154 citations · 292 across the 22 of their papers we have counts for
22 papers
On-Dyn-CDA: A Real-Time Cost-Driven Task Offloading Algorithm for Vehicular Networks with Reduced Latency and Task Loss
Mahsa Paknejad, Parisa Fard Moshiri, Murat Simsek +2
Real-time task processing is a critical challenge in vehicular networks, where achieving low latency and minimizing dropped task ratio depend on efficient task execution. Our prima…
Meeting Deadlines in Motion: Deep RL for Real-Time Task Offloading in Vehicular Edge Networks
Mahsa Paknejad, Parisa Fard Moshiri, Murat Simsek +2
Vehicular Mobile Edge Computing (VEC) drives the future by enabling low-latency, high-efficiency data processing at the very edge of vehicular networks. This drives innovation in k…
A Reliable and Efficient 5G Vehicular MEC: Guaranteed Task Completion with Minimal Latency
Mahsa Paknejad, Parisa Fard Moshiri, Murat Simsek +2
This paper explores the advancement of Vehicular Edge Computing (VEC) as a tailored application of Mobile Edge Computing (MEC) for the automotive industry, addressing the rising de…
Partitioned Task Offloading for Low-Latency and Reliable Task Completion in 5G MEC
Parisa Fard Moshiri, Murat Simsek, Burak Kantarci
The demand for MEC has increased with the rise of data-intensive applications and 5G networks, while conventional cloud models struggle to satisfy low-latency requirements. While t…
Joint Optimization of Completion Ratio and Latency of Offloaded Tasks with Multiple Priority Levels in 5G Edge
Parisa Fard Moshiri, Murat Simsek, Burak Kantarci
Multi-Access Edge Computing (MEC) is widely recognized as an essential enabler for applications that necessitate minimal latency. However, the dropped task ratio metric has not bee…
On the Interplay Between Network Metrics and Performance of Mobile Edge Offloading
Parisa Fard Moshiri, Murat Simsek, Burak Kantarci
Multi-Access Edge Computing (MEC) emerged as a viable computing allocation method that facilitates offloading tasks to edge servers for efficient processing. The integration of MEC…
Rethinking Detection Based Table Structure Recognition for Visually Rich Document Images
Bin Xiao, Murat Simsek, Burak Kantarci +1
Table Structure Recognition (TSR) is a widely discussed task aiming at transforming unstructured table images into structured formats, such as HTML sequences, to make text-only mod…
Multidomain transformer-based deep learning for early detection of network intrusion
Jinxin Liu, Murat Simsek, Michele Nogueira +1
Timely response of Network Intrusion Detection Systems (NIDS) is constrained by the flow generation process which requires accumulation of network packets. This paper introduces Mu…
Host-Based Network Intrusion Detection via Feature Flattening and Two-stage Collaborative Classifier
Zhiyan Chen, Murat Simsek, Burak Kantarci +2
Network Intrusion Detection Systems (NIDS) have been extensively investigated by monitoring real network traffic and analyzing suspicious activities. However, there are limitations…
Table Detection for Visually Rich Document Images
Bin Xiao, Murat Simsek, Burak Kantarci +1
Table Detection (TD) is a fundamental task to enable visually rich document understanding, which requires the model to extract information without information loss. However, popula…
Revisiting Table Detection Datasets for Visually Rich Documents
Bin Xiao, Murat Simsek, Burak Kantarci +1
Table Detection has become a fundamental task for visually rich document understanding with the surging number of electronic documents. However, popular public datasets widely used…
Efficient Information Sharing in ICT Supply Chain Social Network via Table Structure Recognition
Bin Xiao, Yakup Akkaya, Murat Simsek +2
The global Information and Communications Technology (ICT) supply chain is a complex network consisting of all types of participants. It is often formulated as a Social Network to…
Handling big tabular data of ICT supply chains: a multi-task, machine-interpretable approach
Bin Xiao, Murat Simsek, Burak Kantarci +1
Due to the characteristics of Information and Communications Technology (ICT) products, the critical information of ICT devices is often summarized in big tabular data shared acros…
Prior Knowledge based Advanced Persistent Threats Detection for IoT in a Realistic Benchmark
Yu Shen, Murat Simsek, Burak Kantarci +3
The number of Internet of Things (IoT) devices being deployed into networks is growing at a phenomenal level, which makes IoT networks more vulnerable in the wireless medium. Advan…
Collaborative Feature Maps of Networks and Hosts for AI-driven Intrusion Detection
Jinxin Liu, Murat Simsek, Burak Kantarci +2
Intrusion Detection Systems (IDS) are critical security mechanisms that protect against a wide variety of network threats and malicious behaviors on networks or hosts. As both Netw…
Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats
Zhiyan Chen, Jinxin Liu, Yu Shen +4
Despite its technological benefits, Internet of Things (IoT) has cyber weaknesses due to the vulnerabilities in the wireless medium. Machine learning (ML)-based methods are widely…
Table Structure Recognition with Conditional Attention
Bin Xiao, Murat Simsek, Burak Kantarci +1
Tabular data in digital documents is widely used to express compact and important information for readers. However, it is challenging to parse tables from unstructured digital docu…
Collaborative Self Organizing Map with DeepNNs for Fake Task Prevention in Mobile Crowdsensing
Murat Simsek, Burak Kantarci, Azzedine Boukerche
Mobile Crowdsensing (MCS) is a sensing paradigm that has transformed the way that various service providers collect, process, and analyze data. MCS offers novel processes where dat…
On Cropped versus Uncropped Training Sets in Tabular Structure Detection
Yakup Akkaya, Murat Simsek, Burak Kantarci +1
Automated document processing for tabular information extraction is highly desired in many organizations, from industry to government. Prior works have addressed this problem under…
Risk-Aware Fine-Grained Access Control in Cyber-Physical Contexts
Jinxin Liu, Murat Simsek, Burak Kantarci +3
Access to resources by users may need to be granted only upon certain conditions and contexts, perhaps particularly in cyber-physical settings. Unfortunately, creating and modifyin…
Federated Learning-Based Risk-Aware Decision toMitigate Fake Task Impacts on CrowdsensingPlatforms
Zhiyan Chen, Murat Simsek, Burak Kantarci
Mobile crowdsensing (MCS) leverages distributed and non-dedicated sensing concepts by utilizing sensors imbedded in a large number of mobile smart devices. However, the openness an…
Prior Knowledge Input to Improve LSTM Auto-encoder-based Characterization of Vehicular Sensing Data
Nima Taherifard, Murat Simsek, Charles Lascelles +1
Precision in event characterization in connected vehicles has become increasingly important with the responsive connectivity that is available to the modern vehicles. Event charact…