Contextual Dishonest Behaviour Detection for Cognitive Adaptive Charging in Dynamic Smart Micro-Grids
Contextual Dishonest Behaviour Detection for Cognitive Adaptive Charging in Dynamic Smart Micro-Grids
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DOI：
10.23919/wons.2019.8795461
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发表时间：
2019-01
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影响因子：
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通讯作者：
M. Radenkovic;Adam David Walker
中科院分区：
文献类型：
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作者：
M. Radenkovic;Adam David Walker
新兴的智能电网（SG）范式有望解决因安全运营利润变薄而导致的电网稳定性下降问题，满足电动汽车（EV）等普遍高容量设备不断增长的需求，并全面拥抱向绿色能源解决方案的转变。在SG边缘，异构设备的广泛分散，加上能源可用性和需求的波动，以及能源生产者、消费者和商店角色之间的流动性大大增加，对确保信息和能源交换的稳健性和安全性提出了重大挑战。检测并减轻这些环境中的恶意和非恶意威胁对于充分发挥 SG 的潜力至关重要。为了满足网格边缘对强大、本地化、实时安全的需求，我们提出了 CONCEDE，这是一种协作的跨层自我网络完整性意识和攻击影响减少扩展，是对我们之前关于延迟容忍认知自适应能量交换的工作的扩展。我们详细介绍了由移动能源产消者串通实施的大规模、有针对性的能源破坏攻击。然后，我们的 CONCEDE 提案在多个不同的智能微电网 (SMG) 场景中进行评估，使用来自欧洲、北美和南美的电动汽车和基础设施的混合痕迹，并应对恶意分销商寻求破坏目标社区能源供应的协调攻击。我们表明，CONCEDE 成功检测和识别表现出恶意、不诚实行为的节点，并且 CONCEDE 还跨多个标准在所有探索的场景中减少了协调能源破坏攻击对无辜方的影响。关键词—智能能源、移动 DTN、自动驾驶汽车、安全
The emerging Smart Grid (SG) paradigm promises to address decreasing grid stability from thinning safe operating margins, meet continually rising demand from pervasive high capacity devices such as electric vehicles (EVs), and fully embrace the shift towards green energy solutions. At the SG edge, widespread decentralisation of heterogeneous devices coupled with fluctuating energy availability and need as well as a greatly increased fluidity between their roles as energy producers, consumers, and stores raises significant challenges to ensuring robustness and security of both information and energy exchange. Detecting and mitigating both malicious and non-malicious threats in these environments is essential to the realisation of the full potential of the SG. To address this need for robust, localised, real-time security at the grid edge we propose CONCEDE, a collaborative cross-layer ego-network integrity awareness and attack impact reduction extension to our previous work on delay-tolerant cognitive adaptive energy exchange. We detail a substantial, targeted, energy disruption attack perpetrated by colluding mobile energy prosumers. Our CONCEDE proposal is then evaluated in multiple, diverse smart micro-grid (SMG) scenarios using hybrid traces of EVs and infrastructure from Europe, North America, and South America in the presence of a coordinated attack from malicious distributors seeking to disrupt energy supply to a target community. We show that CONCEDE successfully detects and identifies the nodes exhibiting malicious, dishonest behaviour and that CONCEDE also reduces the impact of a coordinated energy disruption attack on innocent parties in all explored scenarios across multiple criteria. Keywords— Smart energy, Mobile DTNs, Autonomous Vehicles, Security