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Aaron Yi Ding

Publications and source records attributed to Aaron Yi Ding.

22 records · Page 2Linked to original sources

Toward Secure Edge Networks Taming Device to Device (D2D) Communication in IoT

The growing popularity of Internet-of-Things (IoT) has created the need for network-based traffic anomaly detection systems that could identify misbehaving devices. In this work, we propose a lightweight technique, IoT-guard, for identifying malicious traffic flows. IoT-guard uses semi-supervised learning to distinguish between malicious and benign device behaviours using the network traffic generated by devices. In order to achieve this, we extracted 39 features from network logs and discard any features containing redundant information. After feature selection, fuzzy C-Mean (FCM) algorithm was trained to obtain clusters discriminating benign traffic from malicious traffic. We studied the feature scores in these clusters and use this information to predict the type of new traffic flows. IoT-guard was evaluated using a real-world testbed with more than 30 devices. The results show that IoTguard achieves high accuracy (98%), in differentiating various types of malicious and benign traffic, with low false positive rates. Furthermore, it has low resource footprint and can operate on OpenWRT enabled access points and COTS computing boards.

cs.CR↗

5G Applications: Requirements, Challenges, and Outlook

The increasing demand for mobile network capacity driven by Internet of Things (IoT) applications results in the need for understanding better the potential and limitations of 5G networks. Vertical application areas like smart mobility, energy networks, industrial IoT applications, and AR/VR enhanced services all pose different requirements on the use of 5G networks. Some applications need low latency, whereas others need high bandwidth or security support. The goal of this paper is to identify the requirements and to understand the limitations for 5G driven applications. We review application areas and list the typical challenges and requirements posed on 5G networks. A main challenge will be to develop a network architecture being able to dynamically adapt to fluctuating traffic patterns and accommodating various technologies such as edge computing, blockchain based distributed ledger, software defined networking, and virtualization. To inspire future research, we reveal open problems and highlight the need for piloting with 5G applications, with tangible steps, to understand the configuration of 5G networks and the use of applications across multiple vertical industries.

cs.NI↗

Five Driving Forces of Multi-Access Edge Computing

The emergence of Multi-Access Edge Computing (MEC) technology aims at extending cloud computing capabilities to the edge of the wireless access networks. MEC provides real-time, high-bandwidth, low-latency access to radio network resources, allowing operators to open their networks to a new ecosystem and value chain. Moreover, it will provide a new insight to the design of future 5th Generation (5G) wireless systems. This paper describes five key technologies, including Network Function Vitalization (NFV), Software Defined Networking (SDN), Network Slicing, Information Centric Networking (ICN) and Internet of Things (IoT), that intensify the widespread of MEC and its adoption. Our goal is to provide the associativity between MEC and these five driving technologies in 5G context while identifying the open challenges, future directions, and tangible integration paths.

cs.NI↗

Securing Edge Networks with Securebox

The number of mobile and IoT devices connected to home and enterprise networks is growing fast. These devices offer new services and experiences for the users; however, they also present new classes of security threats pertaining to data and device safety and user privacy. In this article, we first analyze the potential threats presented by these devices connected to edge networks. We then propose Securebox: a new cloud-driven, low cost Security-as-a-Service solution that applies Software-Defined Networking (SDN) to improve network monitoring, security and management. Securebox enables remote management of networks through a cloud security service (CSS) with minimal user intervention required. To reduce costs and improve the scalability, Securebox is based on virtualized middleboxes provided by CSS. Our proposal differs from the existing solutions by integrating the SDN and cloud into a unified edge security solution, and by offering a collaborative protection mechanism that enables rapid security policy dissemination across all connected networks in mitigating new threats or attacks detected by the system. We have implemented two Securebox prototypes, using a low-cost Raspberry-PI and off-the-shelf fanless PC. Our system evaluation has shown that Securebox can achieve automatic network security and be deployed incrementally to the infrastructure with low management overhead.

cs.CR↗