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2021-04-08
Venkitasubramaniam, P., Yao, J., Pradhan, P..  2015.  Information-Theoretic Security in Stochastic Control Systems. Proceedings of the IEEE. 103:1914–1931.
Infrastructural systems such as the electricity grid, healthcare, and transportation networks today rely increasingly on the joint functioning of networked information systems and physical components, in short, on cyber-physical architectures. Despite tremendous advances in cryptography, physical-layer security and authentication, information attacks, both passive such as eavesdropping, and active such as unauthorized data injection, continue to thwart the reliable functioning of networked systems. In systems with joint cyber-physical functionality, the ability of an adversary to monitor transmitted information or introduce false information can lead to sensitive user data being leaked or result in critical damages to the underlying physical system. This paper investigates two broad challenges in information security in cyber-physical systems (CPSs): preventing retrieval of internal physical system information through monitored external cyber flows, and limiting the modification of physical system functioning through compromised cyber flows. A rigorous analytical framework grounded on information-theoretic security is developed to study these challenges in a general stochastic control system abstraction-a theoretical building block for CPSs-with the objectives of quantifying the fundamental tradeoffs between information security and physical system performance, and through the process, designing provably secure controller policies. Recent results are presented that establish the theoretical basis for the framework, in addition to practical applications in timing analysis of anonymous systems, and demand response systems in a smart electricity grid.
Imai, H., Hanaoka, G., Shikata, J., Otsuka, A., Nascimento, A. C..  2002.  Cryptography with information theoretic security. Proceedings of the IEEE Information Theory Workshop. :73–.
Summary form only given. We discuss information-theoretic methods to prove the security of cryptosystems. We study what is called, unconditionally secure (or information-theoretically secure) cryptographic schemes in search for a system that can provide long-term security and that does not impose limits on the adversary's computational power.
2021-03-29
Kummerow, A., Monsalve, C., Rösch, D., Schäfer, K., Nicolai, S..  2020.  Cyber-physical data stream assessment incorporating Digital Twins in future power systems. 2020 International Conference on Smart Energy Systems and Technologies (SEST). :1—6.

Reliable and secure grid operations become more and more challenging in context of increasing IT/OT convergence and decreasing dynamic margins in today's power systems. To ensure the correct operation of monitoring and control functions in control centres, an intelligent assessment of the different information sources is necessary to provide a robust data source in case of critical physical events as well as cyber-attacks. Within this paper, a holistic data stream assessment methodology is proposed using an expert knowledge based cyber-physical situational awareness for different steady and transient system states. This approach goes beyond existing techniques by combining high-resolution PMU data with SCADA information as well as Digital Twin and AI based anomaly detection functionalities.

Fajri, M., Hariyanto, N., Gemsjaeger, B..  2020.  Automatic Protection Implementation Considering Protection Assessment Method of DER Penetration for Smart Distribution Network. 2020 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP). :323—328.
Due to geographical locations of Indonesia, some technology such as hydro and solar photovoltaics are very attractive to be used and developed. Distribution Energy Resources (DER) is the appropriate schemes implemented to achieve optimal operation respecting the location and capacity of the plant. The Gorontalo sub-system network was chosen as a case study considering both of micro-hydro and PV as contributed to supply the grid. The needs of a smart electrical system are required to improve reliability, power quality, and adaptation to any circumstances during DER application. While the topology was changing over time, intermittent of DER output and bidirectional power flow can be overcome with smart grid systems. In this study, an automation algorithm has been conducted to aid the engineers in solving the protection problems caused by DER implementation. The Protection Security Assessment (PSA) method is used to evaluate the state of the protection system. Determine the relay settings using an adaptive rule-based method on expert systems. The application with a Graphical User Interface (GUI) has been developed to make user easier to get the specific relay settings and locations which are sensitive, fast, reliable, and selective.
Kazemi, Z., Fazeli, M., Hély, D., Beroulle, V..  2020.  Hardware Security Vulnerability Assessment to Identify the Potential Risks in A Critical Embedded Application. 2020 IEEE 26th International Symposium on On-Line Testing and Robust System Design (IOLTS). :1—6.

