Shahid Tufail - Academia.edu (original) (raw)

Papers by Shahid Tufail

Research paper thumbnail of Impact, Vulnerabilities, and Mitigation Strategies for Cyber-Secure Critical Infrastructure

Sensors, Apr 17, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of Advancements and Challenges in Machine Learning: A Comprehensive Review of Models, Libraries, Applications, and Algorithms

Electronics

In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social me... more In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social media platforms, healthcare systems, etc., there is a lot of data online today. Machine learning (ML) is something we need to understand to do smart analyses of these data and make smart, automated applications that use them. There are many different kinds of machine learning algorithms. The most well-known ones are supervised, unsupervised, semi-supervised, and reinforcement learning. This article goes over all the different kinds of machine-learning problems and the machine-learning algorithms that are used to solve them. The main thing this study adds is a better understanding of the theory behind many machine learning methods and how they can be used in the real world, such as in energy, healthcare, finance, autonomous driving, e-commerce, and many more fields. This article is meant to be a go-to resource for academic researchers, data scientists, and machine learning engineers when it...

Research paper thumbnail of Combined Machine Learning and Physics-Based Forecaster for Intra-day and 1-Week Ahead Solar Irradiance Forecasting Under Variable Weather Conditions

arXiv (Cornell University), Mar 16, 2023

Research paper thumbnail of A comprehensive review on Smart Grid Data Security

SoutheastCon 2022

The modern smart grid is a development of traditional power grids that incorporates information a... more The modern smart grid is a development of traditional power grids that incorporates information and communication technology to deliver electricity from suppliers to consumers to improve reliability, efficiency, infrastructure, power system availability, sophisticated metering technology, and energy management approaches. Because smart grids connect millions of devices-wired and wireless, data transmission becomes increasingly complicated and exposed to hackers. In this paper, we reviewed the MITRE ATT&CK architecture, highlighted smart grid vulnerabilities, described the SCADA system, and looked at the primary attacks that may compromise the smart grid system. The security mechanisms that can be employed in smart grids to prevent attackers from gaining access to the system and to secure communications from eavesdropping and other forms of information theft are also discussed. Lastly, cryptographic method is discussed on the issue of securing data communication in smart grids.

Research paper thumbnail of A Comparative Study Of Binary Class Logistic Regression and Shallow Neural Network For DDoS Attack Prediction

Research paper thumbnail of Survey of Solid State Drives, Characteristics, Technology, and Applications

2020 SoutheastCon, 2020

NAND flash storage is a common digital storage architecture, because of its affordability and mat... more NAND flash storage is a common digital storage architecture, because of its affordability and mature design, NAND flash is a dominant storage technology used in embedded systems, and general purpose computers in the form of solid state drives (SSD). The use of SSD in datacenters is less common, because of reliability and cost concerns of the storage, its use in datacenters is an area of active research. Other aspects of the technology being investigated are stacked layers of memory cells, optimization of flash controller algorithms, SSD and digital forensics, and storage class memories. The future challenges and directions for research are provided at the end.

Research paper thumbnail of A Review on Quantum Computing Approach for Next-Generation Energy Storage Solution

SoutheastCon 2021, 2021

Quantum Computing technology is currently prevailing as a promising candidate for expanding the r... more Quantum Computing technology is currently prevailing as a promising candidate for expanding the research horizons in the areas of power engineering and transportation. An across-the-board view of this technology identifies that the intersecting research of interest which covers both areas is the identification of innovative energy storage technologies. Quantum Computers (QC) provide the capability to develop an innovative energy storage system, but its operating principles encompass the domains of Quantum Physics (QP) and Quantum Mechanics (QM) and thus limit the understanding of its underlying functionality. The applicable storage system under research using QC, termed Quantum Battery (QB) is considered to be a theoretical construct, which means that it is not directly observable. This paper attempts to piece together the QM and its applications in a QC, directed towards the identification of an innovative QB, by providing a review of the existing researches. Also, the explanations of various postulates and their corresponding formulations leading to the QM framework behind a QB is presented. This is followed by a review of the underlying operation of a QC and its application in performing battery research. A summary of the existing QB researches is also presented which are categorized into particle- and chemistry-driven (quantum) battery researches.

