将其变成黑洞。从该模型产生的故障节点修复和动态生成的黑洞搜索(FNR-DSBHS)问题比传统的黑洞搜索问题更为复杂和现实。我们首先说明为什么解决现有算法的现有算法在这种新的攻击模型下不起作用。然后,我们区分出一站式灰色病毒,该病毒在感染了已修复的故障节点后无法再传播到其他节点。和多站式灰色病毒。我们观察到,在异步网络中,仅当处理单个一站式灰色病毒时,才可能解决FNR-DSBHS问题。在这种特定的情况下,我们提出了一种使用令牌模型的异步环网解决方案,即一个环,其中恒定数量的令牌是代理团队之间唯一的通信方式。我们声称,在这样的环中,b + 9代理可以修复所有故障节点,并找到受此单一一站式灰色病毒感染的黑洞。我们证明了所提出解决方案的正确性,并根据使用的移动代理的数量以及这些代理执行的移动总数来分析其复杂性。我们表明,在最坏的情况下,在O(kn 2 )移动,b + 9个代理足以修复b个故障节点并报告在任何时间点被一站式灰色病毒感染的黑洞的位置。

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