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Avula, Ramana R., Oechtering, Tobias J..  2020.  On Design of Optimal Smart Meter Privacy Control Strategy Against Adversarial Map Detection. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :5845—5849.
We study the optimal control problem of the maximum a posteriori (MAP) state sequence detection of an adversary using smart meter data. The privacy leakage is measured using the Bayesian risk and the privacy-enhancing control is achieved in real-time using an energy storage system. The control strategy is designed to minimize the expected performance of a non-causal adversary at each time instant. With a discrete-state Markov model, we study two detection problems: when the adversary is unaware or aware of the control. We show that the adversary in the former case can be controlled optimally. In the latter case, where the optimal control problem is shown to be non-convex, we propose an adaptive-grid approximation algorithm to obtain a sub-optimal strategy with reduced complexity. Although this work focuses on privacy in smart meters, it can be generalized to other sensor networks.
Pradhan, Ankit, R., Punith., Sethi, Kamalakanta, Bera, Padmalochan.  2020.  Smart Grid Data Security using Practical CP-ABE with Obfuscated Policy and Outsourcing Decryption. 2020 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA). :1–8.
Smart grid consists of multiple different entities related to various energy management systems which share fine-grained energy measurements among themselves in an optimal and reliable manner. Such delivery is achieved through intelligent transmission and distribution networks composed of various stakeholders like Phasor Measurement Units (PMUs), Master and Remote Terminal Units (MTU and RTU), Storage Centers and users in power utility departments subject to volatile changes in requirements. Hence, secure accessibility of data becomes vital in the context of efficient functioning of the smart grid. In this paper, we propose a practical attribute-based encryption scheme for securing data sharing and data access in Smart Grid architectures with the added advantage of obfuscating the access policy. This is aimed at preserving data privacy in the context of competing smart grid operators. We build our scheme on Linear Secret Sharing (LSS) Schemes for supporting any monotone access structures and thus enhancing the expressiveness of access policies. Lastly, we analyze the security, access policy privacy and collusion resistance properties of our cryptosystem and provide an efficiency comparison as well as experimental analysis using the Charm-Crypto framework to validate the proficiency of our proposed solution.
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.
Chowdary, S. S., Ghany, M. A. Abd El, Hofmann, K..  2020.  IoT based Wireless Energy Efficient Smart Metering System Using ZigBee in Smart Cities. 2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS). :1–4.
Electricity has become the primary need of human life. The emerging of IoT concept recently in our lives, has offered the chance to establish energy efficient smart devices, systems and cities. Due to the urging need for conserving energy, this paper proposes an IoT based wireless energy efficient smart metering systems for smart cities. A network of smart meters is achieved to deliver the energy consumption data to the Energy/Utility provider. The star and mesh topologies are used in creating the network of smart meters in order to increase the distance of coverage. The proposed system offers an easily operated application for users as well as a Website and database for electricity Supplier Company. The proposed system design has an accuracy level of 95% and it is about 35% lower cost than its peer in the global market. The proposed design reduced the power consumption by 25%.
Sarochar, J., Acharya, I., Riggs, H., Sundararajan, A., Wei, L., Olowu, T., Sarwat, A. I..  2019.  Synthesizing Energy Consumption Data Using a Mixture Density Network Integrated with Long Short Term Memory. 2019 IEEE Green Technologies Conference(GreenTech). :1—4.
Smart cities comprise multiple critical infrastructures, two of which are the power grid and communication networks, backed by centralized data analytics and storage. To effectively model the interdependencies between these infrastructures and enable a greater understanding of how communities respond to and impact them, large amounts of varied, real-world data on residential and commercial consumer energy consumption, load patterns, and associated human behavioral impacts are required. The dissemination of such data to the research communities is, however, largely restricted because of security and privacy concerns. This paper creates an opportunity for the development and dissemination of synthetic energy consumption data which is inherently anonymous but holds similarities to the properties of real data. This paper explores a framework using mixture density network (MDN) model integrated with a multi-layered Long Short-Term Memory (LSTM) network which shows promise in this area of research. The model is trained using an initial sample recorded from residential smart meters in the state of Florida, and is used to generate fully synthetic energy consumption data. The synthesized data will be made publicly available for interested users.
Semwal, S., Badoni, M., Saxena, N..  2019.  Smart Meters for Domestic Consumers: Innovative Methods for Identifying Appliances using NIALM. 2019 Women Institute of Technology Conference on Electrical and Computer Engineering (WITCON ECE). :81—90.
A country drives by their people and the electricity energy, the availability of the electricity power reflects the strength of that country. All most everything depends on the electricity energy, So it is become very important that we use the available energy very efficiently, and here the energy management come in the picture and Non Intrusive appliance Load monitoring (NIALM) is the part of energy management, in which the energy consumption by the particular load is monitored without any intrusion of wire/circuit. In literature, NIALM has been discussed as a monitoring process for conservation of energy using single point sensing (SPS) for extraction of aggregate signal of the appliances' features, ignoring the second function of demand response (DR) assuming that it would be manual or sensor-based. This assumption is not implementable in developing countries like India, because of requirement of extra cost of sensors, and privacy concerns. Surprisingly, despite decades of research on NIALM, none of the suggested procedures has resulted in commercial application. This paper highlights the causes behind non- commercialization, and proposes a viable and easy solution worthy of commercial exploitation both for monitoring and DR management for outage reduction in respect of Indian domestic consumers. Using a approach of multi point sensing (MPS), combined with Independent Component Analysis (ICA), experiments has been done in laboratory environment and CPWD specification has been followed.
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.

