Autopolicy: Automated Traffic Policing for Improved IoT Network Security

Foremski, Paweł; Nowak, Sławomir; Fröhlich, Piotr; Hernández-Ramos, José L.; Baldini, Gianmarco

doi:10.3390/s20154265

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…Systems use cameras and sensors to automatically detect and enforce traffic violations such as speeding, red-light running, and illegal parking [90]. These systems are often used to improve public safety by reducing the number of accidents caused by irresponsible driving.…”

Section: Automated Traffic Enforcement (Ate)mentioning

confidence: 99%

Global Models of Smart Cities and Potential IoT Applications: A Review

Hassebo,

Tealab

2023

IoT

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As the world becomes increasingly urbanized, the development of smart cities and the deployment of IoT applications will play an essential role in addressing urban challenges and shaping sustainable and resilient urban environments. However, there are also challenges to overcome, including privacy and security concerns, and interoperability issues. Addressing these challenges requires collaboration between governments, industry stakeholders, and citizens to ensure the responsible and equitable implementation of IoT technologies in smart cities. The IoT offers a vast array of possibilities for smart city applications, enabling the integration of various devices, sensors, and networks to collect and analyze data in real time. These applications span across different sectors, including transportation, energy management, waste management, public safety, healthcare, and more. By leveraging IoT technologies, cities can optimize their infrastructure, enhance resource allocation, and improve the quality of life for their citizens. In this paper, eight smart city global models have been proposed to guide the development and implementation of IoT applications in smart cities. These models provide frameworks and standards for city planners and stakeholders to design and deploy IoT solutions effectively. We provide a detailed evaluation of these models based on nine smart city evaluation metrics. The challenges to implement smart cities have been mentioned, and recommendations have been stated to overcome these challenges.

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Section: Automated Traffic Enforcement (Ate)mentioning

confidence: 99%

Global Models of Smart Cities and Potential IoT Applications: A Review

Hassebo,

Tealab

2023

IoT

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“…A device can have multiple rules, describing different actions to counter an attack against a vulnerability. We assume a mechanism as the one described in (Foremski et al, 2020) is used to monitor device types and identities while unidentified devices are automatically assigned to an 'unprofiled' category.…”

Section: I/o Data For the Pointer Network Mechanismmentioning

confidence: 99%

IoT threat mitigation engine empowered by artificial intelligence multi-objective optimization

Mpatziakas

Drosou

Papadopoulos

et al. 2022

Journal of Network and Computer Applications

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“…As Amazon suffers 2.3 Tbps of DDoS attacks launched from thousands of hijacked IoT devices. One way to avert this situation is the Auto policy system [170]. The system limits the device bandwidth usage and other network resources.…”

Section: E Dynamic Policy Updatementioning

confidence: 99%

Role of Device Identification and Manufacturer Usage Description in IoT Security: A Survey

et al. 2021

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This paper presents an overview of device identification techniques and the Manufacturer Usage Description (MUD) standard used for the Internet of things to reduce the IoT attack surface. The ongoing diversity and the sheer increase in the number of connected IoT devices have crumpled security efforts. There is a need to reconsider and redesign the underlying concept of developing security systems to resolve IoT security challenges. In this backdrop, device profiling and identification have emerged as an exciting technique that helps to reduce IoT device attack surface. One of the known approaches for device identification is to fingerprint a device. There are many ways to fingerprint the device, mostly using device network flows or device local attributes. The device identification ensures the authenticity of the device attached to the network, like user authentication. Since IoT devices mostly work using machine-to-machine (M2M) communication, this requires identifying each device properly. But there is no unified approach for device identification for the ever-growing world of IoT devices and applications. One of the major steps forward in this direction is the development of the Manufacturer Usage Description (MUD) standard that defines the role of a device within the network. It limits the device to execute the primary task only, which will help to reduce the attack surface. Since the inception of MUD, many security frameworks use this standard for IoT security. However, there is a need to scrutinize the security frameworks based on the MUD, to find out the claimed effectiveness of the standard in IoT security. This paper initially identifies and classifies the potential vulnerabilities in IoT devices. Then, the study provides an overview of the research that focuses on device identification techniques and analyzes their role in IoT security. Finally, the research presents an overview of MUD technology, its implementation scenarios, the limitation of the latest MUD standard, and its applications in the industry. The prime aim of this work is to examine the MUD benefits in IoT security along with the weaknesses and challenges while implementing this standard along with future directions. INDEX TERMSManufacturer usage description (MUD), Internet of Things (IoT), device identification (DI), software defined network (SDN), machine learning (ML), deep learning (DL). NOMAN MAZHAR received the B.E. degree in software engineering and the M.S. degree in information technology from the

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Autopolicy: Automated Traffic Policing for Improved IoT Network Security

Cited by 6 publications

References 27 publications

Global Models of Smart Cities and Potential IoT Applications: A Review

Global Models of Smart Cities and Potential IoT Applications: A Review

IoT threat mitigation engine empowered by artificial intelligence multi-objective optimization

Role of Device Identification and Manufacturer Usage Description in IoT Security: A Survey

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