Cyber Security-Privacy: Are We All Living In Glass Houses? Can I Get Some Privacy, Please?
Levent Ertaul, California State University, East Bay
Cyber security, cyberwar, hacking, privacy, and governmental/personal data breaches… We keep hearing these with increasing frequency repeatedly. This creates a cyber
anxiety everywhere. On top of that we, as ordinary people started to learn that corporations and governments all around the world keep track of our personal data. For example, mobile phones constantly provide information about our location to service providers. Google knows what we are thinking about from our personal online searches. Facebook can see who our friends are. Yahoo knows the type of news we are interested in. Our online shopping patterns are recorded. Governments are launching surveillance programs to collect our personal data on the cyber space. AS the list goes on... It is as if we are all living in glass houses in which we do not have any privacy or cannot keep any secrets anymore. Cyber security issues affect everyone. Most of all they affect us individuals. That is why ignorance is not bliss in cyber security. Every day we face new questions, new challenges from our rights and responsibilities as citizens of the cyber world to how to protect ourselves, if we can, from new types of security threats. In this talk, I will try to explain vulnerabilities and security issues in the cyber space along with what we can and cannot do to protect ourselves.
Maya Ackerman, San Jose State University
Songwriting, the art of combining melodies and lyrics, poses new challenges to algorithmic composition. ALYSIA is a machine-learning system that learns the relationship between melodies and lyrics, and uses the resulting model to create new songs in the style of the corpus. While ALYSIA creates melodies for user-provided lyrics, another system, MABLE, creates computer-generated lyrics that convey a coherent story. Original works created with the systems will be shown.
Data Analytics: A Case Study In Healthcare
Mohammad Pourhomayoun, Cal State University, Los Angeles
The increasing cost of chronic disease management demands novel technological solutions that shift healthcare services from clinical and hospital settings to a remote and homebound scenario. Alternative and innovative technologies such as Remote Health Monitoring Systems, Big Data Analytics, and Wireless Health Technologies allow for collecting physiological and contextual data from patients, and providing unique opportunities for real-time data analytics to predict health conditions and prevent medically adverse events. The development of effective predictive models and big data analytics systems, however, faces several fundamental challenges regarding their robustness, scalability, and real-time processing of big heterogeneous data. These challenges necessitate the design and development of robust and scalable data processing techniques based on advanced machine learning algorithms that can efficiently extract the information from physiological data and allow for knowledge discovery and analysis. This talk presents a research methodology for data analytics in next-generation remote health management platforms.
Using Social Programming Environments To Improve Computing Education
Adam S. Carter, Humboldt State University
At only 46%, computing has one of the lowest baccalaureate retention rates. This statistic is especially distressing given the upward trend in demand for computing professionals. To address this problem, I employ social programming environments (SPEs) to explore the application and impact of social learning theory on students enrolled in computing courses. Unlike traditional integrated development environments, SPEs provide students with opportunities to form learning communities and to engage other classmates in both formal and informal discussions. Even though participation within a learning community is positively linked to retention, such communities are frequently absent in early computing courses.
Secure Computation And Its Applications
Mehrdad Aliasgari, California State University, Long Beach
Data is either stored, transmitted or used in computation. Information security aims to provide protection at all the stages of data. Traditional encryption algorithms help us achieve security for data at storage and transmition. However, in order to provide security while executing a function on private data, we need a completely new set of tools. In this talk, we look at secure computation, its applications and challenges that lie ahead.