Romdhane, R. B., Hammami, H., Hamdi, M., Kim, T..  2019.  At the cross roads of lattice-based and homomorphic encryption to secure data aggregation in smart grid. 2019 15th International Wireless Communications Mobile Computing Conference (IWCMC). :1067—1072.

Various research efforts have focused on the problem of customer privacy protection in the smart grid arising from the large deployment of smart energy meters. In fact, the deployed smart meters distribute accurate profiles of home energy use, which can reflect the consumers' behaviour. This paper proposes a privacy-preserving lattice-based homomorphic aggregation scheme. In this approach, the smart household appliances perform the data aggregation while the smart meter works as relay node. Its role is to authenticate the exchanged messages between the home area network appliances and the related gateway. Security analysis show that our scheme guarantees consumer privacy and messages confidentiality and integrity in addition to its robustness against several attacks. Experimental results demonstrate the efficiency of our proposed approach in terms of communication complexity.

Antoniadis, I. I., Chatzidimitriou, K. C., Symeonidis, A. L..  2019.  Security and Privacy for Smart Meters: A Data-Driven Mapping Study. 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). :1—5.
Smart metering systems have been gaining popularity as a vital part of the general smart grid paradigm. Naturally, as new technologies arise to cover this emerging field, so do security and privacy related issues regarding the energy consumer's personal data. These challenges impose the need for the development of new methods through a better understanding of the state-of-the-art. This paper aims at identifying the main categories of security and privacy techniques utilized in smart metering systems from a three-point perspective: i) a field research survey, ii) EU initiatives and findings towards the same direction and iii) a data-driven analysis of the state-of-the-art and the identification of its main topics (or themes) using topic modeling techniques. Detailed quantitative results of this analysis, such as semantic interpretation of the identified topics and a graph representation of the topic trends over time, are presented.
Chin, J., Zufferey, T., Shyti, E., Hug, G..  2019.  Load Forecasting of Privacy-Aware Consumers. 2019 IEEE Milan PowerTech. :1—6.

The roll-out of smart meters (SMs) in the electric grid has enabled data-driven grid management and planning techniques. SM data can be used together with short-term load forecasts (STLFs) to overcome polling frequency constraints for better grid management. However, the use of SMs that report consumption data at high spatial and temporal resolutions entails consumer privacy risks, motivating work in protecting consumer privacy. The impact of privacy protection schemes on STLF accuracy is not well studied, especially for smaller aggregations of consumers, whose load profiles are subject to more volatility and are, thus, harder to predict. In this paper, we analyse the impact of two user demand shaping privacy protection schemes, model-distribution predictive control (MDPC) and load-levelling, on STLF accuracy. Support vector regression is used to predict the load profiles at different consumer aggregation levels. Results indicate that, while the MDPC algorithm marginally affects forecast accuracy for smaller consumer aggregations, this diminishes at higher aggregation levels. More importantly, the load-levelling scheme significantly improves STLF accuracy as it smoothens out the grid visible consumer load profile.

