Analysis of IoT-Based Load Altering Attacks Against Power Grids Using the Theory of Second-Order Dynamical Systems

Abstract : Recent research has shown that large-scale Internet of Things (IoT)-based load altering attacks can have a serious impact on power grid operations such as causing unsafe frequency excursions and destabilizing the grid’s control loops. In this work, we present an analytical framework to investigate the impact of IoT-based static/dynamic load altering attacks (S/DLAAs) on the power grid’s dynamic response. Existing work on this topic has mainly relied on numerical simulations and, to date, there is no analytical framework to identify the victim nodes from which that attacker can launch the most impactful attacks. To address these shortcomings, we use results from secondorder dynamical systems to analyze the power grid frequency control loop under S/DLAAs. We use parametric sensitivity of the system’s eigensolutions to identify victim nodes that correspond to the least-effort destabilizing DLAAs. Further, to analyze the SLAAs, we present closed-form expression for the system’s frequency response in terms of the attacker’s inputs, helping us characterize the minimum load change required to cause unsafe frequency excursions. Using these results, we formulate the defense against S/DLAAs as a linear programming problem in which we determine the minimum amount of load that needs to be secured at the victim nodes to ensure system safety/stability. Extensive simulations conducted using benchmark IEEE-bus systems validate the accuracy and efficacy of our approach.

 EXISTING SYSTEM :

 ? The highlights of the paper include the identification of attack points of different configurations of the LFC system, discussion of the attack strategies, formulation of various attack models, and a brief review of the existing detection and defense mechanisms against cyber-attacks on LFC. ? Apart from these, some reviews also focus on the attack impact analysis, modeling of networked control systems or cyber physical systems (CPS) under cyber-attacks, and existing attack mitigation techniques in general. ? In, the unknown vulnerability of existing bad data detection algorithms for two class of attacks (FDI attacks and generalized FDI attacks) with the attack goals of finding a random attack vector and targeted attack vector is investigated.

 DISADVANTAGE :

 ? Cyber attacks targeting bulk power grid operations and state estimation problems have received significant attention. ? The defense problem requires solving a simple linear programming problem, which is also computationally cheap. ? We also implement the defense against DLAAs by solving the optimization problem. ? Moreover, this approach has been extended in the past to advanced systems involving general higher-order eigenvalue problems. ? While DLAAs require enhanced capabilities on the part of the attacker, they can have a much more severe impact on grid operations than SLAAs, such as destabilizing the power grid control loops, leading to generator trips and cascading failures.

 PROPOSED SYSTEM :

 • A resilient control strategy against aperiodic DoS attack in interconnected-area power systems with communication delay is proposed in. • In, a defense method using ‘’Deep auto-encoder Extreme Learning Machine” (DAELM) is proposed. • The methods of low rank matrix factorization and nuclear norm minimization are proposed to separate the anomalies and nominal states of the power grid. • A recurring neural network (RNN)-based method is proposed for the detection of FDI attack in the AGC system with non-linearities like transportation time delay and governor dead band in. • As a countermeasure for an optimal coordinated attack (FDI attack and load manipulation), a threshold-based detection method is proposed in.

 ADVANTAGE :

 ? These intelligent devices provide convenience, efficiency and monitoring capabilities, enabling consumers to better manage their usage. ? The eigenvalues along with the right and left eigenvectors of the first-order system can be used to obtain the dynamic response of the system in an efficient manner under general forcing and initial conditions. ? LPs can be solved exactly and efficiently, demonstrating the effectiveness of the proposed approach of analyzing DLAAs using the parametric sensitivity analysis of the eigensolutions. ? In this work, we have shown how results from secondorder dynamical systems can be used to analyze IoT-based load altering attacks against power grids.