Internet of Things (IoT) is experiencing significant growth in the safety-critical applications which have caused new security challenges. These devices are becoming targets for different types of physical attacks, which are exacerbated by their diversity and accessibility. Therefore, there is a strict necessity to support embedded software developers to identify and remediate the vulnerabilities and create resilient applications against such attacks. In this paper, we propose a hardware security vulnerability assessment based on fault injection of an embedded application. In our security assessment, we apply a fault injection attack by using our clock glitch generator on a critical medical IoT device. Furthermore, we analyze the potential risks of ignoring these attacks in this embedded application. The results will inform the embedded software developers of various security risks and the required steps to improve the security of similar MCU-based applications. Our hardware security assessment approach is easy to apply and can lead to secure embedded IoT applications against fault attacks.

Dai, Q., Shi, L..  2020.  A Game-Theoretic Analysis of Cyber Attack-Mitigation in Centralized Feeder Automation System. 2020 IEEE Power Energy Society General Meeting (PESGM). :1–5.
The intelligent electronic devices widely deployed across the distribution network are inevitably making the feeder automation (FA) system more vulnerable to cyber-attacks, which would lead to disastrous socio-economic impacts. This paper proposes a three-stage game-theoretic framework that the defender allocates limited security resources to minimize the economic impacts on FA system while the attacker deploys limited attack resources to maximize the corresponding impacts. Meanwhile, the probability of successful attack is calculated based on the Bayesian attack graph, and a fault-tolerant location technique for centralized FA system is elaborately considered during analysis. The proposed game-theoretic framework is converted into a two-level zero-sum game model and solved by the particle swarm optimization (PSO) combined with a generalized reduced gradient algorithm. Finally, the proposed model is validated on distribution network for RBTS bus 2.
2021-03-22
Xu, P., Chen, L., Jiang, Y., Sun, Q., Chen, H..  2020.  Research on Sensitivity Audit Scheme of Encrypted Data in Power Business. 2020 IEEE International Conference on Energy Internet (ICEI). :6–10.

With the rapid progress of informatization construction in power business, data resource has become the basic strategic resource of the power industry and innovative element in power production. The security protection of data in power business is particularly important in the informatization construction of power business. In order to implement data security protection, transparent encryption is one of the fifteen key technical standards in the Construction Guideline of the Standard Network Data Security System. However, data storage in the encrypted state is bound to affect the security audit of data to a certain extent. Based on this problem, this paper proposes a scheme to audit the sensitivity of the power business data under the protection of encryption to achieve an efficient sensitivity audit of ciphertext data with the premise of not revealing the decryption key or data information. Through a security demonstration, this paper fully proves that this solution is secure under the known plaintext attacks.

2021-03-17
Kushal, T. R. B., Gao, Z., Wang, J., Illindala, M. S..  2020.  Causal Chain of Time Delay Attack on Synchronous Generator Control. 2020 IEEE Power Energy Society General Meeting (PESGM). :1—5.

Wide integration of information and communication technology (ICT) in modern power grids has brought many benefits as well as the risk of cyber attacks. A critical step towards defending grid cyber security is to understand the cyber-physical causal chain, which describes the progression of intrusion in cyber-space leading to the formation of consequences on the physical power grid. In this paper, we develop an attack vector for a time delay attack at load frequency control in the power grid. Distinct from existing works, which are separately focused on cyber intrusion, grid response, or testbed validation, the proposed attack vector for the first time provides a full cyber-physical causal chain. It targets specific vulnerabilities in the protocols, performs a denial-of-service (DoS) attack, induces the delays in control loop, and destabilizes grid frequency. The proposed attack vector is proved in theory, presented as an attack tree, and validated in an experimental environment. The results will provide valuable insights to develop security measures and robust controls against time delay attacks.

2021-03-15
Shahkar, S., Khorasani, K..  2020.  A Resilient Control Against Time-Delay Switch and Denial of Service Cyber Attacks on Load Frequency Control of Distributed Power Systems. 2020 IEEE Conference on Control Technology and Applications (CCTA). :718—725.

