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In recent times, the Internet of Things is considered a future internet solution in cloud computing technology. Telecommunication knowledge and solutions have significantly progressed the capability and performance of IoT with enhancements of technology. IoT security environment helps to provide a safeguard for network and system. Rapid progress on IoT applications has progressed with the conjunction of WSN and RFID.
IoT network layer significantly serves different functions containing data transmission and routing for a data centre. However, security and privacy have become a significant concern for data centres due to the lack of IoT devices, physical, software, hardware, compliance, and awareness hardening in a security environment. This research study will help to identify and analyze significant security threats and attacks on data centres that use
IoT solutions.
Cyber-Physical System Security of a Power Grid
Cyber Security threats are nowadays affecting companies large and most popular threats are unauthorized network access, malware attacks, weak-password-inducing threats, and many more. The development of the Smart Power Grid has provided an improvement system
reliability efficiently.
The primary objective of this research is to understand the effectiveness of the Smart Power Grid to improve the capability and accountability of automation and cyber-system threats. Security is significantly referred to as confidentiality, authentication, end-to-end encryption, and integrity solutions,
poor network security over those solutions can induce major security
challenges. Devices with poor network security are vulnerable to inducing security challenges within a data centre.
As shown in figure 1, propose IoT model is fundamentally based upon five layers transport layer, cloud services layer, protocol or network layer, data layer, and perception layer [6]. The physical layer includes IoT devices and sensors including QR code, RFID, WSN, and WBAN, which can ensure protection from cyber threats [6]. This research has proposed an
effective IoT architecture that can include the following factors:
● Supervisory Control:
An intruder-type threat presents a network system for private mining data from a data centre. Persistence threats are consistent within a network and help attackers steal or exfiltrate users’ crucial sensitive information from data centres.
Supervisory Control can effectively control abnormal operating processes in different power grids with organizations, therefore, preventing chances of security threats.
The proposed architecture system has been deployed in different sectors including oil, power, gas, manufacturing, and transportation. Abnormal operating situations of power systems could be identified from a remote location with help of the proposed architecture system.
● Cyber Intrusion Detection Systems:
It is a major and common attack type induced by hackers during drive-by downloading where attackers execute malware into a network server. It is an automated program used by attackers to exploit known vulnerabilities in applications or systems.
A firewall generally serves as a frontline defence for a protection system. However, malicious codes could not be detected in high layers of communication structure. It can introduce a derived intrusion-detection probability in heterogeneous and homogeneous WSNs. Sometimes a decentralized intrusion-detection model is used in WSN [6].
An effective solution to prevent MIM attacks is the use of an Intrusion Detection System and it makes the system appropriate for attack detection and real-time intrusion [6]. Machine-learning algorithms are sometimes used for detecting intrusion in IoT systems; however, the installation of an intrusion protection system could be more effective.
● Distributed Denial-of-service (DDoS) attacks:
IoT-enabled data centres have increased connectivity and scale of data sources within a network for users. In comparison, DDoS attacks are critical for a web trafficking system as it is induced by malicious attacks on a network server for stealing the confidential data of users from data centres [6]. DNS attacks are common in AR-DDoS architecture. DNS Resolvers are utilized as reflectors during an attack on AR-DDoS.
● Data leakage challenges:
Data transmission from a network server to a data centre using an IoT-based layer can induce significant challenges for the security framework. In context, lack of storage protection of servers and security to IoT-enabled data centres can cause data leakage challenges for the system.
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