Sonification of Network Traffic Flow for Monitoring and Situational Awareness

Maintaining situational awareness of what is happening within a network is challenging, not least because the behaviour happens within computers and communications networks, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation is widely used to present information about the dynamics of network traffic dynamics. Although it provides operators with an overall view and specific information about particular traffic or attacks on the network, it often fails to represent the events in an understandable way. Visualisations require visual attention and so are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Situational awareness is critical and essential for decision-making in the domain of computer network monitoring where it is vital to be able to identify and recognize network environment behaviours.Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system to be used in the monitoring of computer networks to support the situational awareness of network administrators. SoNSTAR provides an auditory representation of all the TCP/IP protocol traffic within a network based on the different traffic flows between between network hosts. SoNSTAR raises situational awareness levels for computer network defence by allowing operators to achieve better understanding and performance while imposing less workload compared to visual techniques. SoNSTAR identifies the features of network traffic flows by inspecting the status flags of TCP/IP packet headers and mapping traffic events to recorded sounds to generate a soundscape representing the real-time status of the network traffic environment. Listening to the soundscape allows the administrator to recognise anomalous behaviour quickly and without having to continuously watch a computer screen.Comment: 17 pages, 7 figures plus supplemental material in Github repositor

Network-based system for acoustic mapping of urban areas

The paper presents both a general idea and basic assumptions of the research project, which was started a year ago at Technical University of Silesia, Poland and primarily has been focused on the Region of Upper Silesia. At present, the project is prepared to cover other regions of the country. In particular, the research area of this project contains the problems of preparing and utilizing the acoustical maps of towns that ought to be prepared in accordance with the EC directive com468 (2000). The main two assumptions of the project are as follows: 1) the maps will be prepared by means of advanced computer-based tools of the GIS and GPS classes, 2) both the procedures of developing and utilizing the acoustical maps will be executed in the form of group-work using the PIONIER (Polish Optical Internet) NREN and Intranet tools for online collaboration and audiovisual communication with utilization of resources available at network and HPC centers across the country. It is assumed that the system as primarily being developed for the needs of local scale mapping thanks to the network approach will be adaptable also for larger (regional) scale enterprises. The paper discusses briefly the current state of research in the mentioned field in Poland. The second part of the paper presents the timetable of further activities with a specification of expected results. Apart from the 'technical' problems of acoustic mapping of urban areas, the paper also deals with some 'non-technical' aspects of this field of activity. The final part of the paper introduces some perspectives of dissemination of results of the reported research in the process of European enlargement.

Spatial audio in small display screen devices

Our work addresses the problem of (visual) clutter in mobile device interfaces. The solution we propose involves the translation of technique-from the graphical to the audio domain-for expliting space in information representation. This article presents an illustrative example in the form of a spatialisedaudio progress bar. In usability tests, participants performed background monitoring tasks significantly more accurately using this spatialised audio (a compared with a conventional visual) progress bar. Moreover, their performance in a simultaneously running, visually demanding foreground task was significantly improved in the eye-free monitoring condition. These results have important implications for the design of multi-tasking interfaces for mobile devices

Enhancing AIS to Improve Whale-Ship Collision Avoidance and Maritime Security

Whale-ship strikes are of growing worldwide concern due to the steady growth of commercial shipping. Improving the current situation involves the creation of a communication capability allowing whale position information to be estimated and exchanged among vessels and other observation assets. An early example of such a system has been implemented for the shipping lane approaches to the harbor of Boston, Massachusetts where ship traffic transits areas of the Stellwagen Bank National Marine Sanctuary frequently used by whales. It uses the Automated Identification Systems (AIS) technology, currently required for larger vessels but becoming more common in all classes of vessels. However, we believe the default mode of AIS operation will be inadequate to meet the long-term needs of whale-ship collision avoidance, and will likewise fall short of meeting other current and future marine safety and security communication needs. This paper explores the emerging safety and security needs for vessel communications, and considers the consequences of a communication framework supporting asynchronous messaging that can be used to enhance the basic AIS capability. The options we analyze can be pursued within the AIS standardization process, or independently developed with attention to compatibility with existing AIS systems. Examples are discussed for minimizing ship interactions with Humpback Whales and endangered North Atlantic Right Whales on the east coast, and North Pacific Right Whales, Bowhead Whales, Humpback Whales, Blue Whales and Beluga Whales in west coast, Alaskan and Hawaiian waters

Fiber-optic interferometric sensor for dynamic impact measurement of transport trucks

