Ali Imad Abduljabbar

@uoninevah.edu.iq

College of Electronics Engineering / Department of Computer and Information Engineering
Ninevah University

Ali Imad Abduljabbar


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https://researchid.co/ali.abduljabbar

RESEARCH INTERESTS

Computer network, SDN, network security
3

Scopus Publications

Scopus Publications

  • QR Code Encryption for improving Bank information and Confidentiality
    Fahad Layth Malallah, Ali I. Abduljabbar, Baraa T. Shareef, Ali Othman Al-Janaby
    2023 27th International Conference on Information Technology IT 2023, 2023
    Nowadays, storing confidential documents using cloud services is getting popular due to advantages regarding security and fast processing operations. One of the major services of cloud computing is cloud storage, which is conversely raises some issues regarding information security. Storing information for cooperation such as a bank in the cloud needs a fast processing operation to avoid any bottleneck in the work procedure. Therefore, Quick Response (QR) code is highly required to be utilized in these operations. The advantage of the QR code is easier for reading information by just scanning using any reader available on smart devices. The methodology is to integrate the security with QR code to save the text bank information. This is done by converting text to the QR code as an image form, then applying a cryptography algorithm to the QR code image then upload it to the cloud storage. Later on, once the plaintext is required to be reconstructed, the same operations are applied exactly to the encryption phase. In which the same algorithm will be applied for decryption then a QR code reader is used to preview the target bank text. For security matters, a key is used to be embedded in the protection operation. The type of encryption is proposed to be a symmetric One-time-pad (OTP) cryptography algorithm.
  • DESIGN OF AN IOT SMART CURRENT CONTROL SYSTEM BASED ON GOOGLE ASSISTANT
    Ali Abduljabbar, Omar Alsaydia, Aya Mahfoodh, Rushd Mohammed
    Eastern European Journal of Enterprise Technologies, 2022
    In locations where power is restricted, such as off-grid, solar, and generator-powered houses, considering the capacity of the power source is critical for the effectiveness of home automation systems. During regular power system outages, millions of houses all over the globe are reliant on a fixed current power supply to keep their lights on. In such circumstances, prioritizing and arranging the home's workload is essential. The goal of this paper is to decrease the amount of effort required by the user to manually control a gadget. To connect with the Raspberry Pi and the users, this system makes use of Google Assistant Software Development Kit (SDK), which is offered by Google. Users use voice commands to manage the devices in their homes, check the amount of current available, and chat to the Google Assistant to turn on/off the smart switch. This paper suggests using a sensor, Message Queuing Telemetry Transport (MQTT) protocol, a controller (OpenHAB open source), and an actuator in conjunction with each other (smart switch) has the capability of measuring and monitoring the entire power that is available and making choices based on that knowledge. Finally, the usage of Google Assistant as an artificial intelligence system makes end-user engagement with the smart home more pleasant. The proposed network was executed in both unlimited and limited power or electrical current modes to compare the standard unlimited smart home setup and our current control design. The system was programmed to function based on the proposed algorithm, with a 10 Ampere as a maximum available current. The water heater was considered a low priority load in this trial as a heavy load. In this system’s run, the smart controller was continuously monitoring the load, and when the total load reaches 10 Amperes or above it turns off the low priority loads. Thus, preventing the power supply overload.
  • Controlling Embedded Systems Remotely via Internet-of-Things Based on Emotional Recognition
    Mohammad J. M. Zedan, Ali I. Abduljabbar, Fahad Layth Malallah, Mustafa Ghanem Saeed
    Advances in Human Computer Interaction, 2020
    Nowadays, much research attention is focused on human–computer interaction (HCI), specifically in terms of biosignal, which has been recently used for the remote controlling to offer benefits especially for disabled people or protecting against contagions, such as coronavirus. In this paper, a biosignal type, namely, facial emotional signal, is proposed to control electronic devices remotely via emotional vision recognition. The objective is converting only two facial emotions: a smiling or nonsmiling vision signal captured by the camera into a remote control signal. The methodology is achieved by combining machine learning (for smiling recognition) and embedded systems (for remote control IoT) fields. In terms of the smiling recognition, GENKl-4K database is exploited to train a model, which is built in the following sequenced steps: real-time video, snapshot image, preprocessing, face detection, feature extraction using HOG, and then finally SVM for the classification. The achieved recognition rate is up to 89% for the training and testing with 10-fold validation of SVM. In terms of IoT, the Arduino and MCU (Tx and Rx) nodes are exploited for transferring the resulting biosignal remotely as a server and client via the HTTP protocol. Promising experimental results are achieved by conducting experiments on 40 individuals who participated in controlling their emotional biosignals on several devices such as closing and opening a door and also turning the alarm on or off through Wi-Fi. The system implementing this research is developed in Matlab. It connects a webcam to Arduino and a MCU node as an embedded system.