A time-delay switch (TDS) cyber attack is a deliberate attempt by malicious adversaries aiming at destabilizing a power system by impeding the communication signals to/from the centralized controller from/to the network sensors and generating stations that participate in the load frequency control (LFC). A TDS cyber attack can be targeting the sensing loops (transmitting network measurements to the centralized controller) or the control signals dispatched from the centralized controller to the governor valves of the generating stations. A resilient TDS control strategy is proposed and developed in this work that thwarts network instabilities that are caused by delays in the sensing loops, and control commands, and guarantees normal operation of the LFC mechanism. This will be achieved by augmenting the telemetered control commands with locally generated feedback control laws (i.e., “decentralized” control commands) taking measurements that are available and accessible at the power generating stations (locally) independent from all the telemetered signals to/from the centralized controller. Our objective is to devise a controller that is capable of circumventing all types of TDS and DoS (Denial of Service) cyber attacks as well as a broad class of False Data Injection (FDI) cyber attacks.

2021-02-16
Siu, J. Y., Panda, S. Kumar.  2020.  A Specification-Based Detection for Attacks in the Multi-Area System. IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society. :1526—1526.
In the past decade, cyber-attack events on the power grid have proven to be sophisticated and advanced. These attacks led to severe consequences on the grid operation, such as equipment damage or power outages. Hence, it is more critical than ever to develop tools for security assessment and detection of anomalies in the cyber-physical grid. For an extensive power grid, it is complex to analyze the causes of frequency deviations. Besides, if the system is compromised, attackers can leverage on the frequency deviation to bypass existing protection measures of the grid. This paper aims to develop a novel specification-based method to detect False Data Injection Attacks (FDIAs) in the multi-area system. Firstly, we describe the implementation of a three-area system model. Next, we assess the risk and devise several intrusion scenarios. Specifically, we inject false data into the frequency measurement and Automatic Generation Control (AGC) signals. We then develop a rule-based method to detect anomalies at the system-level. Our simulation results proves that the proposed algorithm can detect FDIAs in the system.
2021-02-08
Liu, S., Kosuru, R., Mugombozi, C. F..  2020.  A Moving Target Approach for Securing Secondary Frequency Control in Microgrids. 2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). :1–6.
Microgrids' dependency on communication links exposes the control systems to cyber attack threats. In this work, instead of designing reactive defense approaches, a proacitve moving target defense mechanism is proposed for securing microgrid secondary frequency control from denial of service (DoS) attack. The sensor data is transmitted by following a Markov process, not in a deterministic way. This uncertainty will increase the difficulty for attacker's decision making and thus significantly reduce the attack space. As the system parameters are constantly changing, a gain scheduling based secondary frequency controller is designed to sustain the system performance. Case studies of a microgrid with four inverter-based DGs show the proposed moving target mechanism can enhance the resiliency of the microgrid control systems against DoS attacks.
2021-01-25
ManJiang, D., Kai, C., ZengXi, W., LiPeng, Z..  2020.  Design of a Cloud Storage Security Encryption Algorithm for Power Bidding System. 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). 1:1875–1879.
To solve the problem of poor security and performance caused by traditional encryption algorithm in the cloud data storage of power bidding system, we proposes a hybrid encryption method based on symmetric encryption and asymmetric encryption. In this method, firstly, the plaintext upload file is divided into several blocks according to the proportion, then the large file block is encrypted by symmetrical encryption algorithm AES to ensure the encryption performance, and then the small file block and AES key are encrypted by asymmetric encryption algorithm ECC to ensure the file encryption strength and the security of key transmission. Finally, the ciphertext file is generated and stored in the cloud storage environment to prevent sensitive files Pieces from being stolen and destroyed. The experimental results show that the hybrid encryption method can improve the anti-attack ability of cloud storage files, ensure the security of file storage, and have high efficiency of file upload and download.
Gracy, S., Milošević, J., Sandberg, H..  2020.  Actuator Security Index for Structured Systems. 2020 American Control Conference (ACC). :2993–2998.
Given a network with a set of vulnerable actuators (and sensors), the security index of an actuator equals the minimum number of sensors and actuators that needs to be compromised so as to conduct a perfectly undetectable attack using the said actuator. This paper deals with the problem of computing actuator security indices for discrete-time LTI network systems, using a structured systems framework. We show that the actuator security index is generic, that is for almost all realizations the actuator security index remains the same. We refer to such an index as generic security index (generic index) of an actuator. Given that the security index quantifies the vulnerability of a network, the generic index is quite valuable for large scale energy systems. Our second contribution is to provide graph-theoretic conditions for computing the generic index. The said conditions are in terms of existence of linkings on appropriately-defined directed (sub)graphs. Based on these conditions, we present an algorithm for computing the generic index.
2020-12-21
Cheng, Z., Chow, M.-Y..  2020.  An Augmented Bayesian Reputation Metric for Trustworthiness Evaluation in Consensus-based Distributed Microgrid Energy Management Systems with Energy Storage. 2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES). 1:215–220.
Consensus-based distributed microgrid energy management system is one of the most used distributed control strategies in the microgrid area. To improve its cybersecurity, the system needs to evaluate the trustworthiness of the participating agents in addition to the conventional cryptography efforts. This paper proposes a novel augmented reputation metric to evaluate the agents' trustworthiness in a distributed fashion. The proposed metric adopts a novel augmentation method to substantially improve the trust evaluation and attack detection performance under three typical difficult-to-detect attack patterns. The proposed metric is implemented and validated on a real-time HIL microgrid testbed.
2020-12-11
Han, Y., Zhang, W., Wei, J., Liu, X., Ye, S..  2019.  The Study and Application of Security Control Plan Incorporating Frequency Stability (SCPIFS) in CPS-Featured Interconnected Asynchronous Grids. 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). :349—354.

