Wireless Sensor Network Based Smart Grid Communications: Cyber Attacks, Intrusion Detection System and Topology Control
1.1. Home Area Network
1.2. Neighborhood Area Network
1.3. Wide Area Network
2. Application of Wireless Sensor Networks in Smart Grid
3. Challenges of Wireless Sensor Networks in Smart Grid Applications
4. Communication Standards for Wireless Sensor Networks
4.3. Wireless Fidelity or Wireless local area network
5. Security Issues and Cyber Attacks in Wireless Sensor Networks
- Device Constraints: WSN nodes have very limited storage, processing and computational capabilities. They have limited power as they are battery operated.
- Communication Constraints: WSNs communicate using radio transmissions and most of them use unlicensed ISM band which is used for many other applications. Co-existence of various wireless standards is a major challenge for secured communication.
5.1. Attacks Based on Location of an Intruder
5.1.1. External Attack
5.1.2. Internal Attack
5.2. Attack Based on Access Level of an Intruder
5.3. Attacks on Various Network Layers
5.3.1. Denial of Service Attack
5.3.2. Misdirection Attack
5.3.3. Selective Forwarding
5.3.4. Sink Hole Attack
5.3.5. Sybil Attack
5.3.6. Wormhole Attack
5.3.7. Hello Flood Attack
6. Intrusion Detection System
- Sensor: It collects statistics from the system being monitored.
- Detector: It analyzes collected data to identify intrusions.
- Information Base: It supports the detector by providing attack signatures.
- Response Manager: It manages the responses to the cyber-attacks.
6.1. Anomaly Detection
- Node Anomaly: This types of anomalies can be detected during failure of WSN node or power problems. Failure of solar panel, or fluctuations in power of different components can cause this type of anomaly. Node anomalies can be due to hardware or software issues in the WSN nodes .
- Network Anomaly: Unexpected fluctuations in the signal strength and connection problems can be used to detect network anomaly. Complete loss of connectivity or episodic connectivity can be used to detect intrusions in the network.
- Data Anomaly: An intrusion attempt can be detected from chaotic or disordered data communication.
6.2. Misuse Detection
6.3. Hybrid Detection
7. Topology Control
7.1. Random Key Predistribution Scheme
7.1.1. Eschenauer-Gligor Random Key Predistribution Scheme (EG Scheme)
7.1.2. s-Composite Random Key Predistribution Scheme
7.2. Link Constraint Models
7.2.1. Full Visibility Model
7.2.2. On-Off Channel Model
7.2.3. Disk Model
Conflicts of Interest
|AES||Advanced Encryption Standard|
|AMI||Advanced Metering Infrastructure|
|DOS||Denial Of Service|
|ETP||European Technology Platform|
|HAN||Home Area Network|
|IDS||Intrusion Detection System|
|IDPS||Intrusion Detection and Prevention System|
|IEC||International Electrotechnical Commission|
|IEEE||Institute of Electrical and Electronics Engineers|
|ISM||Industrial, Scientific and Medical|
|MANET||Mobile and Adhoc NETwork|
|MIMO||Multiple Input Multiple Output|
|NAN||Neighborhood Area Network|
|NIST||National Institute of Standards and Technology|
|OFDM||Orthogonal Frequency Division Multiplexing|
|PHEV||Plug in HybridElectric Vehicle|
|PLC||Power Line Communication|
|SCADA||Supervisory Control And Data Acquisition|
|TDMA||Time Division Multiple access|
|WAN||Wide Area Network|
|WSN||Wireless Sensor Network|
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|Severe ecological conditions||Wireless sensor nodes can be subjected to harsh environmental condition which may cause fault in wireless sensor node.|
|Various network topologies||Heterogeneous network topologies in energy distribution network due to various features and failure of sensor nodes may cause technical challenges in design of sensor nodes.|
|Limited capability||Restricted processing and memory capabilities cause various challenges in design and deployment of wireless sensor networks.|
