Chandra Bajracharya

Detection of False Data Injection Attacks in Smart Grid Communication Systems

The transformation of traditional energy networks to smart grids can assist in revolutionizing the energy industry in terms of reliability, performance and manageability. However, increased connectivity of power grid assets for bidirectional communications presents severe security vulnerabilities. In this letter, we investigate Chi-square detector and cosine similarity matching approaches for attack detection in smart grids where Kalman filter estimation is used to measure any deviation from actual measurements. The cosine similarity matching approach is found to be robust for detecting false data injection attacks as well as other attacks in the smart grids. Once the attack is detected, system can take preventive action and alarm the manager to take preventative action to limit the risk. Numerical results obtained from simulations corroborate our theoretical analysis.

Cyber security for smart grid systems: Status, challenges and perspectives

The transformation of traditional energy networks to smart grids revolutionizes the energy industry in terms of reliability, performance, and manageability by providing bi-directional communications to operate, monitor, and control power flow and measurements. However, communication networks in smart grid bring increased connectivity with increased severe security vulnerabilities and challenges. Smart grid can be a prime target for cyber terrorism because of its critical nature. As a result, smart grid security is already getting a lot of attention from governments, energy industries, and consumers. There have been several research efforts for securing smart grid systems in academia, government and industries. This article provides a comprehensive study of challenges in smart grid security, which we concentrate on the problems and proposed solutions. Then, we outline current state of the research and future perspectives.With this article, readers can have a more thorough understanding of smart grid security and the research trends in this topic.

Towards intelligent transportation Cyber-Physical Systems: Real-time computing and communications perspectives

Traffic accidents and congestion problems continue to worsen worldwide. Because of vast number of vehicles manufactured and sold every year transportation sector is significantly stressed, leading to more accidents and fatalities, and adverse environmental and economic impact. Efforts across the world for Smart Transportation Cyber Physical Systems (CPS) are aimed at addressing a range of problems including reducing traffic accidents, decreasing congestion, reducing fuel consumption, reducing time spent on traffic jams, and improve transportation safety. Thus, smart transportation CPS is expected to contribute a main role in the design and development of intelligent transportation systems. The advances in embedded systems, wireless communications and sensor networks provides the opportunities to bridge the physical components and processes with the cyber world that leading to a Cyber Physical Systems (CPS). Feedback for control through wireless communication in transportation CPS is one of the major components for both safety and infotainment applications where vehicles exchange information using vehicle-to-vehicle (V2V) through vehicular ad hoc network (VANET) and/or vehicle-to-roadside (V2R) communications. For wireless communication IEEE has 802.11p standard for Dedicated Short Range Communication (DSRC) for Wireless Access for Vehicular Environment (WAVE). In this paper, we present how different parameters (e.g., sensing time, association time, number for vehicles, relative speed of vehicles, overlap transmission range, etc.) affect communication in smart transportation CPS. Furthermore, we also present driving components, current trends, challenges, and future directions for transportation CPS.

Simulation Study of Delivery of Subnanosecond Pulses to Biological Tissues With an Impulse Radiating Antenna

We have numerically studied the delivery of subnanosecond pulsed radiation to biological tissues for bioelectric applications. The antenna fed by 200 ps pulses uses an elliptical reflector in conjunction with a dielectric lens. Two numerical targets were studied: one was a hemispherical tissue with a resistivity of 0.3-1 S/m and a relative permittivity of 9-70 and the other was a realistic human head model (HUGO). The electromagnetic simulation shows that despite tissue heterogeneity of the human head, the electric field converges to a spot 8 cm in depth and the spot volume is approximately 1 cm × 2 cm × 1 cm in both cases when using only the reflector and a lens as an addition. Rather than increasing as it approaches the converging point, the electric field decreases strongly with distance from the skin to the converging point due to tissue resistive loss. The electric field distribution, however, can be reversed by making the dielectric lens lossy with the two innermost layers being partially resistive. The lossy lens causes an attenuation of the electric field near the axis, but the electric field generated by the waves which pass the lens at a wider angles compensate for this loss. A local maximum electric field in a deeper region of the tissue may form with the lossy lens. The study shows that it is possible to generate the desired electric field distribution in the complex biological target by modifying the dielectric properties of the lens used in conjunction with the reflector antenna.