Ground vibrations are commonly observed by using a standard seismic station equipped with speed seismometers or acceleration seismometers. The seismometers include three mechanical vibrating systems (sensors) and the primary output is the wave pattern of recording velocity or acceleration of the material point oscillation. An alternative new method how it is possible to realize seismic measurements is using of the fiber-optic interferometric sensors. These interferometers are well-known for their ability to make high-precision measurements of optical path difference or changes that may be induced by a refractive index change in the interferometer or a physical displacement. The paper presents a comparison of the results of the standard seismic measurement by using seismic station and of the fiber-optic interferometric sensor. As a source of dynamic load, truck transport was chosen. When trucks passing through unevenness on the road (due to the road damage, the transition area of the bridge etc.), it generates vibrations that are transmitted to the subsoil and can adversely affect the surrounding building objects. Data comparison of the subsoil dynamic response obtained during both approaches of measurements is present in the amplitude and primary in the frequency domain.Web of Science42463

Social-ecological soundscapes: examining aircraft-harvester-caribou conflict in Arctic Alaska

Thesis (M.S.) University of Alaska Fairbanks, 2017As human development expands across the Arctic, it is crucial to carefully assess the impacts to remote natural ecosystems and to indigenous communities that rely on wild resources for nutritional and cultural wellbeing. Because indigenous communities and wildlife populations are interdependent, assessing how human activities impact traditional harvest practices can advance our understanding of the human dimensions of wildlife management. Indigenous communities across Arctic Alaska have expressed concern over the last four decades that low-flying aircraft interfere with their traditional harvest practices. For example, communities often have testified that aircraft disturb caribou (Rangifer tarandus) and thereby reduce harvest opportunities. Despite this longstanding concern, little research exists on the extent of aircraft activity in Arctic Alaska and on how aircraft affect the behavior and perceptions of harvesters. Therefore, the overarching goal of my research was to highlight the importance of aircraft-harvester conflict in Arctic Alaska and begin to address the issue using a scientific and community-driven approach. In Chapter 1, I demonstrated that conflict between aircraft and indigenous harvesters in Arctic Alaska is a widespread, understudied, and complex issue. By conducting a meta-analysis of the available literature, I quantified the deficiency of scientific knowledge about the impacts of aircraft on rural communities and traditional harvest practices in the Arctic. My results indicated that no peer-reviewed literature has addressed the conflict between low-flying aircraft and traditional harvesters in Arctic Alaska. I speculated that the scale over which aircraft, rural communities, and wildlife interact limits scientists' ability to determine causal relationships and therefore detracts from their interest in researching the human dimension of this social-ecological system. Innovative research approaches like soundscape ecology could begin to quantify interactions and provide baseline data that may foster mitigation discourses among stakeholders. In Chapter 2, I employed a soundscape-ecology approach to address concerns about aircraft activity expressed by the Alaska Native community of Nuiqsut. Nuiqsut faces the greatest volume of aircraft activity of any community in Arctic Alaska because of its proximity to intensive oil and gas activity. However, information on when and where these aircraft are flying is unavailable to residents, managers, and researchers. I worked closely with Nuiqsut residents to deploy acoustic monitoring systems along important caribou harvest corridors during the peak of caribou harvest, from early June through late August 2016. This method successfully captured aircraft sound and the community embraced my science for addressing local priorities. I found aircraft activity levels near Nuiqsut and surrounding oil developments (12 daily events) to be approximately six times greater than in areas over 30 km from the village (two daily events). Aircraft sound disturbance was 26 times lower in undeveloped areas (Noise Free Interval =13 hrs) than near human development (NFI = 0.5 hrs). My study provided baseline data on aircraft activity and noise levels. My research could be used by stakeholders and managers to develop conflict avoidance agreements and minimize interference with traditional harvest practices. Soundscape methods could be adapted to rural regions across Alaska that may be experiencing conflict with aircraft or other sources of noise that disrupt human-wildlife interactions. By quantifying aircraft activity using a soundscape approach, I demonstrated a novel application of an emerging field in ecology and provided the first scientific data on one dimension of a larger social-ecological system. Future soundscape studies should be integrated with research on both harvester and caribou behaviors to understand how the components within this system are interacting over space and time. Understanding the long-term impacts to traditional harvest practices will require integrated, cross-disciplinary efforts that collaborate with communities and other relevant stakeholders. Finally, my research will likely spark efforts to monitor and mitigate aircraft impacts to wildlife populations and traditional harvest practices across Alaska, helping to inform a decision-making process currently hindered by an absence of objective data