|Bit errors||In communication systems, high bit error rates are observed due to high noise level. This calls for various error detection and correction schemes. Detection and correction of errors require greater memory and processing facilities which make the design of sensor network challenging.|
|Security of sensor networks||Security of wireless sensor network is an indispensable and decisive requirement. The sensor nodes must be secured from physical tampering to hacking for smooth functioning of various smart grid applications. Physical tampering is also called node capture.|
|Quality of service necessities for smart grid environment||The parameters like high data rates, latency, reliability and authenticity are vital for quality of service necessities of smart grid applications. Wireless sensor networks must fulfill these criterions for successful implementation of various applications.|
|Protocol/Standard||Spectrum Type||Frequency Band||Maximum Data Throughput||Coverage Range||Advantages||Disadvantages||Market Espousal|
|Zigbee||Unlicensed||868 MHz, 915 MHz, 2.4 MHz||250 Kbps||Up to 100 m||Low cost, Low power usage, Less complex||Low data rate, Short range, Interference with other technologies using ISM band, Low battery power supply||Very High|
|Bluetooth||Unlicensed||2.4 GHz||21 Kbps||Up to 100 m||Low power usage||Low data rates, Very short range, Less secured, Interference with other technologies using ISM band||Very High|
|Wi-Fi||Unlicensed||2.4 GHz, 5.8 GHz||2 Mbps to 54 Mbps||Up to 250 m||High data rates, Robust, Point to point and point to multipoint communication, Low cost, IP support and network scalability||Complex design, Prone to interference, data rates may deteriorate due to interference or co-existence problems||Very high|
|Z-Wave||Unlicensed||868 MHz, 908 MHz||9.6 Kbps to 40 Kbps||Up to 30 m||Low power usage||Very Low data rates, Short range||Medium|
|WirelessHART||Unlicensed||2.4 GHz||Up to 250 Kbps||200 m||Simple and low cost solutions, Allows co-existence of multiple networks, Keeps the black and white list of devices, Self-organizing standard, More secured||All the devices operating on WirelessHART must have routing capability, No directive on how the network is configured by network manager||Very high for industrial control applications|
|6LoWPAN||Unlicensed||868 MHz, 915 MHz, 2.4 MHz||Up to 250 Kbps||Up to 100 m||Low power usage||Low data rates, Short range||Medium|
|Wavenis||Unlicensed||868 MHz, 915 MHz, and 433 MHz||4.8 Kbps to 100 Kbps||Up to 200 m||Low power usage||Very Low data rates, Short range||Very low|
|Physical||DOS (denial of service), Jamming, Node Capture||Spread spectrum technology, Adaptive antennas|
|Data Link||Wormhole, Sink hole, Sybil, Resource exhaustion||Link layer cryptography|
|Network||DOS, Misdirection, Selective forwarding, Eavesdropping||Key management, Secured routing, Topology control|
|Transport||Flooding, Session hacking, Resource exhaustion, DOS||Intrusion detection, encryption|
|Application||DOS, Data corruption, Malicious node||Intrusion detection, Malicious node isolation|
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Chhaya, L.; Sharma, P.; Bhagwatikar, G.; Kumar, A. Wireless Sensor Network Based Smart Grid Communications: Cyber Attacks, Intrusion Detection System and Topology Control. Electronics 2017, 6, 5. https://doi.org/10.3390/electronics6010005
Chhaya L, Sharma P, Bhagwatikar G, Kumar A. Wireless Sensor Network Based Smart Grid Communications: Cyber Attacks, Intrusion Detection System and Topology Control. Electronics. 2017; 6(1):5. https://doi.org/10.3390/electronics6010005Chicago/Turabian Style
Chhaya, Lipi, Paawan Sharma, Govind Bhagwatikar, and Adesh Kumar. 2017. "Wireless Sensor Network Based Smart Grid Communications: Cyber Attacks, Intrusion Detection System and Topology Control" Electronics 6, no. 1: 5. https://doi.org/10.3390/electronics6010005