Volume 16, Issue 1, February 2025

Smart Home Energy Management Algorithm Considering Renewables Energies with Storage System and Electric Vehicles

Halim Halimi, Gazmend Xhaferi

Department of IT, Faculty of Natural Sciences and Mathematics, University of Tetova, Tetova, R. N. Macedonia

Abstract - The efficient use of the incorporation of photovoltaic generation (PV) an electric vehicle (EV) and solar panel with the home energy management system (HEMS) can play a significant role in improving grid stability and economic benefit of the consumers. To reduce the peak load and electricity bill, was proposed a smart appliances control algorithm for the smart home energy management system (SHEMS) with integration of the renewable energy sources (RES), electric vehicles (EV) and energy storage system (ESS). The proposed algorithm decreases the peak load and electricity bill by shifting starting times of shifted appliances from peak to off-peak periods. Therefore, an energy storage system (ESS) and backup battery storage system (BBSS) are also considered for stable and reliable power system operation. The aim of this is to reduce energy usage and monetary cost with an efficient home energy management scheme (HEMS). In this paper, a cost-efficient power-sharing technique is developed which works based on priorities of appliances operating time.

Index Terms - Smart Home, HEMS, RESs, PV, Electric Vehicle (EV) and ESS

A Comprehensive Review of Cyber Threat Modeling and Phishing Resilience in Microsoft 365 Cloud Ecosystem

Pages: 7-9 (3) | [Full Text] PDF (308K)

Rana Ans Shahzad, M. J. Arshad

Department of Computer Science, University of Engineering and Technology, Lahore, Punjab 54890, Pakistan

Abstract - Microsoft 365’s widespread adoption has introduced critical security challenges, including AI-driven phishing campaigns (up 45% in 2023), unpatched legacy vulnerabilities (responsible for 22% of breaches), and insufficient threat modeling automation. This paper synthesizes 2022–2024 research to evaluate advancements in AI-augmented threat intelligence, multi-layered phishing defenses, and temporal vulnerability management. Through a systematic analysis of 10 key studies, we identify persistent gaps in adaptive attack detection (e.g., multi-channel phishing), user awareness (only 34% of employees pass phishing simulations), and hybrid-cloud governance. Our findings propose an integrated framework combining predictive threat modeling, automated email security protocols (e.g., DMARC adoption reducing spoofing by 85%), and legacy system modernization strategies, demonstrating a 40% reduction in manual effort and 60% fewer outages in pilot implementations.

Index Terms - Cyber Threat, Cloud Ecosystem, Phishing Defense and AI Augmented Threat

Fraud Detection in Credit Cards Using Machine Learning

Pages: 10-14 (5) | [Full Text] PDF (314K)

Tehreem Zahid

Department of Computer Science and Engineering, University of Engineering and Technology, Lahore, Pakistan

Abstract - The rapid growth of electronic transactions in the modern financial landscape has led to an increased prevalence of fraudulent activities, particularly in the realm of credit and debit cards. This research paper explores the application of machine learning algorithms for the detection and prevention of fraud in card transactions. By leveraging the power of artificial intelligence and data analytics, financial institutions can significantly enhance their capabilities to identify and mitigate fraudulent activities, thereby safeguarding the interests of both consumers and businesses.

Index Terms - Machine Learning, Data Science, Credit Card Fraud Detection and Algorithms

The Rise of 6G Implications for the Future of Internet of Things Applications: A Review

Pages: 15-23 (9) | [Full Text] PDF (597K)

Dua Iqbal, Romna-tul-jannat, Junaid Arshad

Department of Computer Science, University of Engineering & Technology, Lahore, Pakistan.

Abstract - Due to the rapid urbanization and increasing digital technologies demand, smart sustainable cities (SSC) have been designed by the Internet of Things (IoT) control mechanism to focus on resources and managerial aspects and to improve urban life. As of 2016, 54.7% of the world’s population was living in urban areas and more is predicted to be living in urban areas in 2030 (70%). The key to meeting the United Nations Sustainable Development Goals (SDGs) is the concentration of IoT with next generation wireless communication technologies such as 6G.The current infrastructure stress in Pakistan due to fast urbanization and inadequate energy systems and agricultural efficiency could find transformative solutions through 6G IoT technology. The capabilities of these technologies to deliver fast-latency alongside extensive connectivity would solve key problems in agriculture and energy distribution and healthcare delivery primarily in rural areas. This review paper goes on to survey the evolutionary process of 6G technologies and show how they can bring about the transformative possibilities of IoT applications through major enablers, new use cases, and critical challenges. The paper shows how the ultra low latency, massive connectivity, and the very high data rates of 6G shall make opening up of many new applications possible; such as remote surgery, real time environmental monitoring, holographic communication, just to mention a few, all underpinned by a bundle of existing literature. This can be deployed in the assisted form of artificial intelligence (AI) and machine learning in different aspects of 6G supported IoT systems. For the realization of 6G, it is thus technically concerned with spectrum management, energy efficiency, and cybersecurity. The purpose of this review is to present an overall understanding of the role of 6G in the evolution of IoT and what will be fostered with more intelligence, interconnectedness and sustainability.

Index Terms - 6G, Artificial Intelligence (AI), Digital Twin, Internet of Things (IoT), Smart Sustainable Cities (SSCs), Ultra-Low Latency and Ultra-Dense Networks (UDN)

Volume 16, Issue 1, February 2025

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