Research paper thumbnail of Cyber Physical Systems Applications with a Case Study of Intelligent Dispatch of PV

SoutheastCon 2021, 2021

Increased investments into renewable energy as distributed energy sources throughout the distribu... more Increased investments into renewable energy as distributed energy sources throughout the distribution grid are a driving force behind the need to adopt smart grid advances. Issues such as intermittency of generation from these renewables have been studied concerning the stability of the grid at higher penetration levels. One need that industry meetings have pointed out is the need for forecasting models and advanced controls that mitigate the intermittency effects. Wide-scale adoption of computing nodes into the power grid such as smart meters and smart inverters have transformed the traditional grid into a cyber-physical system (CPS), as well as independent CPS nodes such as microgrids. Centralized command and control are necessary to maintain visibility over resources and management of them. With developments in cyber-physical-systems integrations more distributed controllers are potential. Data collection becomes a more challenging task as the number of intelligent devices in the field that generates data increases. New key-store based database technologies could be utilized in highly heterogeneous data environments. One of the potential distributed CPS controllers are demonstrated in this paper is a case study of a forecasting based economic dispatch controller for large scale PV power plant that is part of the energy mix. The cost in this scenario is found to be lower when the controller is used.

Research paper thumbnail of Latency Critical Data Processing in Cloud for Smart Grid Applications

Research paper thumbnail of A Survey on Cybersecurity Challenges, Detection, and Mitigation Techniques for the Smart Grid

Energies, 2021

The world is transitioning from the conventional grid to the smart grid at a rapid pace. Innovati... more The world is transitioning from the conventional grid to the smart grid at a rapid pace. Innovation always comes with some flaws; such is the case with a smart grid. One of the major challenges in the smart grid is to protect it from potential cyberattacks. There are millions of sensors continuously sending and receiving data packets over the network, so managing such a gigantic network is the biggest challenge. Any cyberattack can damage the key elements, confidentiality, integrity, and availability of the smart grid. The overall smart grid network is comprised of customers accessing the network, communication network of the smart devices and sensors, and the people managing the network (decision makers); all three of these levels are vulnerable to cyberattacks. In this survey, we explore various threats and vulnerabilities that can affect the key elements of cybersecurity in the smart grid network and then present the security measures to avert those threats and vulnerabilities at...

Research paper thumbnail of Detection of False Data Injection of PV Production

2021 IEEE Green Technologies Conference (GreenTech), 2021

Due to cyber attack threats to the cyber physical systems which compose modern smart grids additi... more Due to cyber attack threats to the cyber physical systems which compose modern smart grids additional layers of security could be valuable. The potential of data tampering in the smart grid spurs the research of data integrity attacks and additional security means to detect such tampering. This paper conducts a study of photovoltaic based production data tampering as a detection problem and shows a set of machine learning models and highlights the best performing of the set at the detection task. The signal is observed daily and data tampering by increasing to 110%-150% of original signal is detected with over 80% accuracy and under 10% false alarm. This paper finds that the artificial neural network (ANN) slightly out performs the support vector machine (SVM) at the detection task, however the SVM is a much faster algorithm to fit the data with.

Research paper thumbnail of False Data Injection Impact Analysis In AI-Based Smart Grid

SoutheastCon 2021, 2021

As the traditional grids are transitioning to the smart grid, they are getting more prone to cybe... more As the traditional grids are transitioning to the smart grid, they are getting more prone to cyber-attacks. Among all the cyber-attack one of the most dangerous attack is false data injection attack. When this attack is performed with historical information of the data packet the attack goes undetected. As the false data is included for training and testing the model, the accuracy is decreased, and decision making is affected. In this paper we analyzed the impact of the false data injection attack(FDIA) on AI based smart grid. These analyses were performed using two different multi-layer perceptron architectures with one of the independent variables being compared and modified by the attacker. The root-mean squared values were compared with different models.

Research paper thumbnail of Cloud Computing in Bioinformatics: Solution to Big Data Challenge

International Journal of Computer Sciences and Engineering, 2017

Research paper thumbnail of Analysing data using R: An application in healthcare sector

International Journal of Computer Sciences and Engineering, 2017

Research paper thumbnail of Reliability Assessment of Grid Connected Solar Inverters in 1.4 MW PV Plant from Anomalous Classified Real Field Data

2022 North American Power Symposium (NAPS)

In this work, a top-down analysis is carried out to investigate the impacts of environmental fact... more In this work, a top-down analysis is carried out to investigate the impacts of environmental factors on the health, and hence on the reliability, of solar inverters (SI). Five years of real field data from 46 string inverters in a 1.4 MW Photovoltaic (PV) plant located at Florida International University (FIU) are used for the analysis. Collected data is classified and examined based on inverter faults, failures, and stress conditions using the classification and regression tree (CART) algorithm. Results have shown that inverter performance is highly correlated to ambient conditions, i.e. sunrise and sunset timing, relative humidity, and irradiance profile, and therefore adequate specific ventilation management can be a useful tool to mitigate some major inverter health issues. Triggered by this study, a prognostic analysis from the information in service tickets and machine learning (ML) outcomes will be carried out as future work.