Zhou, Xingyu, Li, Yi, Barreto, Carlos A., Li, Jiani, Volgyesi, Peter, Neema, Himanshu, Koutsoukos, Xenofon.  2019.  Evaluating Resilience of Grid Load Predictions under Stealthy Adversarial Attacks. 2019 Resilience Week (RWS). 1:206–212.
Recent advances in machine learning enable wider applications of prediction models in cyber-physical systems. Smart grids are increasingly using distributed sensor settings for distributed sensor fusion and information processing. Load forecasting systems use these sensors to predict future loads to incorporate into dynamic pricing of power and grid maintenance. However, these inference predictors are highly complex and thus vulnerable to adversarial attacks. Moreover, the adversarial attacks are synthetic norm-bounded modifications to a limited number of sensors that can greatly affect the accuracy of the overall predictor. It can be much cheaper and effective to incorporate elements of security and resilience at the earliest stages of design. In this paper, we demonstrate how to analyze the security and resilience of learning-based prediction models in power distribution networks by utilizing a domain-specific deep-learning and testing framework. This framework is developed using DeepForge and enables rapid design and analysis of attack scenarios against distributed smart meters in a power distribution network. It runs the attack simulations in the cloud backend. In addition to the predictor model, we have integrated an anomaly detector to detect adversarial attacks targeting the predictor. We formulate the stealthy adversarial attacks as an optimization problem to maximize prediction loss while minimizing the required perturbations. Under the worst-case setting, where the attacker has full knowledge of both the predictor and the detector, an iterative attack method has been developed to solve for the adversarial perturbation. We demonstrate the framework capabilities using a GridLAB-D based power distribution network model and show how stealthy adversarial attacks can affect smart grid prediction systems even with a partial control of network.
Patsonakis, Christos, Terzi, Sofia, Moschos, Ioannis, Ioannidis, Dimosthenis, Votis, Konstantinos, Tzovaras, Dimitrios.  2019.  Permissioned Blockchains and Virtual Nodes for Reinforcing Trust Between Aggregators and Prosumers in Energy Demand Response Scenarios. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I CPS Europe). :1–6.
The advancement and penetration of distributed energy resources (DERs) and renewable energy sources (RES) are transforming legacy energy systems in an attempt to reduce carbon emissions and energy waste. Demand Response (DR) has been identified as a key enabler of integrating these, and other, Smart Grid technologies, while, simultaneously, ensuring grid stability and secure energy supply. The massive deployment of smart meters, IoT devices and DERs dictate the need to move to decentralized, or even localized, DR schemes in the face of the increased scale and complexity of monitoring and coordinating the actors and devices in modern smart grids. Furthermore, there is an inherent need to guarantee interoperability, due to the vast number of, e.g., hardware and software stakeholders, and, more importantly, promote trust and incentivize the participation of customers in DR schemes, if they are to be successfully deployed.In this work, we illustrate the design of an energy system that addresses all of the roadblocks that hinder the large scale deployment of DR services. Our DR framework incorporates modern Smart Grid technologies, such as fog-enabled and IoT devices, DERs and RES to, among others, automate asset handling and various time-consuming workflows. To guarantee interoperability, our system employs OpenADR, which standardizes the communication of DR signals among energy stakeholders. Our approach acknowledges the need for decentralization and employs blockchains and smart contracts to deliver a secure, privacy-preserving, tamper-resistant, auditable and reliable DR framework. Blockchains provide the infrastructure to design innovative DR schemes and incentivize active consumer participation as their aforementioned properties promote transparency and trust. In addition, we harness the power of smart contracts which allows us to design and implement fully automated contractual agreements both among involved stakeholders, as well as on a machine-to-machine basis. Smart contracts are digital agents that "live" in the blockchain and can encode, execute and enforce arbitrary agreements. To illustrate the potential and effectiveness of our smart contract-based DR framework, we present a case study that describes the exchange of DR signals and the autonomous instantiation of smart contracts among involved participants to mediate and monitor transactions, enforce contractual clauses, regulate energy supply and handle payments/penalties.
Arrieta, Miguel, Esnaola, Iñaki, Effros, Michelle.  2019.  Universal Privacy Guarantees for Smart Meters. 2019 IEEE International Symposium on Information Theory (ISIT). :2154–2158.
Smart meters enable improvements in electricity distribution system efficiency at some cost in customer privacy. Users with home batteries can mitigate this privacy loss by applying charging policies that mask their underlying energy use. A battery charging policy is proposed and shown to provide universal privacy guarantees subject to a constraint on energy cost. The guarantee bounds our strategy's maximal information leakage from the user to the utility provider under general stochastic models of user energy consumption. The policy construction adapts coding strategies for non-probabilistic permuting channels to this privacy problem.
Zhang, Tianchen, Zhang, Taimin, Ji, Xiaoyu, Xu, Wenyuan.  2019.  Cuckoo-RPL: Cuckoo Filter based RPL for Defending AMI Network from Blackhole Attacks. 2019 Chinese Control Conference (CCC). :8920—8925.

