Iraqi Journal of Information and Communication Technology

Experimental Realization of Quantum Cryptography by Arduino

Harith Qaisi — 2023-08-09

This paper is concerned with the experimental realization of an Arduino-based quantum cryptography system, in which a setup of five laser diodes is constructed in the transmitter that randomly emits photons to encode information consisting of a sequence of "0" and "1" bits. The receiver contains five photoresistor sensors that detect the presence or absence of light as well as determine the intensity of the light. Laser light is used to securely transmit data, such as text or numbers, in this technology.

Improving Detection for Intrusion Using Deep LSTM With Hybrid Feature Selection Method

Baraa Farhan — 2023-08-09

Due to the importance of the intrusion detection system, which is considered supportive of enhancing network security. Therefore, we seek to increase the efficiency of intrusion detection systems through the use of deep learning mechanisms. However, intrusion detection algorithms still suffer from problems in the process of classification and determining the presence and type of attack, which causes a decrease in the detection rate, an increase in the number of false alarms, and reduces system performance. This is due to a large number of redundant features that are not relevant to the dataset. To find the solve for this problem, here propose a hybrid algorithm based on the use of the feature selection technique, which helps in reaching the goal optimally by choosing the best and most important features. And it works by integrating three ways to minimize the features by deleting the static features, that do not have much value from the information gain and is done before the training stage by the deep learning model of LSTM as preprocessing for the CSE-CIC-IDS data set, which helps in improving the performance of the system By minimizing the time for processing and increasing the detection rate and accuracy ratio. The results of the experiment showed a high accuracy of 99.84%.

Oil and Gas pipelines monitoring using IoT platform

Ahmed Yas — 2023-08-09

The early detection of pipeline breaches in the pipeline monitoring system is a crucial concern for oil management firms. Diverse technologies have been created to identify pipeline leaks. However, they need development as the current systems take a long time to detect leaks. As a result, it can contribute to oil waste and natural disasters. This paper provides a system for detecting pipeline leaks using pressure, water-flow, Accelerometer, and voltage sensors coupled to an Arduino mega microcontroller with BLYNK IoT platform real-time monitoring. It is obvious from the data that the Oil Pipe Monitoring System is capable of displaying pipeline flowrates, pressures, and acceleration. When a leak occurs or an event occurs during operation, a message is delivered to the responsible technical individual indicating which pipe is leaking. This project successfully established an Internet of Things (IoT) platform to monitor pipeline events in real-time.

Pass Point Selection of Automatic Graphical Password Authentication Technique Based on Histogram Method

Safa Abbas — 2023-08-09

Graphical passwords, as opposed to textual passwords, require the user to pick pictures or draw symbols rather than input written letters. They are an option that may be explored in order to get over the issues that are caused by the system of passwords that are based on text. It has been hypothesized that graphical passwords are more difficult to crack using a brute force technique or to figure out through guessing. This paper proposes an authentication system based on a graphical password method. The proposed system computes the password points using histogram arithmetic and encrypts the chosen password points using SHA512. The envisioned system has been realized as an android application and evaluated with existing research considering multiple measurements such as required login time, password space, and entropy. The findings reveal that the new suggested system outperforms the reference work by more than 85% in terms of login latency and more than 72% in terms of entropy results.

Face Detection and Recognition Using Google-Net Architecture

Basmal Mahmmed — 2023-08-09

Using face detection to secure places is an important application merging with machine vision. This paper reposed a system to do face detection and recognition using existing architecture google-net and transfer learning to let the network learn images based on pre-trained architecture, The design of a network leads to an architecture that leads to maximizing the accuracy of the system and accurately detecting faces that are saved to the database and specifying the effect of weights used within the nodes of the hidden layer which consider the most time-consuming task within the architecture. The main characteristics are explained and the architecture used as well as the used data set in detail with the design of a network which provides an architecture that leads to maximizing the accuracy of the system and accurately detecting faces that are saved to the database and specifying the effect of weights used within the nodes of the hidden layer which consider the most time-consuming task within the architecture. Experimental results show using epochs 10 and 100 samples imply 98.37% training accuracy whereas other numbers of epochs either provide less accuracy or consume more time, and the number of epochs and training samples can be modified according to the system requirements. Other factors like illumination, the color of the background, and face rotation or scale were discussed as impact factors.