Computer Science, Artificial Intelligence, Information Systems, Computer Networks and Communications
14
Scopus Publications
149
Scholar Citations
7
Scholar h-index
6
Scholar i10-index
Scopus Publications
Energy-saving potentials in high-temperature data centers: A spatio-temporal analysis Safaa Hriez, Mohammad Hmidan Results in Engineering, 2025 Because of the rapid growth of digital transformation, data center energy consumption has risen significantly, with cooling systems accounting for approximately 40% of total energy use. This study investigates high-temperature data centers, where operating temperatures are moderately increased to reduce cooling energy consumption while maintaining safe hardware operation. A comprehensive spatio-temporal analysis of sensor data under varying temperature and power levels (50%, 75%, and 100%) revealed strong correlations among sensors (r>0.8), confirming the reliability of measurements and enabling predictive temperature management. In particular, power consumption showed negligible correlation (r<0.3) with sensor readings at constant temperatures, indicating that temperature is the primary driver of sensor behavior. Spatial analysis highlighted a unified thermal response across inlet sensors (r>0.95) and air-conditioning systems, supporting targeted cooling strategies, whereas outlet sensors revealed localized hotspots, emphasizing the need for rack-level monitoring. Temporal analysis confirmed stationarity and strong autocorrelation (lag−1>0.9), validating the suitability of predictive models such as ARIMA, LSTM, and hybrid ARIMA–LSTM for proactive thermal management. Together, these findings establish a solid foundation for optimizing cooling strategies, enhancing energy efficiency, and improving the operational reliability of high-temperature data centers.
Efficient Temperature Forecasting for High-Temperature Data Centers Safaa Hriez 6th International Conference on Electrical Communication and Computer Engineering Icecce 2025 Conference Proceedings, 2025 As data centers continue to expand in scale and energy consumption, efficient thermal management has become crucial for reducing operational costs and environmental impact. Traditional cooling strategies often maintain low ambient temperatures, resulting in significant energy usage. This study investigates the feasibility of operating high-temperature data centers by predicting server temperatures under various thermal and workload conditions. A hybrid forecasting model combining SARIMAX and GRU is proposed to accurately capture both linear and nonlinear temperature dynamics. The model is evaluated using real-world data from a CFD-simulated testbed across nine distinct scenarios, combining varying server utilization levels and cooling setpoints. Experimental results, supported by the excellent RMSE values, demonstrate the model's high accuracy in forecasting temperature behavior. This research forms a strong basis for developing intelligent thermal management strategies to optimize cooling power demand and reduce carbon emissions.
Face Swap Detection: A Systematic Literature Review Safaa Hriez IEEE Access, 2025 Face swap technology, often associated with deepfakes, has rapidly advanced in recent years, raising serious concerns around misinformation, digital impersonation, and privacy. As a result, the development of reliable face swap detection methods has become a critical area of research. This survey provides a comprehensive review of existing approaches to face swap detection, addressing key research questions such as commonly used datasets, evaluation metrics, comparative model performance, and persistent challenges in the field. It includes a detailed taxonomy of detection methods, categorizing approaches into spatial, temporal, and spatiotemporal techniques. The survey further examines cross-dataset generalization performance to assess how well models adapt to domain shifts between training and testing data. Recent innovative directions are explored, covering adversarial defense strategies, explainability techniques, lightweight models for edge deployment, and privacy-preserving training. Additionally, best practices for building and releasing face swap detection tools are discussed to promote ethical, robust, and practical implementations. Finally, the paper outlines future research directions aimed at advancing model robustness, generalization, and compliance with legal and ethical standards. The discussions provide valuable insights that help researchers and practitioners gain a clear understanding of the face swap detection field, supporting and guiding their future research efforts.
Temperature Forecasting for High-Temperature Data Centers: Enhancing Energy Efficiency Through Predictive Modeling Safaa Hriez, Mohammad Hmidan Proceeding 12th International Conference on Information Technology Innovation Technologies Icit 2025, 2025 With the growing global concerns about climate change and the rising carbon emissions from energy-intensive industries, data centers have become a significant focus due to their high energy consumption, primarily for cooling purposes. Data centers typically require substantial power to maintain optimal operating temperatures for servers, leading to inefficiencies and a large carbon footprint. High-temperature data centers present a potential solution to reduce cooling energy consumption by operating at higher temperatures, which can significantly minimize the energy required for cooling systems. This paper explores the potential of forecasting temperature changes in high-temperature data centers to optimize thermal management, using the SARIMAX model. By accurately predicting temperature variations, data center operators can adjust their systems proactively, reducing energy usage and mitigating the environmental impact of these facilities. Three different forecasting scenarios were evaluated, with the model’s performance and accuracy discussed in relation to various temperature shifts, ultimately aiming to offer insights for more sustainable and energy-efficient data center operations.
