A Trusted Authentication Scheme for IoT-based Smart Grid Applications

Amsaad, Fathi; Köse, Selçuk

doi:10.1109/wf-iot48130.2020.9221442

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…To increase effectiveness and performance, these methods are used in a variety of sectors, including healthcare, transit, and industry. CPS, however, faces significant difficulties with security and privacy issues because they are susceptible to cyberattacks that could jeopardize their usefulness and security levels [24,25,26]. To handle these issues, a number of security and private approaches have been put forth for different use cases.…”

Section: Review Of Security Models For Securing Cyber Physical Deploy...mentioning

confidence: 99%

BSCSML: Design of an Efficient Bioinspired Security &Privacy Model for Cyber Physical System using Machine Learning

Megha Sanjay Wankhade

2023

IJRITCC

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With the increasing prevalence of Smart Grid Cyber Physical Systems with Advanced Metering Infrastructure (SG CPS AMI), securing their internal components has become one of the paramount concerns. Traditional security mechanisms have proven to be insufficient in defending against sophisticated attacks. Bioinspired security and privacy models have emerged as promising solutions due to their stochastic solutions. This paper proposes a novel bio-inspired security and privacy model for SG CPS AMI that utilizes machine learning to strengthen their security levels. The proposed model is inspired by the hybrid Grey Wolf Teacher Learner based Optimizer (GWTLbO) Method’s ability to detect and respond to threats in real-time deployments. The GWTLbO Model also ensures higher privacy by selecting optimal methods between k-privacy, t-closeness & l-diversity depending upon contextual requirements. This study improves system accuracy and efficiency under diverse attacks using machine learning techniques. The method uses supervised learning to teach the model to recognize known attack trends and uncontrolled learning to spot unknown attacks. Our model was tested using real-time IoT device data samples. The model identified Zero-Day Attacks, Meter Bypass, Flash Image Manipulation, and Buffer-level attacks. The proposed model detects and responds to attacks with high accuracy and low false-positive rates. In real-time operations, the proposed model can handle huge volumes of data efficiently. The bioinspired security and privacy model secures CPS efficiently and is scalable for various cases. Machine learning techniques can improve the security and secrecy of these systems and revolutionize defense against different attacks.

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Section: Review Of Security Models For Securing Cyber Physical Deploy...mentioning

confidence: 99%

BSCSML: Design of an Efficient Bioinspired Security &Privacy Model for Cyber Physical System using Machine Learning

Megha Sanjay Wankhade

2023

IJRITCC

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“…PUFs use a challenge-response mechanism to obtain unique devicespecific binary secret keys. SPUFs have recently emerged as a promising hardwarebased security primitive to protect intelligent systems, including consumer electronics and smart grid, against invasive and non-invasive attacks [33,34]. Such attacks include counterfeit parts in electronics consumer manufacturing, physical tampering and reverse-engineering attacks used by an adversary for design cloning and/or overbidding, detection of fault-injection attacks on SRAM and EEPROM based devices, and detection of malicious circuitry such as hardware Trojans [22-24, 31, 35-44].…”

Section: Related Workmentioning

confidence: 99%

“…The storage requirement for the authentication levels of the proposed scheme according to NIST standards is also explored in this section. For L1, the authentication process is performed where 128 different authentication bits are encrypted and sent every time a PEV needs to authenticate itself to the UCCC [34]. For a community of 200 vehicles, an external hard drive with a size of 25,600 bits = 3.12 kB (128× 200) is required to store the encrypted PUF secret key information in terms of encrypted binary PUF response bits.…”

Section: Storage Requirementsmentioning

confidence: 99%

A Secure Lightweight Hardware-Assisted Charging Coordination Authentication Framework for Trusted Smart Grid Energy Storage Units

Amsaad

Köse

2021

SN COMPUT. SCI.

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Smart plug-in electrical vehicles (PEVs) have recently become essential components of the energy storage units (ESUs) in a smart power grid network. ESUs need to frequently communicate with charging stations for authentication before their battery systems are securely and efficiently charged. In this paper, an efficient lightweight hardware-assisted authentication and key management framework for ESU based charging coordination system is proposed. The framework integrates a hybrid lightweight arbiter linear feedback shift register (ALFSR) physical unclonable function and a low-cost advanced encryption standard (AES) for more secure, trusted, and robust secret key scheme. The scheme is implemented and validated on a reprogrammable device using 28 nm Field Programmable Gate Arrays (FPGA) platform. The results demonstrate that our framework can generate inherently unique and reliable secret keys. The proposed scheme is efficient in terms of key storage requirements and satisfies the authentication time of five security levels required by National Institute of Standards and Technology (NIST). Furthermore, the resilience of the proposed ALFSR is analyzed against ML modeling attacks, including k-nearest neighbor (kNN), kernel support vector machines (KernelSVM), and artificial neural network (ANN) which aim to clone the PUF behavior and compromise the secret key. The preliminary results demonstrate that the ALFSR PUF design is less vulnerable to kNN and SVM ML attacks as compared to ANN attacks. Keywords Energy storage units • Physical unclonable functions (PUFs) • Smart grid securityThis article is part of the topical collection "Technologies and Components for Smart Cities" guest edited by Himanshu Thapliyal, Saraju P. Mohanty, Srinivas Katkoori and Kailash Chandra Ray.

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A Lightweight Hardware-based Authentication for Secure Smart Grid Energy Storage Units

Amsaad

Köse

2021

2021 IEEE 7th World Forum on Internet of Things (WF-IoT)

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A Trusted Authentication Scheme for IoT-based Smart Grid Applications

Cited by 3 publications

References 19 publications

BSCSML: Design of an Efficient Bioinspired Security &Privacy Model for Cyber Physical System using Machine Learning

BSCSML: Design of an Efficient Bioinspired Security &Privacy Model for Cyber Physical System using Machine Learning

A Secure Lightweight Hardware-Assisted Charging Coordination Authentication Framework for Trusted Smart Grid Energy Storage Units

A Lightweight Hardware-based Authentication for Secure Smart Grid Energy Storage Units

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