Leveraging Artificial Intelligence of Things for Anomaly Detection in Advanced Metering Infrastructures

Ogu, Reginald E.; Ikerionwu, Charles; Ayogu, Ikechukwu Ignatius

doi:10.1109/cybernigeria51635.2021.9428792

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…Relatively fast and accurate anomaly detection rates [30] Mostly deployed for the detection of threats and attacks [31] 4…”

Section: Artificial Intelligence (Ai) Techniquementioning

confidence: 99%

“…However, with attenuation being proportional to frequency (which is high), there's a need for repeaters which introduces additional cost and also latency to the system. Hence, in ensuring maximum reduction of latency in AMI operations, the broadband PLC is not advisable [31].…”

Section: Ami Architecture and Its Communication Protocolsmentioning

confidence: 99%

“…The latter protocol is a centralized system that controls the network metering process. It improves the robustness and agility of the communication network in use and also allows automatic network configuration, transmission management, and ease in the usage of the 128-bit AES encryption method [31,34,35]. A tabular summary of some of the vulnerabilities of AMI protocols and suggested countermeasures are given in Table 7.…”

Section: Ami Architecture and Its Communication Protocolsmentioning

confidence: 99%

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Privacy and security of advanced metering infrastructure (AMI) data and network: a comprehensive review

Ajiboye,

Agyekum,

Frimpong

2024

J. Eng. Appl. Sci.

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The traditional electrical grid has to be digitally improved as digitalization and effective integration of renewable energy bring better efficiency, intelligence, and safety into the grid; hence, the transition from the traditional grid to a smart grid. A smart grid is a modernized and digitalized standard electrical infrastructure that has a key component known as the advanced metering infrastructure (AMI). AMI, also known as smart metering, is a key technological enabler of the smart grid that allows automatic collection and reporting of power-consumed data via two-way communication networks. However, the collected power consumption data is confidential; hence, its privacy must be maintained. Similarly, for the benefit of the smart grid to be consistently maximized, the AMI data and network security must always be intact despite the evolving threats and attacks targeted at it.This paper provides a comprehensive review of the existing vulnerabilities/attacks, security and privacy challenges associated with the smart metering data and network system, its open issues, and future direction. The major contributions of this review paper lie in the AMI vulnerabilities, AMI state-of-the-art security schemes with their pros and cons, its communication protocols analysis, and its emerging security measures. This gave enumerated recommendations for the efficiency improvement of AMI security in terms of its latency reduction while implementing efficient security measures in its future work.

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“…Relatively fast and accurate anomaly detection rates [30] Mostly deployed for the detection of threats and attacks [31] 4…”

Section: Artificial Intelligence (Ai) Techniquementioning

confidence: 99%

Section: Ami Architecture and Its Communication Protocolsmentioning

confidence: 99%

Section: Ami Architecture and Its Communication Protocolsmentioning

confidence: 99%

See 1 more Smart Citation

Privacy and security of advanced metering infrastructure (AMI) data and network: a comprehensive review

Ajiboye,

Agyekum,

Frimpong

2024

J. Eng. Appl. Sci.

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“…As we look to the future, there are several promising avenues for further research and development in TCP/IP header security. One area of focus could be on the development of advanced anomaly detection techniques (shown in Figure 9) that leverage machine learning algorithms to detect subtle deviations in TCP/IP header patterns indicative of malicious activity [170], [171]. Additionally, research into enhancing the security features of TCP/IP headers themselves, such as incorporating cryptographic mechanisms for authentication and integrity verification [172], holds potential for strengthening overall network defenses.…”

Section: Future Research Directionsmentioning

confidence: 99%

Survey on evolving threats in TCP/IP header attacks: Emerging trends and future directions

Winnie Owoko

2024

World J. Adv. Eng. Technol. Sci.

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The TCP/IP protocol suite, a cornerstone of modern networking, faces escalating threats from evolving attack vectors targeting its headers. This survey explores emerging trends in TCP/IP header attacks, assessing their potential impact and outlining future directions for defense strategies. By scrutinizing recent research and real-world incidents, the paper aims to offer insights into the evolving threat landscape and provide recommendations for enhancing network security. Key areas of investigation include the historical evolution of TCP/IP header vulnerabilities, the adaptation of attackers' techniques over time, and the development of novel defense mechanisms to counteract these threats. The survey underscores the critical importance of understanding TCP/IP header attacks in contemporary cybersecurity and highlights the necessity for proactive measures to safeguard network infrastructures. By addressing the challenges posed by evolving TCP/IP header attacks and identifying areas for further research and development, this survey contributes to the ongoing efforts to strengthen network defenses and mitigate the risks associated with cyber threats targeting TCP/IP protocols.

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“…AntiConcealer is an Edge AI approach for detecting adversary concealed behaviors in the IoT [18]. For the security solutions, Edge AI is also used for anomaly detection in the advanced metering infrastructures [19], while Nawaz et al introduce Ethereum blockchain based solution for analysing the data and tracking the parties accessing that analysis data [20].…”

Section: Edge Ai Applicationsmentioning

confidence: 99%

Artificial Intelligence in the IoT Era: A Review of Edge AI Hardware and Software

Sipola

Alatalo

Kokkonen

et al. 2022

2022 31st Conference of Open Innovations Association (FRUCT)

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The modern trend of moving artificial intelligence computation near to the origin of data sources has increased the demand for new hardware and software suitable for such environments. We carried out a scoping study to find the current resources used when developing Edge AI applications. Due to the nature of the topic, the research combined scientific sources with product information and software project sources. The paper is structured as follows. In the first part, Edge AI applications are briefly discussed followed by hardware options and finally, the software used to develop AI models is described. There are various hardware products available, and we found as many as possible for this research to identify the best-known manufacturers. We describe the devices in the following categories: artificial intelligence accelerators and processors, field-programmable gate arrays, system-on-a-chip devices, system-on-modules, and full computers from development boards to servers. There seem to be three trends in Edge AI software development: neural network optimization, mobile device software and microcontroller software. We discussed these emerging fields and how the special challenges of low power consumption and machine learning computation are being taken into account. Our findings suggest that the Edge AI ecosystem is currently developing, and it has its own challenges to which vendors and developers are responding.

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Leveraging Artificial Intelligence of Things for Anomaly Detection in Advanced Metering Infrastructures

Cited by 7 publications

References 25 publications

Privacy and security of advanced metering infrastructure (AMI) data and network: a comprehensive review

Privacy and security of advanced metering infrastructure (AMI) data and network: a comprehensive review

Survey on evolving threats in TCP/IP header attacks: Emerging trends and future directions

Artificial Intelligence in the IoT Era: A Review of Edge AI Hardware and Software

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