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Optimizing resource and data security in shared sensor networks

机译:在共享传感器网络中优化资源和数据安全性

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A growing number of deployments of wireless sensor networks (WSNs) position the nodes as multipurpose albeit limited platforms. These platforms offer services to a set of applications of different owners. This view introduces security problems complementary to protection against outsiders requiring mechanisms beyond the existing physical, base crypto and network-level protection. Limited trust in the different applications mandates a security solution providing granular control over resources and data. Because of the constrained nature of network-embedded systems, transferring solutions from the distributed systems domain to the embedded system requires optimization. Distributed monitors can provide adequate security but must be concise and controllable by lightweight run-time artifacts as well as be deployed only where needed. Presented research consists of an operational model that inserts controls by instrumentation of local or remote interaction in the resource-rich back end, subsequently enforcing control at the nodes by using scaled down policy engines. The selective injection is achieved through aspect-oriented techniques. The solution is demonstrated for two paradigms encountered when building WSN applications, thus achieving local resource protection and protection of distributed event-based data flow. The costs and benefits of the selective injection approach are validated and quantified through a river monitoring case and associated simulation experiments. Copyright (c) 2011 John Wiley & Sons, Ltd.
机译:尽管节点数量有限,但无线传感器网络(WSN)的部署越来越多,这些节点仍被定位为多功能。这些平台为不同所有者的一组应用程序提供服务。这种观点引入了安全性问题,这些安全性问题是对外部人员的保护的补充,这些外部人员所需要的机制超出了现有的物理,基础加密和网络级保护范围。对不同应用程序的有限信任要求使用安全解决方案,以提供对资源和数据的精细控制。由于网络嵌入式系统的约束性质,因此需要将解决方案从分布式系统域转移到嵌入式系统需要进行优化。分布式监视器可以提供足够的安全性,但是必须由轻量级的运行时构件简洁且可控,并且只能在需要时进行部署。当前的研究包括一个操作模型,该模型通过在资源丰富的后端中通过本地或远程交互的手段插入控件来插入控件,然后使用缩小的策略引擎在节点上执行控件。选择性注入是通过面向方面的技术实现的。该解决方案针对构建WSN应用程序时遇到的两个范例进行了演示,从而实现了本地资源保护和对基于分布式事件的数据流的保护。通过河流监测案例和相关的模拟实验,对选择性注入方法的成本和收益进行了验证和量化。版权所有(c)2011 John Wiley&Sons,Ltd.

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