Trust models in IoT-enabled WSN: A review Safaa Fawzey Hriez, Sufyan Almajali, Moussa Ayyash ACM International Conference Proceeding Series, 2021 Wireless Sensor Network (WSN) enables the digital world to hear, see, and smell the physical world without the interaction of human beings. It is an essential enabler of the Internet of Things (IoT) in many domains. A WSN is a group of a large number of sensor nodes and a base station. The sensor nodes are characterized by their limited processing, storage, and communication capabilities. In addition, they might get deployed in harsh physical environments where reliability is not guaranteed. Because of that, the IoT-enabled WSNs are challenged by the need to determine the trust of the sensor nodes. Thus, many research studies considered the trust of the sensor nodes in all the IoT layers. This paper overviewed the well-known attacks in the field of IoT-enabled WSN. In addition, it reviewed the trust models in the perception and the network layers of IoT. Also, it discussed the limitations and the challenges of the existing trust models to be considered by the researchers.
A novel trust-aware and energy-aware clustering method that uses stochastic fractal search in IoT-enabled wireless sensor networks Safaa Hriez, Sufyan Almajali, Hany Elgala, Moussa Ayyash, Haythem Bany Salameh IEEE Systems Journal, 2021 Wireless sensor network (WSN) technology is considered to be an integral part of large-scale and efficient deployment of Internet-of-Things (IoT). More specifically, in mission-critical IoT applications, trust in the sensor data is becoming increasingly important. Sensor nodes have limited processing, storage, and communication capabilities, which make them susceptible to attacks and unreliable functioning. However, the limitations in the energy resources of the sensors are a major challenge in maximizing the network’s lifetime. Grouping the sensors into clusters was proposed to address such energy limitations. Many meta-heuristic clustering protocols have been proposed to maximize the network lifetime, which is an NP-hard problem. This problem is more complicated when considering the trust factor. The majority of existing clustering models were built to reduce the energy consumption in the network without considering the energy consumption required to detect untrusted nodes, and thus, it requires extra energy consumption to perform this task. This article proposes a clustering protocol with a trust model that detects the untrusted nodes through energy and data-trust. In addition, the proposed clustering protocol maximizes the network’s lifetime through the good characteristics of stochastic fractal search optimization. Finally, a novel fitness function is introduced to select the cluster-heads among the trusted nodes. The function is based on the following four parameters: 1) the remaining energy of the nodes; 2) the density of the nodes; 3) the distance between each node and the base-station; and 4) the network’s dissipated energy. When forming the clusters, the density of the cluster-heads is considered to balance the load of all of the cluster-heads. The experimental evaluation performed here affirms the efficacy of the proposed protocol in comparison with existing protocols.
A novel method to verify the search results of database queries on cloud computing Safaa Hraiz, Ghazi Al-Naymat, Arafat Awajan Proceedings 2020 21st International Arab Conference on Information Technology Acit 2020, 2020 With the attractive characteristics of cloud computing, most companies manage to use it in order to decrease the costs and efforts of management. Database as a service is one of the attractive delivery models on cloud computing. It represents great opportunities for companies to decrease the efforts and costs of managing the databases. Because of that, most companies outsourced their databases to the cloud but new challenges have arisen including the guarantee of the integrity of the search results. This paper proposes a new technique that aids to ensure the integrity of the search results. It uses variants of the Bloom Filter data structure. The analysis using the TPC-H benchmark affirms that the proposed method is secure and efficient for practical deployment.
User authentication on smartphones using keystroke dynamics Safaa Hriez, Nadim Obeid, Arafat Awajan ACM International Conference Proceeding Series, 2019 These days, mobile devices have very sensitive and personal data that needs to be secured. Mobile devices use authentication techniques to protect data from unauthorized access. Consequently, many authentication mechanisms were proposed and many techniques were applied. One of these mechanisms is the analysis of the typing rhythm. It is also known as keystroke dynamics which enhances the password-based authentication by identifying the users based on their typing rhythms. This paper proposes a new authentication mechanism using keystroke dynamics. The dataset which is used in this research consists of 71 features for 42 users with 2142 records. The proposed method consists of two stages; firstly, applying some statistical methods on the 71 features in order to result with valuable new features, then the second stage is to use the existing features with the resulted features with the Random Forest machine learning algorithm. Experimental results showed an accuracy of 94.26%.