The CPS-featured modern asynchronous grids interconnected with HVDC tie-lines facing the hazards from bulk power imbalance shock. With the aid of cyber layer, the SCPIFS incorporates the frequency stability constrains is put forwarded. When there is bulk power imbalance caused by HVDC tie-lines block incident or unplanned loads increasing, the proposed SCPIFS ensures the safety and frequency stability of both grids at two terminals of the HVDC tie-line, also keeps the grids operate economically. To keep frequency stability, the controllable variables in security control strategy include loads, generators outputs and the power transferred in HVDC tie-lines. McCormick envelope method and ADMM are introduced to solve the proposed SCPIFS optimization model. Case studies of two-area benchmark system verify the safety and economical benefits of the SCPFS. HVDC tie-line transferred power can take the advantage of low cost generator resource of both sides utmost and avoid the load shedding via tuning the power transferred through the operating tie-lines, thus the operation of both connected asynchronous grids is within the limit of frequency stability domain.

2020-12-02
Scheffer, V., Ipach, H., Becker, C..  2019.  Distribution Grid State Assessment for Control Reserve Provision Using Boundary Load Flow. 2019 IEEE Milan PowerTech. :1—6.

With the increasing expansion of wind and solar power plants, these technologies will also have to contribute control reserve to guarantee frequency stability within the next couple of years. In order to maintain the security of supply at the same level in the future, it must be ensured that wind and solar power plants are able to feed in electricity into the distribution grid without bottlenecks when activated. The present work presents a grid state assessment, which takes into account the special features of the control reserve supply. The identification of a future grid state, which is necessary for an ex ante evaluation, poses the challenge of forecasting loads. The Boundary Load Flow method takes load uncertainties into account and is used to estimate a possible interval for all grid parameters. Grid congestions can thus be detected preventively and suppliers of control reserve can be approved or excluded. A validation in combination with an exemplary application shows the feasibility of the overall methodology.

2020-11-20
Efstathopoulos, G., Grammatikis, P. R., Sarigiannidis, P., Argyriou, V., Sarigiannidis, A., Stamatakis, K., Angelopoulos, M. K., Athanasopoulos, S. K..  2019.  Operational Data Based Intrusion Detection System for Smart Grid. 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). :1—6.

