Raed Alharthi

558 total citations
25 papers, 355 citations indexed

About

Raed Alharthi is a scholar working on Artificial Intelligence, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Raed Alharthi has authored 25 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 6 papers in Signal Processing. Recurrent topics in Raed Alharthi's work include Network Security and Intrusion Detection (6 papers), Privacy-Preserving Technologies in Data (6 papers) and Advanced Malware Detection Techniques (6 papers). Raed Alharthi is often cited by papers focused on Network Security and Intrusion Detection (6 papers), Privacy-Preserving Technologies in Data (6 papers) and Advanced Malware Detection Techniques (6 papers). Raed Alharthi collaborates with scholars based in United States, Saudi Arabia and Pakistan. Raed Alharthi's co-authors include Mohamed Zohdy, Ibrahim Alrashdi, Ali Alqazzaz, Esam Aloufi, Hua Ming, Abdulrahman Alzahrani, Huirong Fu, Hani Alshahrani, Shtwai Alsubai and Muhammad Umer and has published in prestigious journals such as PLoS ONE, IEEE Access and Cancers.

In The Last Decade

Raed Alharthi

20 papers receiving 330 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Raed Alharthi United States	7	231	189	147	72	37	25	355
Esam Aloufi United States	5	203 0.9×	159 0.8×	114 0.8×	39 0.5×	36 1.0×	12	273
Yulong Fu China	9	249 1.1×	170 0.9×	112 0.8×	59 0.8×	28 0.8×	15	350
Junyang Qiu China	11	265 1.1×	191 1.0×	270 1.8×	183 2.5×	18 0.5×	21	463
Bimal Ghimire United States	6	167 0.7×	255 1.3×	43 0.3×	112 1.6×	27 0.7×	9	377
Farzaneh Shoeleh Canada	9	130 0.6×	159 0.8×	98 0.7×	81 1.1×	30 0.8×	18	304
Ali A. Ghorbani Canada	10	337 1.5×	235 1.2×	195 1.3×	94 1.3×	60 1.6×	23	451
Tianlong Yu United States	9	373 1.6×	163 0.9×	153 1.0×	135 1.9×	24 0.6×	14	486
Yuan Luo United Kingdom	8	421 1.8×	207 1.1×	118 0.8×	51 0.7×	55 1.5×	21	535
Weifeng Chen United States	9	257 1.1×	184 1.0×	61 0.4×	91 1.3×	24 0.6×	25	364
Chunyu Ai United States	10	305 1.3×	123 0.7×	56 0.4×	27 0.4×	14 0.4×	28	411

Countries citing papers authored by Raed Alharthi

Since Specialization

Citations

This map shows the geographic impact of Raed Alharthi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Raed Alharthi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raed Alharthi more than expected).

Fields of papers citing papers by Raed Alharthi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raed Alharthi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Raed Alharthi. The network helps show where Raed Alharthi may publish in the future.

Co-authorship network of co-authors of Raed Alharthi

This figure shows the co-authorship network connecting the top 25 collaborators of Raed Alharthi. A scholar is included among the top collaborators of Raed Alharthi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Raed Alharthi. Raed Alharthi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Alharthi, Raed, et al.. (2025). Novel deep reinforcement learning based collision avoidance approach for path planning of robots in unknown environment. PLoS ONE. 20(1). e0312559–e0312559. 1 indexed citations

Umer, Muhammad, et al.. (2025). Deepfake detection using optimized VGG16-based framework enhanced with LIME for secure digital content. Image and Vision Computing. 162. 105696–105696.

Sarwar, Nadeem, et al.. (2025). Enhancing IoT communication in fog computing: a lightweight remote user authentication and key management scheme utilizing ECC. Journal of Cloud Computing Advances Systems and Applications. 14(1).

Arshad, Muhammad, et al.. (2025). BioAug-Net: a bioimage sensor-driven attention-augmented segmentation framework with physiological coupling for early prostate cancer detection in T2-weighted MRI. BioData Mining. 18(1). 49–49.

Alturki, Nazik, Raed Alharthi, Muhammad Umer, et al.. (2024). Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology. Computer Modeling in Engineering & Sciences. 139(3). 3387–3415. 3 indexed citations

Alharthi, Raed, et al.. (2024). Attention 3D central difference convolutional dense network for hyperspectral image classification. PLoS ONE. 19(4). e0300013–e0300013. 4 indexed citations

Noreen, Iram, et al.. (2023). Forged Video Detection Using Deep Learning: A SLR. Applied Computational Intelligence and Soft Computing. 2023. 1–21. 2 indexed citations

Karamti, Hanen, et al.. (2023). Improving Prediction of Cervical Cancer Using KNN Imputed SMOTE Features and Multi-Model Ensemble Learning Approach. Cancers. 15(17). 4412–4412. 36 indexed citations

Karamti, Hanen, Raed Alharthi, Muhammad Umer, et al.. (2023). Breast cancer detection employing stacked ensemble model with convolutional features. Cancer Biomarkers. 40(2). 155–170. 4 indexed citations

10.

Alharthi, Raed, et al.. (2020). Protecting Location Privacy for Crowd Workers in Spatial Crowdsourcing Using a Novel Dummy-Based Mechanism. IEEE Access. 8. 114608–114622. 8 indexed citations

11.

Aloufi, Esam, et al.. (2020). An Efficient Approach for Task Assignment in Spatial Crowdsourcing. 1–5. 2 indexed citations

12.

Aloufi, Esam, et al.. (2020). TASC: Efficient Task Assignment in Spatial Crowdsourcing with Workers Privacy Protection. 39. 546–550. 3 indexed citations

13.

Alqazzaz, Ali, Raed Alharthi, Ibrahim Alrashdi, et al.. (2019). A Practical Evaluation of a Secure and Energy-Efficient Smart Parking System Using the MQTT Protocol. 2. 165–170. 1 indexed citations

14.

Alrashdi, Ibrahim, Ali Alqazzaz, Raed Alharthi, et al.. (2019). FBAD: Fog-based Attack Detection for IoT Healthcare in Smart Cities. 515–522. 34 indexed citations

15.

Alshehri, Ali, Hani Alshahrani, Abdulrahman Alzahrani, et al.. (2018). DOPA: Detecting Open Ports in Android OS. EngagedScholarship @ Cleveland State University (Cleveland State University). 1–2. 1 indexed citations

16.

Alharthi, Raed, Abdulrahman Alzahrani, Ali Alshehri, et al.. (2018). Location Privacy Challenges in Spatial Crowdsourcing. 14. 564–569. 8 indexed citations

17.

Alshehri, Ali, Hani Alshahrani, Abdulrahman Alzahrani, Raed Alharthi, & Esam Aloufi. (2018). The Potential of Utilizing Mobile Cloud Computing in Mobile Devices. 5. 1328–1331. 2 indexed citations

18.

Alzahrani, Abdulrahman, Ali Alshehri, Hani Alshahrani, et al.. (2018). RanDroid: Structural Similarity Approach for Detecting Ransomware Applications in Android Platform. 892–897. 28 indexed citations

19.

Alzahrani, Abdulrahman, et al.. (2018). T-PAAD: Trajectory Privacy Attack on Autonomous Driving. 7 indexed citations

20.

Alshahrani, Hani, Abdulrahman Alzahrani, Ali Alshehri, Raed Alharthi, & Huirong Fu. (2017). Evaluation of Gradient Descent Optimization: Using Android Applications in Neural Networks. 1471–1476. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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