Outputs (18)

A Novel Web Attack Detection System for Internet of Things via Ensemble Classification (2020)
Journal Article
Luo, C., Tan, Z., Min, G., Gan, J., Shi, W., & Tian, Z. (2021). A Novel Web Attack Detection System for Internet of Things via Ensemble Classification. IEEE Transactions on Industrial Informatics, 17(8), 5810-5818. https://doi.org/10.1109/tii.2020.3038761

Internet of things (IoT) has become one of the fastestgrowing technologies and has been broadly applied in various fields. IoT networks contain millions of devices with the capability of interacting with each other and providing functionalities that... Read More about A Novel Web Attack Detection System for Internet of Things via Ensemble Classification.

A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network (2020)
Presentation / Conference Contribution
Thomson, C., Wadhaj, I., Al-Dubai, A., & Tan, Z. (2020, April). A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network. Presented at IEEE 6th World Forum on Internet of Things, New Orleans, Louisiana, USA

The issue of energy holes, or hotspots, in wireless sensor networks is well referenced. As is the proposed mobilisa-tion of the sink node in order to combat this. However, as the sink node shall still pass some nodes more closely and frequently than... Read More about A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network.

Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection (2020)
Journal Article
Tian, Z., Shi, W., Tan, Z., Qiu, J., Sun, Y., Jiang, F., & Liu, Y. (online). Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection. Mobile Networks and Applications, https://doi.org/10.1007/s11036-020-01656-7

Organizations' own personnel now have a greater ability than ever before to misuse their access to critical organizational assets. Insider threat detection is a key component in identifying rare anomalies in context, which is a growing concern for ma... Read More about Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection.

A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading (2020)
Journal Article
Zhao, L., Yang, K., Tan, Z., Li, X., Sharma, S., & Liu, Z. (2021). A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading. IEEE Transactions on Intelligent Transportation Systems, 22(6), 3664-3674. https://doi.org/10.1109/TITS.2020.3024186

Vehicular computation offloading is a well-received strategy to execute delay-sensitive and/or compute-intensive tasks of legacy vehicles. The response time of vehicular computation offloading can be shortened by using mobile edge computing that offe... Read More about A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading.

Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples (2020)
Presentation / Conference Contribution
Babaagba, K., Tan, Z., & Hart, E. (2020, July). Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. Presented at The 2020 IEEE Congress on Evolutionary Computation (IEEE CEC 2020), Glasgow, UK

Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this, we explore whether machine-learning models can be improved by augmenting t... Read More about Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples.

Evaluation of Ensemble Learning for Android Malware Family Identification (2020)
Journal Article
Wylie, J., Tan, Z., Al-Dubai, A., & Wang, J. (2020). Evaluation of Ensemble Learning for Android Malware Family Identification. Journal of Guangzhou University (Natural Science Edition), 19(4), 28-41

Every Android malware sample generally belongs to a specific family that performs a similar set of actions and characteristics. Having the ability to effectively identify Android malware families can assist in addressing the damage caused by malware.... Read More about Evaluation of Ensemble Learning for Android Malware Family Identification.

Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment (2020)
Journal Article
Zhao, L., Huang, H., Su, C., Ding, S., Huang, H., Tan, Z., & Li, Z. (2021). Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment. IEEE Internet of Things Journal, 8(5), 3211-3223. https://doi.org/10.1109/jiot.2020.3019732

Device-free localization (DFL) locates targets without equipping with wireless devices or tag under the Internet-of-Things (IoT) architectures. As an emerging technology, DFL has spawned extensive applications in IoT environment, such as intrusion de... Read More about Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment.

FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture (2020)
Journal Article
Song, J., Zhong, Q., Su, C., Tan, Z., & Liu, Y. (2021). FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture. IEEE Sensors Journal, 21(16), 17430-17438. https://doi.org/10.1109/JSEN.2020.3017695

Food security is a global concern. Benefit from the development of 5G, IoT is used in agriculture to help the farmers to maintain and improve productivity. It not only enables the customers, both at home and abroad, to become more informed about the... Read More about FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture.

IEEE Access Special Section Editorial: Security and Trusted Computing for Industrial Internet of Things: Research Challenges and Opportunities (2020)
Journal Article
Li, S., Choo, K.-K. R., Tan, Z., He, X., Hu, J., & Qin, T. (2020). IEEE Access Special Section Editorial: Security and Trusted Computing for Industrial Internet of Things: Research Challenges and Opportunities. IEEE Access, 8, 145033-145036. https://doi.org/10.1109/access.2020.3014416

Industrial IoT (IIoT) interconnects critical devices and sensors in critical infrastructure sectors with existing Internet of Things (IoT) devices and applications. Generally, IIoT deployment allows organizations and users to gain invaluable insights... Read More about IEEE Access Special Section Editorial: Security and Trusted Computing for Industrial Internet of Things: Research Challenges and Opportunities.