With the rapid progression of Information and Communication Technology (ICT) and especially of Internet of Things (IoT), the conventional electrical grid is transformed into a new intelligent paradigm, known as Smart Grid (SG). SG provides significant benefits both for utility companies and energy consumers such as the two-way communication (both electricity and information), distributed generation, remote monitoring, self-healing and pervasive control. However, at the same time, this dependence introduces new security challenges, since SG inherits the vulnerabilities of multiple heterogeneous, co-existing legacy and smart technologies, such as IoT and Industrial Control Systems (ICS). An effective countermeasure against the various cyberthreats in SG is the Intrusion Detection System (IDS), informing the operator timely about the possible cyberattacks and anomalies. In this paper, we provide an anomaly-based IDS especially designed for SG utilising operational data from a real power plant. In particular, many machine learning and deep learning models were deployed, introducing novel parameters and feature representations in a comparative study. The evaluation analysis demonstrated the efficacy of the proposed IDS and the improvement due to the suggested complex data representation.

Prasad, G., Huo, Y., Lampe, L., Leung, V. C. M..  2019.  Machine Learning Based Physical-Layer Intrusion Detection and Location for the Smart Grid. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1—6.
Security and privacy of smart grid communication data is crucial given the nature of the continuous bidirectional information exchange between the consumer and the utilities. Data security has conventionally been ensured using cryptographic techniques implemented at the upper layers of the network stack. However, it has been shown that security can be further enhanced using physical layer (PHY) methods. To aid and/or complement such PHY and upper layer techniques, in this paper, we propose a PHY design that can detect and locate not only an active intruder but also a passive eavesdropper in the network. Our method can either be used as a stand-alone solution or together with existing techniques to achieve improved smart grid data security. Our machine learning based solution intelligently and automatically detects and locates a possible intruder in the network by reusing power line transmission modems installed in the grid for communication purposes. Simulation results show that our cost-efficient design provides near ideal intruder detection rates and also estimates its location with a high degree of accuracy.
Lu, X., Guan, Z., Zhou, X., Du, X., Wu, L., Guizani, M..  2019.  A Secure and Efficient Renewable Energy Trading Scheme Based on Blockchain in Smart Grid. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :1839—1844.
Nowadays, with the diversification and decentralization of energy systems, the energy Internet makes it possible to interconnect distributed energy sources and consumers. In the energy trading market, the traditional centralized model relies entirely on trusted third parties. However, as the number of entities involved in the transactions grows and the forms of transactions diversify, the centralized model gradually exposes problems such as insufficient scalability, High energy consumption, and low processing efficiency. To address these challenges, we propose a secure and efficient energy renewable trading scheme based on blockchain. In our scheme, the electricity market trading model is divided into two levels, which can not only protect the privacy, but also achieve a green computing. In addition, in order to adapt to the relatively weak computing power of the underlying equipment in smart grid, we design a credibility-based equity proof mechanism to greatly improve the system availability. Compared with other similar distributed energy trading schemes, we prove the advantages of our scheme in terms of high operational efficiency and low computational overhead through experimental evaluations. Additionally, we conduct a detailed security analysis to demonstrate that our solution meets the security requirements.
Yogarathinam, A., Chaudhuri, N. R..  2019.  Wide-Area Damping Control Using Multiple DFIG-Based Wind Farms Under Stochastic Data Packet Dropouts. 2019 IEEE Power Energy Society General Meeting (PESGM). :1—1.
Data dropouts in communication network can have a significant impact on wide-area oscillation damping control of a smart power grid with large-scale deployment of distributed and networked phasor measurement units and wind energy resources. Remote feedback signals sent through communication channels encounter data dropout, which is represented by the Gilbert-Elliott model. An observer-driven reduced copy (ORC) approach is presented, which uses the knowledge of the nominal system dynamics during data dropouts to improve the damping performance where conventional feedback would suffer. An expression for the expectation of the bound on the error norm between the actual and the estimated states relating uncertainties in the cyber system due to data dropout and physical system due to change in operating conditions is also derived. The key contribution comes from the analytical derivation of the impact of coupling between the cyber and the physical layer on ORC performance. Monte Carlo simulation is performed to calculate the dispersion of the error bound. Nonlinear time-domain simulations demonstrate that the ORC produces significantly better performance compared to conventional feedback under higher data drop situations.
2020-11-16
Tamimi, A., Touhiduzzaman, M., Hahn, A..  2019.  Modeling and Analysis Cyber Threats in Power Systems Using Architecture Analysis Design Language (AADL). 2019 Resilience Week (RWS). 1:213–218.
The lack of strong cyber-physical modeling capabilities presents many challenges across the design, development, verification, and maintenance phases of a system [7]. Novel techniques for modeling the cyber-grid components, along with analysis and verification techniques, are imperative to the deployment of a resilient and robust power grid. Several works address False Data Injection (FDI) attacks to the power grid. However, most of them suffer from the lack of a model to investigate the effects of attacks. This paper proposed a cyber-physical model using Architecture Analysis & Design Language (AADL) [15] and power system information models to address different attacks in power systems.
2020-11-04
Liang, Y., He, D., Chen, D..  2019.  Poisoning Attack on Load Forecasting. 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). :1230—1235.

