Overview
The threats to the cybersecurity of today’s organizations’ networks are numerous, vastly varied and constantly evolving. According to a very recent report, about 81 percent of US organizations have faced a cyberattack. Operational downtime was the biggest impact for those organizations (55 percent), followed by compromised customer data (37 percent), and compromised end-user safety (36 percent). Most recently, the COVID-19 pandemic has reared its ugly head – cyberattacks have become more common and have large increased very recently. However, the scale of contemporary network traffic volumes makes monitoring and visualizing real-time information considerably more challenging for human ability to process [8]. Although many IDSs utilizes several visualization techniques and notification mechanisms to provide administrators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way, and it is quite difficult to understand the relevance of aggregate traffic when receiving only the alarms for individual intrusion records. Moreover, these tools are not well suited for continuous monitoring scenarios since network administrators will suffer from loss of concentration, visual fatigue, temporal demand, and frustration increase.
In this project, we aim at designing and exploring the effectiveness of a real-time ”haptification” system for monitoring computer network traffic to support network administrators’ situational awareness through feeling the state of network traffic. In our proposed project, haptification refers to the process by which different traffic flows and the network environment are transformed into haptic-enabled sensing at different body locations, and the combinations of feelings represent the current state of the network. The system is intended to enable network administrators to perceive in real-time the state of each traffic flow in order to assist with the maintenance of security, awareness of anomalous events such as attacks, maintenance of network health through monitoring and tuning, and increasing the understanding of the cyber environment which is vital for network management in the situational awareness process. Haptic-enabled sensing should enable the network administrator to differentiate between normal and anomalous network behavior and to develop an understanding of what is actually happening in the network. What makes the proposed system distinctive compared to other available tools is that it allows the user to monitor general and specific behaviors in a human understandable form.
People
PI
PhD Student
- Mohammed Ayyat
Funding
- CCI VV-1Q23-010: “NetworkTouch - Towards Haptics for Network Traffic Monitoring and Situational Awareness”