Visible to the public Biblio

Filters: Keyword is data analytics techniques  [Clear All Filters]
2020-02-17
Rodriguez, Ariel, Okamura, Koji.  2019.  Generating Real Time Cyber Situational Awareness Information Through Social Media Data Mining. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 2:502–507.
With the rise of the internet many new data sources have emerged that can be used to help us gain insights into the cyber threat landscape and can allow us to better prepare for cyber attacks before they happen. With this in mind, we present an end to end real time cyber situational awareness system which aims to efficiently retrieve security relevant information from the social networking site Twitter.com. This system classifies and aggregates the data retrieved and provides real time cyber situational awareness information based on sentiment analysis and data analytics techniques. This research will assist security analysts to evaluate the level of cyber risk in their organization and proactively take actions to plan and prepare for potential attacks before they happen as well as contribute to the field through a cybersecurity tweet dataset.
2018-02-06
Iqbal, H., Ma, J., Mu, Q., Ramaswamy, V., Raymond, G., Vivanco, D., Zuena, J..  2017.  Augmenting Security of Internet-of-Things Using Programmable Network-Centric Approaches: A Position Paper. 2017 26th International Conference on Computer Communication and Networks (ICCCN). :1–6.

Advances in nanotechnology, large scale computing and communications infrastructure, coupled with recent progress in big data analytics, have enabled linking several billion devices to the Internet. These devices provide unprecedented automation, cognitive capabilities, and situational awareness. This new ecosystem–termed as the Internet-of-Things (IoT)–also provides many entry points into the network through the gadgets that connect to the Internet, making security of IoT systems a complex problem. In this position paper, we argue that in order to build a safer IoT system, we need a radically new approach to security. We propose a new security framework that draws ideas from software defined networks (SDN), and data analytics techniques; this framework provides dynamic policy enforcements on every layer of the protocol stack and can adapt quickly to a diverse set of industry use-cases that IoT deployments cater to. Our proposal does not make any assumptions on the capabilities of the devices - it can work with already deployed as well as new types of devices, while also conforming to a service-centric architecture. Even though our focus is on industrial IoT systems, the ideas presented here are applicable to IoT used in a wide array of applications. The goal of this position paper is to initiate a dialogue among standardization bodies and security experts to help raise awareness about network-centric approaches to IoT security.