Advanced metering infrastructure (AMI) is a key component in the smart grid. Transmitting data robustly and reliably between the tremendous smart meters in the AMI is one of the most crucial tasks for providing various services in smart grid. Among the many efforts for designing practical routing protocols for the AMI, the Routing Protocol for Low-Power and Lossy Networks (RPL) proposed by the IETF ROLL working group is considered the most consolidated candidate. Resent research has shown cyber attacks such as blackhole attack and version number attack can seriously damage the performance of the network implementing RPL. The main reason that RPL is vulnerable to these kinds of attacks is the lack an authentication mechanism. In this paper, we study the impact of blackhole attacks on the performance of the AMI network and proposed a new blackhole attack that can bypass the existing defense mechanism. Then, we propose a cuckoo filter based RPL to defend the AMI network from blackhole attacks. We also give the security analysis of the proposed method.

Xie, Yuanpeng, Jiang, Yixin, Liao, Runfa, Wen, Hong, Meng, Jiaxiao, Guo, Xiaobin, Xu, Aidong, Guan, Zewu.  2015.  User Privacy Protection for Cloud Computing Based Smart Grid. 2015 IEEE/CIC International Conference on Communications in China - Workshops (CIC/ICCC). :7–11.

The smart grid aims to improve the efficiency, reliability and safety of the electric system via modern communication system, it's necessary to utilize cloud computing to process and store the data. In fact, it's a promising paradigm to integrate smart grid into cloud computing. However, access to cloud computing system also brings data security issues. This paper focuses on the protection of user privacy in smart meter system based on data combination privacy and trusted third party. The paper demonstrates the security issues for smart grid communication system and cloud computing respectively, and illustrates the security issues for the integration. And we introduce data chunk storage and chunk relationship confusion to protect user privacy. We also propose a chunk information list system for inserting and searching data.

Richardson, Christopher, Race, Nicholas, Smith, Paul.  2016.  A Privacy Preserving Approach to Energy Theft Detection in Smart Grids. 2016 IEEE International Smart Cities Conference (ISC2). :1–4.

A major challenge for utilities is energy theft, wherein malicious actors steal energy for financial gain. One such form of theft in the smart grid is the fraudulent amplification of energy generation measurements from DERs, such as photo-voltaics. It is important to detect this form of malicious activity, but in a way that ensures the privacy of customers. Not considering privacy aspects could result in a backlash from customers and a heavily curtailed deployment of services, for example. In this short paper, we present a novel privacy-preserving approach to the detection of manipulated DER generation measurements.

Niu, Yukun, Tan, Xiaobin, Zhou, Zifei, Zheng, Jiangyu, Zhu, Jin.  2013.  Privacy Protection Scheme in Smart Grid Using Rechargeable Battery. Proceedings of the 32nd Chinese Control Conference. :8825–8830.

It can get the user's privacy and home energy use information by analyzing the user's electrical load information in smart grid, and this is an area of concern. A rechargeable battery may be used in the home network to protect user's privacy. In this paper, the battery can neither charge nor discharge, and the power of battery is adjustable, at the same time, we model the real user's electrical load information and the battery power information and the recorded electrical power of smart meters which are processed with discrete way. Then we put forward a heuristic algorithm which can make the rate of information leakage less than existing solutions. We use statistical methods to protect user's privacy, the theoretical analysis and the examples show that our solution makes the scene design more reasonable and is more effective than existing solutions to avoid the leakage of the privacy.

