Intrusion Detection for Smart Grid Communication Systems

Transformation of the traditional power grid into a smart grid hosts an array of vulnerabilities associated with communication networks. Furthermore, wireless mediums used throughout the smart grid promote an environment where Denial of Service (DoS) attacks are very effective. In wireless mediums, jamming and spoofing attack techniques diminish system operations thus affecting smart grid stability and posing an immediate threat to Confidentiality, Integrity, and Availability (CIA) of the smart grid. Intrusion detection systems (IDS) serve as a primary defense in mitigating network vulnerabilities. In IDS, signatures created from historical data are compared to incoming network traffic to identify abnormalities. In this thesis, intrusion detection algorithms are proposed for attack detection in smart grid networks by means of physical, data link, network, and session layer analysis. Irregularities in these layers provide insight to whether the network is experiencing genuine or malicious activity

Moving Target Defense Intrusion Detection System

The smart grid solution brings about significant improvement in reliability, performance, and manageability by integrating two-way communication technology into the current power grid. Added inter-connectivity enables consumers and energy suppliers to take advantage of convenience, dependability, and energy savings provided by real time energy management. However, the convergence of communication technology and energy systems creates a new realm of network security issues ranging from a larger attack surface to an abundance of sensitive information available to an intruder. Network stability is achieved by means of intrusion detection systems (IDS). An intrusion detection system monitors a network or system for malicious activity or policy violations. Conventional intrusion detection systems detect inconsistencies by analyzing and comparing network traffic with historic malicious signatures. If network traffic matches the malicious signature, the network is presumed compromised. Therefore, conventional intrusion detection system approach is static in nature. Though very effective, a significant drawback of static based IDS is the inability to preserve network stability in the presence of a cyber attack where no historical data is present. In order to resolve such a drawback, Moving Target Defense Intrusion Detection System (MTDIDS) is proposed to detect network anomalies. MTDIDS accomplishes stability by introducing entropy and the concept of planar keys to network operations. An increase in entropy correlates to a dynamic environment where static based attacks are ineffective. Additionally, MTDIDS compensates for a new era of attacks known as moving target attacks (MTA). MTA renders conventional IDS useless by randomizing attack vector components to evade detection. The entropic nature of MTDIDS combats MTA by significantly decreasing the likelihood of success. In essence, MTDIDS provides a viable solution to protect networks from historic and forthcoming attack vectors

Frequency Tunable Antennas for Smart Grid Communications

The transformation of the traditional power grid into a smart grid brings about significant improvement in terms of reliability, performance, and manageability. Furthermore, communication infrastructures represent the backbone of the smart grid’s home area networks, neighborhood area networks, and wide area networks. Existing wireless communication infrastructures such as 4G LTE, Wi-Fi, Zigbee, and Bluetooth are set to play dominant roles as they collectively serve as available mediums for transmission of data. As a result of the opportunistic spectrum created by the given mediums, bandwidths span across a large spectrum thus requiring smart devices to possess communication capabilities for several allocated frequencies. In standard communications, arrays of antennas are employed for signal detection across a differing frequency spectrum. Consequently, manufacturing costs, scalability, and efficiency are compromised. The study to be conducted will research frequency tunable antennas as a solution along with associated effects on antenna characteristics. Frequency tunable antennas provide an effective mean for detection of differing frequencies by way of a single antenna. Though there are six major types of frequency tuning techniques, only three, RF MEMS, PIN Diodes, and Varactors, belong to the electrical field. The listed components serve as switches to redistribute the surface currents and alter the antenna radiating structure topology and/or radiating edges. In regards to simulation, CST-Studio will be employed to simulate a frequency tunable antenna for analysis of radiation patterns, gain, necessary time for change in frequency, associated noise, etc. Additionally, numerical analysis is to be conducted by means of MATLAB. Frequency tunable antennas provide a viable solution for smart grid communications by reducing manufacturing costs for smart devices. Moreover, utilizing a single antenna to perform functions associated with an array of antennas produces an improvement in scalability, smart device connectivity, and power usage. An additional advantage is the realization of wireless power readings throughout the smart grid community. By studying frequency tunable antennas, significant advances in the fields of electrical engineering, telecommunications, and smart grid will be achieved