Evaluating Secrecy Outage of Physical Layer Security in Large-Scale MIMO Wireless Communications for Cyber-Physical Systems

Large-scale multiple input multiple output (MIMO) wireless system is regarded as a solution to provide high speed connection for exponentially increasing wireless subscriptions for emerging cyber-physical systems (CPSs) and Internet of Things. In order to realize its full potential, there are several challenges to be addressed to achieve high secrecy rate or data rate. In this paper, we analyze outage probability for secrecy rate in MIMO wireless systems in the presence of eavesdroppers and jammers for CPS devices. Our proposed approach takes into account the impact of jammers while finding the best response to minimize the jamming/interfering effect (or to enhance the secrecy rate) and the impact of eavesdropper in secrecy rates of the users. We present formal analysis for secrecy outage probability and interception probability considering Rayleigh fading scenario. The performance is evaluated by using numerical results obtained from Monte Carlo simulations. Numerical results indicate that the system performance is improved significantly when the users adapt their transmit vectors based on their observed interference values. Furthermore, the secrecy outage probability increases with power of jammer and the secrecy capacity decreases when jammer power increases. We observed that the proposed approach outperforms the other existing approaches.

nROAR: Near Real-Time Opportunistic Spectrum Access and Management in Cloud-Based Database-Driven Cognitive Radio Networks

Cognitive radio network with spectrum sensing to find idle channels and access them opportunistically is regarded as an emerging technology to deal with spectrum scarcity caused by exclusive licensing to primary systems. Simulation-based studies loose practical relevance due to assumptions and usage of simple models for defining transmission regions, multi-path propagation, and traffic intensity. In this paper, we present an experimental study for near real-time spectrum sensing and opportunistic spectrum access in database-driven cognitive radio networks (nROAR) using national instrument USRP devices in wide-band regime. We present numerical results for evaluating spectrum sensing using adaptive threshold-based joint energy and bandwidth detection. Furthermore, we evaluate the dynamic spectrum access using database-driven quorum-based rendezvous for opportunistic access for admitted unlicensed secondary users in diverse wireless bands. The proposed nROAR architecture addresses challenges related to providing spectrum access which require fast processing of a large number of spectrum-sensing measurements across diverse wireless bands, geography, and time.

Enhancing connectivity for communication and control in Unmanned Aerial Vehicle networks

Wireless connectivity for communication and control in Unmanned Aerial Vehicles (UAVs) networks is very critical to accomplish an assigned task such as monitoring a given area. Because of dynamic mobility of UAVs, robust adaptive wireless connectivity for UAVs is crucial. In this paper, we analyze the connectivity for UAV networks that is based on density of UAVs, velocity of UAVs, angle of arrival, and transmission range used by UAVs. We evaluate the performance of the proposed approach using numerical results obtained from simulations.

Software Defined networking for reducing energy consumption and carbon emission

With the exponential growth of the internet use, many organizations use vast amount of energy/power to operate and cool their network infrastructures and thus produce significant amount of carbon waste. The main focus of this research is to design OpenFlow based networks that will result in high speed computer networks and dramatic reductions of energy consumption and carbon emission. Note that optimizing a physical network requires tedious time spent manually debugging hardware, by manipulating a virtual network one may add and remove hosts with the click of a mouse. Mininet virtualization software allows the user to carry out what would normally be tedious processes in the matter of minutes. We also present steps toward converting a typical network set-up into an OpenFlow controlled Software Defined Network (SDN); to reduce the power consumption used by the network. Mininet is useful in visually representing a physical network to optimize power consumption using Software Defined Network.

Channel and power adaptation for cognitive radios in multiuser OFDM systems

In this paper, we investigate joint power and channel allocation problem for the orthogonal frequency-division multiplexing (OFDM) based multi-user cognitive radio systems with quality-of-service (QoS) in terms of signal-to-interference-plus-noise ratio (SINR) and proportional rate constraints. The QoS requirement of each cognitive radio user imposed by its minimum SINR and interference introduced by unlicensed secondary users to primary users make power and channel allocation problem more complex. We present a formal analysis for a proposed approach and illustrate the approach with numerical results obtained from simulations.

Dynamic spectrum access enabled home area networks for smart grid communications

In this paper, we investigate the dynamic spectrum access for home area network in smart grid communications where home appliances access RF spectrum opportunistically. We evaluate the proposed approach through simulations and the numerical results show that the proposed dynamic spectrum access-based smart grid communication outperforms the static spectrum access-based smart grid communications. Smart grid is the transformation of current power grid system through the integration of advanced information technology and communication technology with power system grid. The choice of communication technology for smart grid is highly critical to provide secure, reliable and efficient information transfer between the smart grid components. However, because of dynamic topology changes, connectivity problems, interference and fading issues, and delay requirements, current information and communication infrastructures and standards are incapable of meeting the strict requirements of smart grid technology. The dynamic spectrum access capability of cognitive radio networks is a promising technology that can be used to reduce the communication expenses and improve reliability by improving spectrum utilisation in smart grids.