Visible to the public Biblio

Filters: Keyword is Smart industry  [Clear All Filters]
2019-12-02
Chi, Po-Wen, Wang, Ming-Hung.  2018.  A Lightweight Compound Defense Framework Against Injection Attacks in IIoT. 2018 IEEE Conference on Dependable and Secure Computing (DSC). :1–8.
Industrial Internet of Things (IIoT) is a trend of the smart industry. By collecting field data from sensors, the industry can make decisions dynamically in time for better performance. In most cases, IIoT is built on private networks and cannot be reached from the Internet. Currently, data transmission in most of IIoT network protocols is in plaintext without encryption protection. Once an attacker breaks into the field, the attacker can intercept data and injects malicious commands to field agents. In this paper, we propose a compound approach for defending command injection attacks in IIOT. First, we leverage the power of Software Defined Networking (SDN) to detect the injection attack. When the injection attack event is detected, the system owner is alarmed that someone tries to pretend a controller or a field agent to deceive the other entity. Second, we develop a lightweight authentication scheme to ensure the identity of the command sender. Command receiver can verify commands first before processing commands.
2018-11-19
Langfinger, M., Schneider, M., Stricker, D., Schotten, H. D..  2017.  Addressing Security Challenges in Industrial Augmented Reality Systems. 2017 IEEE 15th International Conference on Industrial Informatics (INDIN). :299–304.

In context of Industry 4.0 Augmented Reality (AR) is frequently mentioned as the upcoming interface technology for human-machine communication and collaboration. Many prototypes have already arisen in both the consumer market and in the industrial sector. According to numerous experts it will take only few years until AR will reach the maturity level to be deployed in productive applications. Especially for industrial usage it is required to assess security risks and challenges this new technology implicates. Thereby we focus on plant operators, Original Equipment Manufacturers (OEMs) and component vendors as stakeholders. Starting from several industrial AR use cases and the structure of contemporary AR applications, in this paper we identify security assets worthy of protection and derive the corresponding security goals. Afterwards we elaborate the threats industrial AR applications are exposed to and develop an edge computing architecture for future AR applications which encompasses various measures to reduce security risks for our stakeholders.