Energy Life-Time of Wireless Nodes with Network Attacks and Mitigation

Gelenbe, Erol; Kadioglu, Yasin Murat

doi:10.1109/iccw.2018.8403561

Cited by 21 publications

(13 citation statements)

References 24 publications

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“…For instance, the adversary conducts a discovery phase to learn the accumulative energy dynamics of the network, by probing and estimating the level of available battery on each individual node of the system. Countermeasures to the attack, like those in [16,27] are similar to some of the ideas discussed in Section 5.…”

Section: Routing Literaturementioning

confidence: 91%

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On the Difficulty of Hiding the Balance of Lightning Network Channels

Herrera-Joancomartí

Navarro‐Arribas

Ranchal-Pedrosa

et al. 2019

Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security

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The Lightning Network is a second layer technology running on top of Bitcoin and other Blockchains. It is composed of a peer-to-peer network, used to transfer raw information data. Some of the links in the peer-to-peer network are identified as payment channels, used to conduct payments between two Lightning Network clients (i.e., the two nodes of the channel). Payment channels are created with a fixed credit amount, the channel capacity. The channel capacity, together with the IP address of the nodes, is published to allow a routing algorithm to find an existing path between two nodes that do not have a direct payment channel. However, to preserve users' privacy, the precise balance of the pair of nodes of a given channel (i.e. the bandwidth of the channel in each direction), is kept secret. Since balances are not announced, second-layer nodes probe routes iteratively, until they find a successful route to the destination for the amount required, if any. This feature makes the routing discovery protocol less efficient but preserves the privacy of channel balances. In this paper, we present an attack to disclose the balance of a channel in the Lightning Network. Our attack is based on performing multiple payments ensuring that none of them is finalized, minimizing the economical cost of the attack. We present experimental results that validate our claims, and countermeasures to handle the attack.

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Section: Routing Literaturementioning

confidence: 91%

“…In this case, the maximum bandwidth (cf. Lines [16][17][18] is modified. Since the adversary cannot get any further information w.r.t.…”

Section: Attack Implementationmentioning

confidence: 99%

On the Difficulty of Hiding the Balance of Lightning Network Channels

Herrera-Joancomartí

Navarro‐Arribas

Ranchal-Pedrosa

et al. 2019

Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security

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“…In [84], the authors derived a new PFS, which is a distinct approach from G-network, for a tandem network of N nodes using harvested energy stored in batteries. The effect of battery attacks at the nodes of energy provisioning systems was investigated in [46]. A simple mitigation technique was proposed for a wireless node with a renewable or a replaceable battery to drop a fraction of the traffic to prolong battery lifetime.…”

Section: Energy Packet Network With Zero Service Timementioning

confidence: 99%

G-Networks and the Performance of ICT with Renewable Energy

Zhang

2020

SN COMPUT. SCI.

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As a consequence of developing information and communication technology that is playing a significant role in our society and has changed our life dramatically, we witnessed a significant increase in energy consumption in computer systems and networks. Subsequently, energy harvesting technologies with renewable energy are of great interest in the field of computer systems and networks, and thus lead to abundant research which has been carried out to address energy harvesting from different aspects. However, the majority of them focuses on wireless or small-scale networks, which left wired networks with a general structure neglected. We first present a comprehensive systemic review of the trends of overall energy consumption, and energy and quality of service optimization in computer systems and networks. Then, this paper reviews the recent research progress in G-networks and energy packet networks with renewable and intermittent energy from both the system paradigms and the performance optimization and energy reduction algorithms for the wired networks.

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“…Denial-of-Sleep attacks may target various IoT protocols [6]. Various strategies can be used, ranging from useless data packets that receivers must process to jamming of radio channels that causes errors and thus costly retransmissions [9]. Furthermore, malicious control packets may lead to excessive energy consumption due to e.g., illegitimate duty-cycle modifications.…”

Section: Background and Related Workmentioning

confidence: 99%

Denial-of-Sleep Attacks against IoT Networks

Gallais

Hedli

Loscrì

et al. 2019

2019 6th International Conference on Control, Decision and Information Technologies (CoDIT)

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Numerous medium access control (MAC) have been proposed for Low-power Lossy Networks (LLNs) over the recent years. They aim at ensuring both energy efficiency and robustness of the communication transmissions. Nowadays, we observe deployments of LLNs for potentially critical application scenarios (e.g., plant monitoring, building automation), which require both determinism and security guarantees. They involve battery-powered devices which communicate over lossy wireless links. Radio interfaces are turned off by a node as soon as no traffic is to be sent or relayed. Denial-of-sleep attacks consist in exhausting the devices by forcing them to keep their radio on. We here focus on jamming attacks whose impact can be mitigated by approaches such as time-division and channel hopping techniques. We use the IEEE 802.15.4e standard to show that such approaches manage to be resistant to basic jamming but yet remain vulnerable to selective jamming. We discuss the potential impacts of such onslaughts, depending on the knowledge gained by the attacker, and to what extent envisioned protections may allow jamming attacks to be handled at upper layers.

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Energy Life-Time of Wireless Nodes with Network Attacks and Mitigation

Cited by 21 publications

References 24 publications

On the Difficulty of Hiding the Balance of Lightning Network Channels

On the Difficulty of Hiding the Balance of Lightning Network Channels

G-Networks and the Performance of ICT with Renewable Energy

Denial-of-Sleep Attacks against IoT Networks

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