Neureiter, Christian, Eibl, Günther, Veichtlbauer, Armin, Engel, Dominik.  2013.  Towards a Framework for Engineering Smart-Grid-Specific Privacy Requirements. IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society. :4803–4808.

Privacy has become a critical topic in the engineering of electric systems. This work proposes an approach for smart-grid-specific privacy requirements engineering by extending previous general privacy requirements engineering frameworks. The proposed extension goes one step further by focusing on privacy in the smart grid. An alignment of smart grid privacy requirements, dependability issues and privacy requirements engineering methods is presented. Starting from this alignment a Threat Tree Analysis is performed to obtain a first set of generic, high level privacy requirements. This set is formulated mostly on the data instead of the information level and provides the basis for further project-specific refinement.

Hiller, Jens, Komanns, Karsten, Dahlmanns, Markus, Wehrle, Klaus.  2019.  Regaining Insight and Control on SMGW-based Secure Communication in Smart Grids. 2019 AEIT International Annual Conference (AEIT). :1–6.
Smart Grids require extensive communication to enable safe and stable energy supply in the age of decentralized and dynamic energy production and consumption. To protect the communication in this critical infrastructure, public authorities mandate smart meter gateways (SMGWs) to be in control of the communication security. To this end, the SMGW intercepts all inbound and outbound communication of its premise, e.g., a factory or smart home, and forwards it on secure channels that the SMGW established itself. However, using the SMGW as proxy, local devices can neither review the security of these remote connections established by the SMGW nor enforce higher security guarantees than established by the all in one configuration of the SMGW which does not allow for use case-specific security settings. We present mechanisms that enable local devices to regain this insight and control over the full connection, i.e., up to the final receiver, while retaining the SMGW's ability to ensure a suitable security level. Our evaluation shows modest computation and transmission overheads for this increased security in the critical smart grid infrastructure.
Kumar, Sanjeev, Kumar, Harsh, Gunnam, Ganesh Reddy.  2019.  Security Integrity of Data Collection from Smart Electric Meter under a Cyber Attack. 2019 2nd International Conference on Data Intelligence and Security (ICDIS). :9–13.
Cyber security has been a top concern for electric power companies deploying smart meters and smart grid technology. Despite the well-known advantages of smart grid technology and the smart meters, it is not yet very clear how and to what extent, the Cyber attacks can hamper the operation of the smart meters, and remote data collections regarding the power usage from the customer sites. To understand these questions, we conducted experiments in a controlled lab environment of our cyber security lab to test a commercial grade smart meter. In this paper, we present results of our investigation for a commercial grade smart meter and measure the operation integrity of the smart meter under cyber-attack conditions.
Ganguly, Pallab, Nasipuri, Mita, Dutta, Sourav.  2019.  Challenges of the Existing Security Measures Deployed in the Smart Grid Framework. 2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE). :1–5.
Due to the rise of huge population in mankind and the large variety of upcoming utilization of power, the energy requirement has substantially increased. Smart Grid is a very important part of the Smart Cities initiative and is one of the crucial components in distribution and reconciliation of energy. Security of the smart grid infrastructure, which is an integral part of the smart grid framework, intended at transitioning the conventional power grid system into a robust, reliable, adaptable and intelligent energy utility, is an impending problem that needs to be arrested quickly. With the increasingly intensifying integration of smart devices in the smart grid infrastructure with other interconnected applications and the communication backbone is compelling both the energy users and the energy utilities to thoroughly look into the privacy and security issues of the smart grid. In this paper, we present challenges of the existing security mechanisms deployed in the smart grid framework and we tried to bring forward the unresolved problems that would highlight the security aspects of Smart Grid as a challenging area of research and development in the future.
Benmalek, Mourad, Challal, Yacine, Derhab, Abdelouahid.  2019.  An Improved Key Graph Based Key Management Scheme for Smart Grid AMI Systems. 2019 IEEE Wireless Communications and Networking Conference (WCNC). :1–6.

