1,525 research outputs found
Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids
Smart grid is a large complex network with a myriad of vulnerabilities,
usually operated in adversarial settings and regulated based on estimated
system states. In this study, we propose a novel highly secure distributed
dynamic state estimation mechanism for wide-area (multi-area) smart grids,
composed of geographically separated subregions, each supervised by a local
control center. We firstly propose a distributed state estimator assuming
regular system operation, that achieves near-optimal performance based on the
local Kalman filters and with the exchange of necessary information between
local centers. To enhance the security, we further propose to (i) protect the
network database and the network communication channels against attacks and
data manipulations via a blockchain (BC)-based system design, where the BC
operates on the peer-to-peer network of local centers, (ii) locally detect the
measurement anomalies in real-time to eliminate their effects on the state
estimation process, and (iii) detect misbehaving (hacked/faulty) local centers
in real-time via a distributed trust management scheme over the network. We
provide theoretical guarantees regarding the false alarm rates of the proposed
detection schemes, where the false alarms can be easily controlled. Numerical
studies illustrate that the proposed mechanism offers reliable state estimation
under regular system operation, timely and accurate detection of anomalies, and
good state recovery performance in case of anomalies
Direct Acyclic Graph based Ledger for Internet of Things: Performance and Security Analysis
Direct Acyclic Graph (DAG)-based ledger and the corresponding consensus
algorithm has been identified as a promising technology for Internet of Things
(IoT). Compared with Proof-of-Work (PoW) and Proof-of-Stake (PoS) that have
been widely used in blockchain, the consensus mechanism designed on DAG
structure (simply called as DAG consensus) can overcome some shortcomings such
as high resource consumption, high transaction fee, low transaction throughput
and long confirmation delay. However, the theoretic analysis on the DAG
consensus is an untapped venue to be explored. To this end, based on one of the
most typical DAG consensuses, Tangle, we investigate the impact of network load
on the performance and security of the DAG-based ledger. Considering unsteady
network load, we first propose a Markov chain model to capture the behavior of
DAG consensus process under dynamic load conditions. The key performance
metrics, i.e., cumulative weight and confirmation delay are analysed based on
the proposed model. Then, we leverage a stochastic model to analyse the
probability of a successful double-spending attack in different network load
regimes. The results can provide an insightful understanding of DAG consensus
process, e.g., how the network load affects the confirmation delay and the
probability of a successful attack. Meanwhile, we also demonstrate the
trade-off between security level and confirmation delay, which can act as a
guidance for practical deployment of DAG-based ledgers.Comment: accepted by IEEE Transactions on Networkin
Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
The Internet of Things (IoT) has started to empower the future of many
industrial and mass-market applications. Localization techniques are becoming
key to add location context to IoT data without human perception and
intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN)
technologies have advantages such as long-range, low power consumption, low
cost, massive connections, and the capability for communication in both indoor
and outdoor areas. These features make LPWAN signals strong candidates for
mass-market localization applications. However, there are various error sources
that have limited localization performance by using such IoT signals. This
paper reviews the IoT localization system through the following sequence: IoT
localization system review -- localization data sources -- localization
algorithms -- localization error sources and mitigation -- localization
performance evaluation. Compared to the related surveys, this paper has a more
comprehensive and state-of-the-art review on IoT localization methods, an
original review on IoT localization error sources and mitigation, an original
review on IoT localization performance evaluation, and a more comprehensive
review of IoT localization applications, opportunities, and challenges. Thus,
this survey provides comprehensive guidance for peers who are interested in
enabling localization ability in the existing IoT systems, using IoT systems
for localization, or integrating IoT signals with the existing localization
sensors
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