Research paper thumbnail of Impact, Vulnerabilities, and Mitigation Strategies for Cyber-Secure Critical Infrastructure

Sensors, Apr 17, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of Advancements and Challenges in Machine Learning: A Comprehensive Review of Models, Libraries, Applications, and Algorithms

Electronics

In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social me... more In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social media platforms, healthcare systems, etc., there is a lot of data online today. Machine learning (ML) is something we need to understand to do smart analyses of these data and make smart, automated applications that use them. There are many different kinds of machine learning algorithms. The most well-known ones are supervised, unsupervised, semi-supervised, and reinforcement learning. This article goes over all the different kinds of machine-learning problems and the machine-learning algorithms that are used to solve them. The main thing this study adds is a better understanding of the theory behind many machine learning methods and how they can be used in the real world, such as in energy, healthcare, finance, autonomous driving, e-commerce, and many more fields. This article is meant to be a go-to resource for academic researchers, data scientists, and machine learning engineers when it...

Research paper thumbnail of Combined Machine Learning and Physics-Based Forecaster for Intra-day and 1-Week Ahead Solar Irradiance Forecasting Under Variable Weather Conditions

arXiv (Cornell University), Mar 16, 2023

Research paper thumbnail of A comprehensive review on Smart Grid Data Security

SoutheastCon 2022

The modern smart grid is a development of traditional power grids that incorporates information a... more The modern smart grid is a development of traditional power grids that incorporates information and communication technology to deliver electricity from suppliers to consumers to improve reliability, efficiency, infrastructure, power system availability, sophisticated metering technology, and energy management approaches. Because smart grids connect millions of devices-wired and wireless, data transmission becomes increasingly complicated and exposed to hackers. In this paper, we reviewed the MITRE ATT&CK architecture, highlighted smart grid vulnerabilities, described the SCADA system, and looked at the primary attacks that may compromise the smart grid system. The security mechanisms that can be employed in smart grids to prevent attackers from gaining access to the system and to secure communications from eavesdropping and other forms of information theft are also discussed. Lastly, cryptographic method is discussed on the issue of securing data communication in smart grids.

Research paper thumbnail of A Comparative Study Of Binary Class Logistic Regression and Shallow Neural Network For DDoS Attack Prediction

Research paper thumbnail of Survey of Solid State Drives, Characteristics, Technology, and Applications

2020 SoutheastCon, 2020

NAND flash storage is a common digital storage architecture, because of its affordability and mat... more NAND flash storage is a common digital storage architecture, because of its affordability and mature design, NAND flash is a dominant storage technology used in embedded systems, and general purpose computers in the form of solid state drives (SSD). The use of SSD in datacenters is less common, because of reliability and cost concerns of the storage, its use in datacenters is an area of active research. Other aspects of the technology being investigated are stacked layers of memory cells, optimization of flash controller algorithms, SSD and digital forensics, and storage class memories. The future challenges and directions for research are provided at the end.

Research paper thumbnail of A Review on Quantum Computing Approach for Next-Generation Energy Storage Solution

SoutheastCon 2021, 2021

Quantum Computing technology is currently prevailing as a promising candidate for expanding the r... more Quantum Computing technology is currently prevailing as a promising candidate for expanding the research horizons in the areas of power engineering and transportation. An across-the-board view of this technology identifies that the intersecting research of interest which covers both areas is the identification of innovative energy storage technologies. Quantum Computers (QC) provide the capability to develop an innovative energy storage system, but its operating principles encompass the domains of Quantum Physics (QP) and Quantum Mechanics (QM) and thus limit the understanding of its underlying functionality. The applicable storage system under research using QC, termed Quantum Battery (QB) is considered to be a theoretical construct, which means that it is not directly observable. This paper attempts to piece together the QM and its applications in a QC, directed towards the identification of an innovative QB, by providing a review of the existing researches. Also, the explanations of various postulates and their corresponding formulations leading to the QM framework behind a QB is presented. This is followed by a review of the underlying operation of a QC and its application in performing battery research. A summary of the existing QB researches is also presented which are categorized into particle- and chemistry-driven (quantum) battery researches.

