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20182026
most citedMachine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats

154 citations · 445 across the 69 of their papers we have counts for

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Showing 2022Show all

10 papers · 1 filter

cs.NI2022★ 3 cited

Cooperate or not Cooperate: Transfer Learning with Multi-Armed Bandit for Spatial Reuse in Wi-Fi

Pedro Enrique Iturria-Rivera, Marcel Chenier, Bernard Herscovici +2

The exponential increase of wireless devices with highly demanding services such as streaming video, gaming and others has imposed several challenges to Wireless Local Area Network…

cs.CV2022

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…

cs.CV2022★ 3 cited

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…

cs.CR2022★ 35 cited

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…

cs.CR2022★ 12 cited

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…

cs.CR2022★ 7 cited

Adversarial Machine Learning-Based Anticipation of Threats Against Vehicle-to-Microgrid Services

Ahmed Omara, Burak Kantarci

In this paper, we study the expanding attack surface of Adversarial Machine Learning (AML) and the potential attacks against Vehicle-to-Microgrid (V2M) services. We present an anti…

cs.CR2022★ 154 cited

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…

cs.CV2022★ 9 cited

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…

cs.NE2022★ 7 cited

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…

cs.CR2022

Generative Adversarial Network-Driven Detection of Adversarial Tasks in Mobile Crowdsensing

Zhiyan Chen, Burak Kantarci

Mobile Crowdsensing systems are vulnerable to various attacks as they build on non-dedicated and ubiquitous properties. Machine learning (ML)-based approaches are widely investigat…