Short-term load forecasting systems for power grids have demonstrated high accuracy and have been widely employed for commercial use. However, classic load forecasting systems, which are based on statistical methods, are subject to vulnerability from training data poisoning. In this paper, we demonstrate a data poisoning strategy that effectively corrupts the forecasting model even in the presence of outlier detection. To the best of our knowledge, poisoning attack on short-term load forecasting with outlier detection has not been studied in previous works. Our method applies to several forecasting models, including the most widely-adapted and best-performing ones, such as multiple linear regression (MLR) and neural network (NN) models. Starting with the MLR model, we develop a novel closed-form solution to quickly estimate the new MLR model after a round of data poisoning without retraining. We then employ line search and simulated annealing to find the poisoning attack solution. Furthermore, we use the MLR attacking solution to generate a numerical solution for other models, such as NN. The effectiveness of our algorithm has been tested on the Global Energy Forecasting Competition (GEFCom2012) data set with the presence of outlier detection.

2020-10-14
Song, Yufei, Yu, Zongchao, Liu, Xuan, Tian, Jianwei, CHEN, Mu.  2019.  Isolation Forest based Detection for False Data Attacks in Power Systems. 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). :4170—4174.
Power systems become a primary target of cyber attacks because of the vulnerability of the integrated communication networks. An attacker is able to manipulate the integrity of real-time data by maliciously modifying the readings of meters transmitted to the control center. Moreover, it is demonstrated that such attack can escape the bad data detection in state estimation if the topology and network information of the entire power grid is known to the attacker. In this paper, we propose an isolation forest (IF) based detection algorithm as a countermeasure against false data attack (FDA). This method requires no tedious pre-training procedure to obtain the labels of outliers. In addition, comparing with other algorithms, the IF based detection method can find the outliers quickly. The performance of the proposed detection method is verified using the simulation results on the IEEE 118-bus system.
Khezrimotlagh, Darius, Khazaei, Javad, Asrari, Arash.  2019.  MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids. 2019 North American Power Symposium (NAPS). :1—7.
Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.
Trevizan, Rodrigo D., Ruben, Cody, Nagaraj, Keerthiraj, Ibukun, Layiwola L., Starke, Allen C., Bretas, Arturo S., McNair, Janise, Zare, Alina.  2019.  Data-driven Physics-based Solution for False Data Injection Diagnosis in Smart Grids. 2019 IEEE Power Energy Society General Meeting (PESGM). :1—5.
This paper presents a data-driven and physics-based method for detection of false data injection (FDI) in Smart Grids (SG). As the power grid transitions to the use of SG technology, it becomes more vulnerable to cyber-attacks like FDI. Current strategies for the detection of bad data in the grid rely on the physics based State Estimation (SE) process and statistical tests. This strategy is naturally vulnerable to undetected bad data as well as false positive scenarios, which means it can be exploited by an intelligent FDI attack. In order to enhance the robustness of bad data detection, the paper proposes the use of data-driven Machine Intelligence (MI) working together with current bad data detection via a combined Chi-squared test. Since MI learns over time and uses past data, it provides a different perspective on the data than the SE, which analyzes only the current data and relies on the physics based model of the system. This combined bad data detection strategy is tested on the IEEE 118 bus system.