Regional Short‐Term Wind Power Prediction Based on CEEMDAN‐FTC Feature Mapping and EC‐TCN‐BiLSTM Deep Learning by Guoyuan Qin, Xiaosheng Peng, Zimin Yang

“…Third, by combining the strengths of TCN and BiLSTM neural networks, the temporal and spatial correlations of input features can be captured effectively. …”
Get full text

Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

Get full text

A hybrid model for fake news detection: Leveraging news content and user comments in fake news by Marwan Albahar

Get full text

Security monitoring via sound analysis and voice identification with artificial intelligence by Balabanova Ivelina, Sidorova Kristina, Georgiev Georgi

“…Successful correct recognition of the test voice profiles on access and security personalization with a quantitative equivalent of 100.0 % accuracy was achieved in the Linear transfer function for Cascade-Forward Neural Networks. …”
Get full text

HCAP: Hybrid cyber attack prediction model for securing healthcare applications. by Mohanad Faeq Ali, Mohammed Shakir Mohmood, Ban Salman Shukur, Rex Bacarra, Jamil Abedalrahim Jamil Alsayaydeh, Masrullizam Mat Ibrahim, Safarudin Gazali Herawan

“…The extracted features are fed into the lion-optimization technique to fine-tune the hyperparameters of the recurrent neural networks, enhancing the model's ability to efficiently predict cybersecurity threats with a maximum recognition rate in IoMT environments. …”
Get full text

Group feature calibration for sound event detection by Yanzhen Ren, Wuyang Liu, Chenyu Liu, Tingting Zhu

Get full text

A Hybrid Deep Learning Approach for Secure Biometric Authentication Using Fingerprint Data by Abdulrahman Hussian, Foud Murshed, Mohammed Nasser Alandoli, Ghalib Aljafari

“…Addressing these limitations is crucial for ensuring reliable biometric security in real-world applications, including law enforcement, financial transactions, and border security. …”
Get full text

DynBlock: dynamic data encryption with Toffoli gate for IoT by Mubasher Haq, Ijaz Ali Shoukat, Alamgir Naushad, Mohsin Raza Jafri, Moid Sandhu, Abd Ullah Khan, Hyundong Shin

“…We evaluate DynBlock with both 3 and 5 rounds to assess its security and computational efficiency. While the 5-round configuration offers stronger resistance to cryptanalytic attacks, the 3-round setup already delivers robust security, featuring high entropy and a strong avalanche effect, making it well-suited for resource-constrained environments. …”
Get full text

CRIMINOLOGICAL FEATURES ORGANIZED COUNTERFEITING IN THE DIGITAL AGE by Jamaludin Kh. Umakhanov, Maya G. Dieva

Get full text

Overview of detection techniques for malicious social bots by Rong LIU, Bo CHEN, Ling YU, Ya-shang LIU, Si-yuan CHEN

“…The attackers use social bots to steal people’s privacy,propagate fraud messages and influent public opinions,which has brought a great threat for personal privacy security,social public security and even the security of the nation.The attackers are also introducing new techniques to carry out anti-detection.The detection of malicious social bots has become one of the most important problems in the research of online social network security and it is also a difficult problem.Firstly,development and application of social bots was reviewed and then a formulation description for the problem of detecting malicious social bots was made.Besides,main challenges in the detection of malicious social bots were analyzed.As for how to choose features for the detection,the development of choosing features that from static user features to dynamic propagation features and to relationship and evolution features were classified.As for choosing which method,approaches from the previous research based on features,machine learning,graph and crowd sourcing were summarized.Also,the limitation of these methods in detection accuracy,computation cost and so on was dissected.At last,a framework based on parallelizing machine learning methods to detect malicious social bots was proposed.…”
Get full text

Overview of detection techniques for malicious social bots by Rong LIU, Bo CHEN, Ling YU, Ya-shang LIU, Si-yuan CHEN

“…The attackers use social bots to steal people’s privacy,propagate fraud messages and influent public opinions,which has brought a great threat for personal privacy security,social public security and even the security of the nation.The attackers are also introducing new techniques to carry out anti-detection.The detection of malicious social bots has become one of the most important problems in the research of online social network security and it is also a difficult problem.Firstly,development and application of social bots was reviewed and then a formulation description for the problem of detecting malicious social bots was made.Besides,main challenges in the detection of malicious social bots were analyzed.As for how to choose features for the detection,the development of choosing features that from static user features to dynamic propagation features and to relationship and evolution features were classified.As for choosing which method,approaches from the previous research based on features,machine learning,graph and crowd sourcing were summarized.Also,the limitation of these methods in detection accuracy,computation cost and so on was dissected.At last,a framework based on parallelizing machine learning methods to detect malicious social bots was proposed.…”
Get full text

Integration of data science with the intelligent IoT (IIoT): Current challenges and future perspectives by Inam Ullah, Deepak Adhikari, Xin Su, Francesco Palmieri, Celimuge Wu, Chang Choi

Get full text

A Cloud User Anomaly Detection Method Based on Mouse Behavior by XU Hong-jun, ZHANG Hong, HE Wei

Get full text

Deep Fusion Intelligence: Enhancing 5G Security Against Over-the-Air Attacks by Mohammadreza Amini, Ghazal Asemian, Burak Kantarci, Cliff Ellement, Melike Erol-Kantarci

Get full text

A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

Get full text

A lightweight speaker verification approach for autonomous vehicles by Yousef Salah, Omar Shalash, Esraa Khatab

Get full text

SH-SDS: a new static-dynamic strategy for substation host security detection by Yang Diao, Hui Chen, Wei Liu, Abdur Rasool

Get full text

Mapping Grayscale Images to Colour Space Using Deep Learning by Anu Saini, Jyoti Tripathi

Get full text

Robust Network Traffic Classification Based on Information Bottleneck Neural Network by Wei Lin, Yu Chen

Get full text

DDoS classification of network traffic in software defined networking SDN using a hybrid convolutional and gated recurrent neural network by Ahmed M. Elshewey, Safia Abbas, Ahmed M. Osman, Eman Abdullah Aldakheel, Yasser Fouad

Get full text