Journal of Electronics and Telecommunication System Engineering

Transformative Role of Generative AI in Safeguarding Cyber Security and Privacy

Punith B. S., Shalini M. G. — Tue, 09 Jul 2024 00:00:00 +0000

Generative AI models, commonly called GenAI, have undoubtedly marked the apex of the digital transformation in 2022. It's essential to comprehend the implications of various GenAI models, such as ChatGPT and Google Bard, from a cybersecurity standpoint as they grow in complexity and capabilities. Several cases have recently highlighted the application of GenAI methods in cybersecurity, encompassing offensive and defensive strategies while underscoring this technology's social, ethical, and privacy considerations. The constraints, difficulties, dangers, and possibilities of GenAI in the context of privacy and cybersecurity are highlighted in this research study. The work exposes ChatGPT's flaws, which malevolent users might employ to exfiltrate harmful data and overcome the model's ethical limitations. This article presents examples of successful attacks against ChatGPT, including quick injection assaults, reverse psychology, and jailbreaks. The study also explores the scenarios in which adversaries could use ChatGPT to create automated hacking, phishing, social engineering, malware creation, and polymorphic malware. It also looks into how cyber offenders could use GenAI tools to develop cyberattacks. After that, this paper looks at defence strategies and how GenAI tools can enhance security measures. We'll discuss various methods, including automated cyber defence, improving reporting mechanisms, utilizing threat intelligence, generating and detecting secure code, identifying attacks, establishing ethical guidelines, formulating incident response plans, and implementing malware detection. Additionally, we'll delve into the moral, legal, and societal considerations surrounding ChatGPT. As the community becomes aware of the cybersecurity implications of this GenAI, the article concludes by highlighting open issues and future approaches to make this technology safe, trustworthy, ethical, and secure.

IoT-Driven Medical Surveillance System

Ghule Priya Satish, Pansare Tejswini Balasaheb — Thu, 25 Jul 2024 00:00:00 +0000

The next technological revolution is the recently created Internet of Things (IoT), which links all devices together. Internet of Things (IoT) applications includes industrial settings, agricultural fields, smart parking, smart homes, smart cities, smart surrounds, and health monitoring systems. One application is monitoring a patient's health in the medical industry. The technology aims to reduce the need for manual data entry, increase hospital bed capacity especially during large public gatherings and prevent delays in patient medical information flow to healthcare providers, especially in an accident or emergency. This system's architecture is built on medical sensors that use Wireless Sensor Networks (WSNs) to evaluate patients' physical characteristics. These sensors work with the wireless network to transmit patient data. In this system, we use the Thingspeak application for the graphical representation of received data and the web-host application for the patient position. Doctors can access this data anytime and anywhere.

Real-Time Hazard Monitoring: IoT-Driven Fire and Gas Alerts with Blynk

Anagha K.K, Mjauhar, Hemalatha P, Viswanatha V — Mon, 12 Aug 2024 00:00:00 +0000

In the wake of increasing industrial and residential hazards, real-time fire and gas detection systems have become crucial for ensuring safety and minimizing damage. This research explores an IoT-based solution influencing Blynk—a robust IoT platform—to provide timely alerts for fire and gas emergencies. The system integrates various sensors with IoT technology to monitor environmental conditions continuously and send instant notifications. This paper presents an IoT-based fire and gas detection solution utilizing the Blynk platform. The proposed system integrates sensors with a microcontroller to identify gas leaks and fire incidents. These sensors transmit data wirelessly to a central processing unit. Through the Blynk platform, users can access real-time data, receive instant alerts, and respond quickly to emergencies. This approach offers a practical and efficient method to enhance safety measures across various environments, including commercial, residential, and industrial settings. In this study, we propose wireless data collection systems designed to monitor changes in gas behavior and detect gas leaks while aiming to minimize power consumption. The system utilizes flame, gas sensors (MQ2), and smoke sensors to assess environmental conditions and identify harmful gases within a manufacturing plant. The collected data can be accessed online. Our research shows that this approach significantly improves energy efficiency and data accuracy compared to traditional safety device methods.

Automated Plant Monitoring with Blynk IoT

S. Swathi, S. Kiruthika, N. Hemapriya, P. Vaijayanthi, G. Arunachalam — Mon, 12 Aug 2024 00:00:00 +0000

In today's era of technological advancement, automation is transforming every aspect of our lives, including plant care. This article delves into the development of an automated plant monitoring system powered by Blynk IoT. The system is designed to ensure optimal plant growth conditions by automating essential maintenance tasks and minimizing the need for human intervention. The system meticulously monitors and regulates moisture levels and temperature, maintaining the ideal environment for plant growth. It features a sophisticated alert mechanism notifying users of deviations from preset parameters, ensuring prompt corrective actions.

Additionally, the system is equipped with an automated irrigation feature, activating a water pump when soil moisture levels drop below the desired threshold. Enhanced security and monitoring capabilities are integrated through a PIR motion sensor, which detects any unusual activity around the plants. The critical components of this automated system include an ESP8266 Node MCU board, a DHT11 temperature and humidity sensor, a soil moisture sensor, a PIR motion sensor, an 18650 battery, a relay module, and a water pump. All system functionalities are accessible and controllable via the Blynk Application, providing users with a seamless and user-friendly graphical interface. This integration with the Blynk IoT platform allows users to remotely monitor and manage their plants, ensuring optimal care with minimal effort. This innovative approach transforms plants into smart entities capable of self-maintenance, ushering in a new era of intelligent gardening.

AI-Enhanced Wireless Smart Glasses for Seamless Remote Guidance and Reading Support for the Visually Impaired

Sahil Rizvi — Tue, 20 Aug 2024 00:00:00 +0000

Integrating Artificial Intelligence (AI) and wireless communication technologies into smart glasses represents a transformative advancement in assistive devices for visually impaired individuals. This paper explores developing and deploying AI-enhanced wireless smart glasses, which offer seamless remote guidance and reading support. By enabling AI technologies, such as object detection with Optical Character Recognition (OCR) and advanced text-to-speech systems, these smart glasses address critical challenges in reading and navigation for the blind and partially sighted. The system utilizes Raspberry Pi technology to integrate these functionalities, providing real-time assistance through a combination of sensors, cameras, and audio feedback. This study reviews current advancements in AI and wireless communication, evaluates the capabilities of these smart glasses, and analyzes their impact on user experience. Case studies are presented to demonstrate the effectiveness of these devices, while critical challenges and future research directions are identified to enhance their development and deployment.