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When Good Machine Learning Leads to Bad Security: Big Data (Ubiquity symposium)
by Tegjyot Singh Sethi, Mehmed Kantardzic
While machine learning has proven to be promising in several application domains, our understanding of its behavior and limitations is still in its nascent stages. One such domain is that of cybersecurity, where machine learning models are replacing traditional rule based systems, owing to their ability to generalize and deal with large scale attacks which are not seen before. However, the naive transfer of machine learning principles to the domain of security needs to be taken with caution. Machine learning was not designed with security in mind and as such is prone to adversarial manipulation and reverse engineering. While most data based learning models rely on a static assumption of the world, the security landscape is one that is especially dynamic, with an ongoing never ending arms race between the system designer and the attackers. Any solution designed for such a domain needs to take into account an active adversary and needs to evolve over time, in the face of emerging threats. We term this as the "Dynamic Adversarial Mining" problem, and this paper provides motivation and foundation for this new interdisciplinary area of research, at the crossroads of machine learning, cybersecurity, and streaming data mining.
First write like you speak, then write like you write
by Philip Yaffe
April 2018Each "Communication Corner" essay is self-contained; however, they build on each other. For best results, before reading this essay and doing the exercise, go to the first essay "How an ...
Developing an Open Source 'Big Data' Cognitive Computing Platform: Big Data (Ubiquity symposium)
by Michael Kowolenko, Mladen A. Vouk
March 2018The ability to leverage diverse data types requires a robust and dynamic approach to systems design. The needs of a data scientist are as varied as the questions being explored. ...
High Performance Synthetic Information Environments
An integrating architecture in the age of pervasive data and computing: Big Data (Ubiquity symposium)
by Christopher L. Barrett, Jeffrey Johnson, Madhav Marathe
March 2018The complexities of social and technological policy domains, such as the economy, the environment, and public health, present challenges that require a new approach to modeling and decision-making. ...
Technology and Business Challenges of Big Data in the Digital Economy: Big Data (Ubiquity symposium)
by Dave Penkler
January 2018The early digital economy during the dot-com days of internet commerce successfully faced its first big data challenges of click-stream analysis with map-reduce technology. Since then the digital economy has ...
Why putting yourself in the mind of your reader is easier---and more challenging---than you might have imagined
by Philip Yaffe
January 2018Each "Communication Corner" essay is self-contained; however, they build on each other. ...
Big Data for Social Science Research: Big Data (Ubiquity symposium)
by Mark Birkin
January 2018Academic studies exploiting novel data sources are scarce. Typically, data is generated by commercial businesses or government organizations with no mandate and little motivation to share their assets with academic ...