Text-based Authorship Identification - A survey Bushra Alhijawi, Safaa Hriez, Arafat Awajan 5th International Symposium on Innovation in Information and Communication Technology Isiict 2018, 2018
Energy-Saving Potentials in High-Temperature Data Centers: A Spatio-Temporal Analysis S Hriez, M Hmidan Results in Engineering, 108138 , 2025 2025
Efficient Temperature Forecasting for High-Temperature Data Centers S Hriez 2025 International Conference on Electrical, Communication and Computer … , 2025 2025
Face Swap Detection: A Systematic Literature Review S Hriez IEEE Access , 2025 2025 Citations: 2
Temperature Forecasting for High-Temperature Data Centers: Enhancing Energy Efficiency Through Predictive Modeling S Hriez, M Hmidan 2025 12th International Conference on Information Technology (ICIT), 620 - 625 , 2025 2025
Real-parameter constrained optimization using enhanced quality-based cultural algorithm with novel influence and selection schemes RS Al-Gharaibeh, MZ Ali, MI Daoud, R Alazrai, H Abdel-Nabi, S Hriez, ... Information Sciences 576, 242-273 , 2021 2021 Citations: 17
A novel trust-aware and energy-aware clustering method that uses stochastic fractal search in IoT-enabled wireless sensor networks S Hriez, S Almajali, H Elgala, M Ayyash, HB Salameh IEEE Systems Journal 16 (2), 2693-2704 , 2021 2021 Citations: 50
Trust models in IoT-enabled WSN: A review SF Hriez, S Almajali, M Ayyash International Conference on Data Science, E-learning and Information Systems … , 2021 2021 Citations: 6
Novel Energy-and Security-Aware Strategies for IoT-Enabled WSNs SF Hriez PQDT-Global , 2021 2021 Citations: 2
A novel method to verify the search results of database queries on cloud computing S Hraiz, G Al-Naymat, A Awajan 2020 21st International Arab Conference on Information Technology (ACIT), 1-7 , 2020 2020 Citations: 1
Authorship Identification for Arabic texts using logistic model tree classification S Hriez, A Awajan Science and Information Conference, 656-666 , 2020 2020 Citations: 12
User authentication on smartphones using keystroke dynamics S Hriez, N Obeid, A Awajan Proceedings of the Second International Conference on Data Science, E … , 2019 2019 Citations: 14
Structured encryption algorithm for text cryptography W Al Etaiwi, S Hraiz Journal of Discrete Mathematical Sciences and Cryptography 21 (7-8), 1559-1572 , 2018 2018 Citations: 8
Text-based authorship identification-a survey B Alhijawi, S Hriez, A Awajan 2018 Fifth International Symposium on Innovation in Information and … , 2018 2018 Citations: 14
Symmetric encryption algorithm using graph representation S Hraiz, W Etaiwi 2017 8th International Conference on Information Technology (ICIT), 501-506 , 2017 2017 Citations: 5
Challenges of digital forensic investigation in cloud computing S Hraiz 2017 8th international conference on information technology (ICIT), 568-571 , 2017 2017 Citations: 18
MOST CITED SCHOLAR PUBLICATIONS
A novel trust-aware and energy-aware clustering method that uses stochastic fractal search in IoT-enabled wireless sensor networks S Hriez, S Almajali, H Elgala, M Ayyash, HB Salameh IEEE Systems Journal 16 (2), 2693-2704 , 2021 2021 Citations: 50
Challenges of digital forensic investigation in cloud computing S Hraiz 2017 8th international conference on information technology (ICIT), 568-571 , 2017 2017 Citations: 18
Real-parameter constrained optimization using enhanced quality-based cultural algorithm with novel influence and selection schemes RS Al-Gharaibeh, MZ Ali, MI Daoud, R Alazrai, H Abdel-Nabi, S Hriez, ... Information Sciences 576, 242-273 , 2021 2021 Citations: 17
User authentication on smartphones using keystroke dynamics S Hriez, N Obeid, A Awajan Proceedings of the Second International Conference on Data Science, E … , 2019 2019 Citations: 14
Text-based authorship identification-a survey B Alhijawi, S Hriez, A Awajan 2018 Fifth International Symposium on Innovation in Information and … , 2018 2018 Citations: 14
Authorship Identification for Arabic texts using logistic model tree classification S Hriez, A Awajan Science and Information Conference, 656-666 , 2020 2020 Citations: 12
Structured encryption algorithm for text cryptography W Al Etaiwi, S Hraiz Journal of Discrete Mathematical Sciences and Cryptography 21 (7-8), 1559-1572 , 2018 2018 Citations: 8
Trust models in IoT-enabled WSN: A review SF Hriez, S Almajali, M Ayyash International Conference on Data Science, E-learning and Information Systems … , 2021 2021 Citations: 6
Symmetric encryption algorithm using graph representation S Hraiz, W Etaiwi 2017 8th International Conference on Information Technology (ICIT), 501-506 , 2017 2017 Citations: 5
Face Swap Detection: A Systematic Literature Review S Hriez IEEE Access , 2025 2025 Citations: 2
Novel Energy-and Security-Aware Strategies for IoT-Enabled WSNs SF Hriez PQDT-Global , 2021 2021 Citations: 2
A novel method to verify the search results of database queries on cloud computing S Hraiz, G Al-Naymat, A Awajan 2020 21st International Arab Conference on Information Technology (ACIT), 1-7 , 2020 2020 Citations: 1
Energy-Saving Potentials in High-Temperature Data Centers: A Spatio-Temporal Analysis S Hriez, M Hmidan Results in Engineering, 108138 , 2025 2025
Efficient Temperature Forecasting for High-Temperature Data Centers S Hriez 2025 International Conference on Electrical, Communication and Computer … , 2025 2025
Temperature Forecasting for High-Temperature Data Centers: Enhancing Energy Efficiency Through Predictive Modeling S Hriez, M Hmidan 2025 12th International Conference on Information Technology (ICIT), 620 - 625 , 2025 2025