Research paper thumbnail of Cyber Physical Systems Applications with a Case Study of Intelligent Dispatch of PV

SoutheastCon 2021, 2021

Increased investments into renewable energy as distributed energy sources throughout the distribu... more Increased investments into renewable energy as distributed energy sources throughout the distribution grid are a driving force behind the need to adopt smart grid advances. Issues such as intermittency of generation from these renewables have been studied concerning the stability of the grid at higher penetration levels. One need that industry meetings have pointed out is the need for forecasting models and advanced controls that mitigate the intermittency effects. Wide-scale adoption of computing nodes into the power grid such as smart meters and smart inverters have transformed the traditional grid into a cyber-physical system (CPS), as well as independent CPS nodes such as microgrids. Centralized command and control are necessary to maintain visibility over resources and management of them. With developments in cyber-physical-systems integrations more distributed controllers are potential. Data collection becomes a more challenging task as the number of intelligent devices in the field that generates data increases. New key-store based database technologies could be utilized in highly heterogeneous data environments. One of the potential distributed CPS controllers are demonstrated in this paper is a case study of a forecasting based economic dispatch controller for large scale PV power plant that is part of the energy mix. The cost in this scenario is found to be lower when the controller is used.

Research paper thumbnail of Latency Critical Data Processing in Cloud for Smart Grid Applications

Research paper thumbnail of A Survey on Cybersecurity Challenges, Detection, and Mitigation Techniques for the Smart Grid

Energies, 2021

The world is transitioning from the conventional grid to the smart grid at a rapid pace. Innovati... more The world is transitioning from the conventional grid to the smart grid at a rapid pace. Innovation always comes with some flaws; such is the case with a smart grid. One of the major challenges in the smart grid is to protect it from potential cyberattacks. There are millions of sensors continuously sending and receiving data packets over the network, so managing such a gigantic network is the biggest challenge. Any cyberattack can damage the key elements, confidentiality, integrity, and availability of the smart grid. The overall smart grid network is comprised of customers accessing the network, communication network of the smart devices and sensors, and the people managing the network (decision makers); all three of these levels are vulnerable to cyberattacks. In this survey, we explore various threats and vulnerabilities that can affect the key elements of cybersecurity in the smart grid network and then present the security measures to avert those threats and vulnerabilities at...

Research paper thumbnail of Detection of False Data Injection of PV Production

2021 IEEE Green Technologies Conference (GreenTech), 2021

Due to cyber attack threats to the cyber physical systems which compose modern smart grids additi... more Due to cyber attack threats to the cyber physical systems which compose modern smart grids additional layers of security could be valuable. The potential of data tampering in the smart grid spurs the research of data integrity attacks and additional security means to detect such tampering. This paper conducts a study of photovoltaic based production data tampering as a detection problem and shows a set of machine learning models and highlights the best performing of the set at the detection task. The signal is observed daily and data tampering by increasing to 110%-150% of original signal is detected with over 80% accuracy and under 10% false alarm. This paper finds that the artificial neural network (ANN) slightly out performs the support vector machine (SVM) at the detection task, however the SVM is a much faster algorithm to fit the data with.

Research paper thumbnail of False Data Injection Impact Analysis In AI-Based Smart Grid

SoutheastCon 2021, 2021

As the traditional grids are transitioning to the smart grid, they are getting more prone to cybe... more As the traditional grids are transitioning to the smart grid, they are getting more prone to cyber-attacks. Among all the cyber-attack one of the most dangerous attack is false data injection attack. When this attack is performed with historical information of the data packet the attack goes undetected. As the false data is included for training and testing the model, the accuracy is decreased, and decision making is affected. In this paper we analyzed the impact of the false data injection attack(FDIA) on AI based smart grid. These analyses were performed using two different multi-layer perceptron architectures with one of the independent variables being compared and modified by the attacker. The root-mean squared values were compared with different models.

Research paper thumbnail of Cloud Computing in Bioinformatics: Solution to Big Data Challenge

International Journal of Computer Sciences and Engineering, 2017

Research paper thumbnail of Analysing data using R: An application in healthcare sector

International Journal of Computer Sciences and Engineering, 2017

Research paper thumbnail of Reliability Assessment of Grid Connected Solar Inverters in 1.4 MW PV Plant from Anomalous Classified Real Field Data

2022 North American Power Symposium (NAPS)

In this work, a top-down analysis is carried out to investigate the impacts of environmental fact... more In this work, a top-down analysis is carried out to investigate the impacts of environmental factors on the health, and hence on the reliability, of solar inverters (SI). Five years of real field data from 46 string inverters in a 1.4 MW Photovoltaic (PV) plant located at Florida International University (FIU) are used for the analysis. Collected data is classified and examined based on inverter faults, failures, and stress conditions using the classification and regression tree (CART) algorithm. Results have shown that inverter performance is highly correlated to ambient conditions, i.e. sunrise and sunset timing, relative humidity, and irradiance profile, and therefore adequate specific ventilation management can be a useful tool to mitigate some major inverter health issues. Triggered by this study, a prognostic analysis from the information in service tickets and machine learning (ML) outcomes will be carried out as future work.