On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining (2020)
Journal Article
Cha, S.-C., Wang, H., Tan, Z., Joung, Y.-J., Tseng, Y.-C., & Yeh, K.-H. (2020). On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(5), 641-652. https://doi.org/10.1109/tetci.2019.2938547

Intelligence mining is one of the most promising technologies for effectively extracting intelligence (and knowledge) to enhance the quality of decision-making. In Taiwan, the government curtails underground economic activities and facilitates tax ma... Read More about On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining.

Deep learning based emotion analysis of microblog texts (2020)
Journal Article
Xu, D., Tian, Z., Lai, R., Kong, X., Tan, Z., & Shi, W. (2020). Deep learning based emotion analysis of microblog texts. Information Fusion, 64, 1-11. https://doi.org/10.1016/j.inffus.2020.06.002

Traditional text emotion analysis methods are primarily devoted to studying extended texts, such as news reports and full-length documents. Microblogs are considered short texts that are often characterized by large noises, new words, and abbreviatio... Read More about Deep learning based emotion analysis of microblog texts.

Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites (2020)
Presentation / Conference Contribution
Babaagba, K. O., Tan, Z., & Hart, E. (2020, April). Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites. Presented at EvoStar 2020, Seville, Spain

In the field of metamorphic malware detection, training a detection model with malware samples that reflect potential mutants of the malware is crucial in developing a model resistant to future attacks. In this paper, we use a Multi-dimensional Archi... Read More about Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites.

Exploring coupled images fusion based on joint tensor decomposition (2020)
Journal Article
Lu, L., Ren, X., Yeh, K.-H., Tan, Z., & Chanussot, J. (2020). Exploring coupled images fusion based on joint tensor decomposition. Human-Centric Computing and Information Sciences, 10, Article 10 (2020). https://doi.org/10.1186/s13673-020-00215-z

Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the e... Read More about Exploring coupled images fusion based on joint tensor decomposition.

KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data (2020)
Journal Article
Zhu, R., Ji, X., Yu, D., Tan, Z., Zhao, L., Li, J., & Xia, X. (2020). KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data. IEEE Access, 8, 42749-42759. https://doi.org/10.1109/access.2020.2977114

KNN-Based outlier detection over IoT streaming data is a fundamental problem, which has many applications. However, due to its computational complexity, existing efforts cannot efficiently work in the IoT streaming data. In this paper, we propose a n... Read More about KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data.

Secure Information Transmissions in Wireless-powered Cognitive Radio Networks for Internet of Medical Things (2020)
Journal Article
Tang, K., Tang, W., Luo, E., Tan, Z., Meng, W., & Qi, L. (2020). Secure Information Transmissions in Wireless-powered Cognitive Radio Networks for Internet of Medical Things. Security and Communication Networks, 2020, Article 7542726. https://doi.org/10.1155/2020/7542726

In this paper, we consider the issue of the secure transmissions for the cognitive radio-based Internet of Medical Things (IoMT) with wireless energy harvesting. In these systems, a primary transmitter (PT) will transmit its sensitive medical informa... Read More about Secure Information Transmissions in Wireless-powered Cognitive Radio Networks for Internet of Medical Things.

FIMPA: A Fixed Identity Mapping Prediction Algorithm in Edge Computing Environment (2020)
Journal Article
Zhang, S., Liu, Y., Li, S., Tan, Z., Zhao, X., & Zhou, J. (2020). FIMPA: A Fixed Identity Mapping Prediction Algorithm in Edge Computing Environment. IEEE Access, 8, 17356-17365. https://doi.org/10.1109/access.2020.2966399

Edge computing is a research hotspot that extends cloud computing to the edge of the network. Due to the recent developments in computation, storage and network technology for end devices, edge networks have become more powerful, making it possible t... Read More about FIMPA: A Fixed Identity Mapping Prediction Algorithm in Edge Computing Environment.

FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks (2020)
Journal Article
Lai, S., Fan, X., Ye, Q., Tan, Z., Zhang, Y., He, X., & Nanda, P. (2020). FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks. IEEE Access, 8, 13516-13526. https://doi.org/10.1109/access.2020.2965562

Mobile cloud computing has emerged as a promising paradigm to facilitate computation-intensive and delay-sensitive mobile applications. Computation offloading services at the edge mobile cloud environment are provided by small-scale cloud infrastruct... Read More about FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks.

Double-Arc Parallel Coordinates and its Axes re-Ordering Methods (2020)
Journal Article
Lu, L., Wang, W., & Tan, Z. (2020). Double-Arc Parallel Coordinates and its Axes re-Ordering Methods. Mobile Networks and Applications, 25(4), 1376-1391. https://doi.org/10.1007/s11036-019-01455-9

The Parallel Coordinates Plot (PCP) is a popular technique for the exploration of high-dimensional data. In many cases, researchers apply it as an effective method to analyze and mine data. However, when today's data volume is getting larger, visual... Read More about Double-Arc Parallel Coordinates and its Axes re-Ordering Methods.