In this paper, we focus on versatile and scalable key management for Advanced Metering Infrastructure (AMI) in Smart Grid (SG). We show that a recently proposed key graph based scheme for AMI systems (VerSAMI) suffers from efficiency flaws in its broadcast key management protocol. Then, we propose a new key management scheme (iVerSAMI) by modifying VerSAMI's key graph structure and proposing a new broadcast key update process. We analyze security and performance of the proposed broadcast key management in details to show that iVerSAMI is secure and efficient in terms of storage and communication overheads.

Radhakrishnan, Vijayanand, Durairaj, Devaraj, Balasubramanian, Kannapiran, Kamatchi, Kartheeban.  2019.  Development Of A Novel Security Scheme Using DNA Biocryptography For Smart Meter Data Communication. 2019 3rd International Conference on Computing and Communications Technologies (ICCCT). :237-244.

Data security is a major requirement of smart meter communication to control server through Advanced Metering infrastructure. Easy access of smart meters and multi-faceted nature of AMI communication network are the main reasons of smart meter facing large number of attacks. The different topology, bandwidth and heterogeneity in communication network prevent the existing security mechanisms in satisfying the security requirements of smart meter. Hence, advanced security mechanisms are essential to encrypt smart meter data before transmitting to control server. The emerging biocryptography technique has several advantages over existing techniques and is most suitable for providing security to communication of low processing devices like smart meter. In this paper, a lightweight encryption scheme using DNA sequence with suitable key management scheme is proposed for secure communication of smart meter in an efficient way. The proposed 2-phase DNA cryptography provides confidentiality and integrity to transmitted data and the authentication of keys is attained by exchanging through Diffie Hellman scheme. The strength of proposed encryption scheme is analyzed and its efficiency is evaluated by simulating an AMI communication network using Simulink/Matlab. Comparison of simulation results with various techniques show that the proposed scheme is suitable for secure communication of smart meter data.

Sahu, Abhijeet, Goulart, Ana.  2019.  Implementation of a C-UNB Module for NS-3 and Validation for DLMS-COSEM Application Layer Protocol. 2019 IEEE ComSoc International Communications Quality and Reliability Workshop (CQR). :1-6.

The number of sensors and embedded devices in an urban area can be on the order of thousands. New low-power wide area (LPWA) wireless network technologies have been proposed to support this large number of asynchronous, low-bandwidth devices. Among them, the Cooperative UltraNarrowband (C-UNB) is a clean-slate cellular network technology to connect these devices to a remote site or data collection server. C-UNB employs small bandwidth channels, and a lightweight random access protocol. In this paper, a new application is investigated - the use of C-UNB wireless networks to support the Advanced Metering Infrastructure (AMI), in order to facilitate the communication between smart meters and utilities. To this end, we adapted a mathematical model for C-UNB, and implemented a network simulation module in NS-3 to represent C-UNB's physical and medium access control layer. For the application layer, we implemented the DLMS-COSEM protocol, or Device Language Message Specification - Companion Specification for Energy Metering. Details of the simulation module are presented and we conclude that it supports the results of the mathematical model.

Ying, Huan, Zhang, Yanmiao, Han, Lifang, Cheng, Yushi, Li, Jiyuan, Ji, Xiaoyu, Xu, Wenyuan.  2019.  Detecting Buffer-Overflow Vulnerabilities in Smart Grid Devices via Automatic Static Analysis. 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). :813-817.

As a modern power transmission network, smart grid connects plenty of terminal devices. However, along with the growth of devices are the security threats. Different from the previous separated environment, an adversary nowadays can destroy the power system by attacking these devices. Therefore, it's critical to ensure the security and safety of terminal devices. To achieve this goal, detecting the pre-existing vulnerabilities of the device program and enhance the terminal security, are of great importance and necessity. In this paper, we propose a novel approach that detects existing buffer-overflow vulnerabilities of terminal devices via automatic static analysis (ASA). We utilize the static analysis to extract the device program information and build corresponding program models. By further matching the generated program model with pre-defined vulnerability patterns, we achieve vulnerability detection and error reporting. The evaluation results demonstrate that our method can effectively detect buffer-overflow vulnerabilities of smart terminals with a high accuracy and a low false positive rate.