Detecting Sophisticated Attacks in Maritime Environments using Hybrid Situational Awareness

Schauer, Stefan; Kalogeraki, Eleni Maria; Papastergiou, Spyros; Douligeris, Christos

doi:10.1109/ict-dm47966.2019.9032900

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Malware/Ransomware/Trojans: Generally, the aim of these classes of attacks is to damage the information system or server by targeting the networked computers ( [150][151][152][153][154]). On the 8 July 2019, an attack targeted a US vessel causing critical credential mining.…”

Section: In-port Cyber-attacksmentioning

confidence: 99%

Cyber Security in the Maritime Industry: A Systematic Survey of Recent Advances and Future Trends

et al. 2022

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The paper presents a classification of cyber attacks within the context of the state of the art in the maritime industry. A systematic categorization of vessel components has been conducted, complemented by an analysis of key services delivered within ports. The vulnerabilities of the Global Navigation Satellite System (GNSS) have been given particular consideration since it is a critical subcategory of many maritime infrastructures and, consequently, a target for cyber attacks. Recent research confirms that the dramatic proliferation of cyber crimes is fueled by increased levels of integration of new enabling technologies, such as IoT and Big Data. The trend to greater systems integration is, however, compelling, yielding significant business value by facilitating the operation of autonomous vessels, greater exploitation of smart ports, a reduction in the level of manpower and a marked improvement in fuel consumption and efficiency of services. Finally, practical challenges and future research trends have been highlighted.

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Section: In-port Cyber-attacksmentioning

confidence: 99%

Cyber Security in the Maritime Industry: A Systematic Survey of Recent Advances and Future Trends

et al. 2022

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“…Additionally, WaSR is exceptionally robust in challenging conditions. Maritime environments can be highly unpredictable, with factors like fog, glare, and varying light conditions often impeding visibility [57][58][59]. WaSR's design and integration of IMU data make it adept at navigating these challenges, ensuring accurate segmentation even in less-than-ideal visual conditions.…”

mentioning

confidence: 99%

Urban Aquatic Scene Expansion for Semantic Segmentation in Cityscapes

Yue,

Lo,

et al. 2024

Urban Science

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In urban environments, semantic segmentation using computer vision plays a pivotal role in understanding and interpreting the diverse elements within urban imagery. The Cityscapes dataset, widely used for semantic segmentation in urban scenes, predominantly features urban elements like buildings and vehicles but lacks aquatic elements. Recognizing this limitation, our study introduces a method to enhance the Cityscapes dataset by incorporating aquatic classes, crucial for a comprehensive understanding of coastal urban environments. To achieve this, we employ a dual-model approach using two advanced neural networks. The first network is trained on the standard Cityscapes dataset, while the second focuses on aquatic scenes. We adeptly integrate aquatic features from the marine-focused model into the Cityscapes imagery. This integration is carefully executed to ensure a seamless blend of urban and aquatic elements, thereby creating an enriched dataset that reflects the realities of coastal cities more accurately. Our method is evaluated by comparing the enhanced Cityscapes model with the original on a set of diverse urban images, including aquatic views. The results demonstrate that our approach effectively maintains the high segmentation accuracy of the original Cityscapes dataset for urban elements while successfully integrating marine features. Importantly, this is achieved without necessitating additional training, which is a significant advantage in terms of resource efficiency.

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