Advising

In the last years, context-awareness and mobile computing has seen popular adoption connecting also with Service Oriented Computing (SOC) and the Internet of Things (IoT). Relevant hardware equipment can be found in smartphones, smartwatches, sensors and microcontroller boards, such as Arduino, Raspberry pi and the recent CHIP. Context-aware mobile computing in this framework with IoT and smart Cyber Systems will change the way we interact with objects and services, but includes many challenges. For instance, access to context requires access to sensitive information concerning users and their surroundings. Deep understanding of data sharing consequences by mobile platform users is limited (e.g. Android OS, iOS); users usually accept all requirements (e.g., when installing an application) without understanding well if there are potential violations on the privacy sphere related to the application use.

To address the above there are postdoc (and PhD) opportunities at the Software and Internet Technologies (SEIT) laboratory of the Department of Computer Science.If this is of interest to you, you can consider more working on topic like the following:

  • Extraction of context profiles from different sources: This topic involves the investigation of techniques and methods that can lead to the extraction of context-relevant data from user models/profiles in social media and other sources.
  • Privacy by Design methods in application development for mobile platforms: This topic involves the design a specification model to capture privacy requirements for privacy-aware native mobile platform application development with a focus on Android and the enrichment of current solutions that respect privacy options in native mobile platform environments through IDE-based plugins (e.g., Eclipse).
  • Privacy design patterns recommendations: This topic involves building privacy design patterns at platform independent level, tailor them to mobile platforms, linking them with corresponding code excerpts and refining them using contextual information, and building and recommending privacy protecting coding best practices.

There are also topics available on Software reuse in Software Engineering:

  • Mining software repositories and developer expertise: The developer social coding and Q&A websites are sources of valuable information that can be combined to draw different conclusions on users' activity and expertise. This topic involves the intelligent combination of information from various sources in order to draw meaningful conclusions on developers' knowledge.

For any further information, please contact me in the email address found here or visit me!

If you are interested in spending 1-3 months working on a research activity in an internship in the SEIT lab of UCY, please contact me in the email address found here or visit me!

Some of the available topics:

  • Privacy mechanisms for web applications:Privacy protection is an important aspect for sensitive information required by many web and mobile applications. In this project, you will study the mechanisms used for access to sentitive data in web browsers with HTML5.
  • Collecting data from activity trackers: There are many mobile applications that perform user activity tracking collecting various information (e.g., RunKeeper, DailyMile, EndoMondo. In this project you will study this format of activity data.
  • Microcontroller models: Boards with microcontrollers can be used for different purposes (e.g., Arduino, Raspberry pi, CHIP). In this project you will study the diferences among them and build a sample application for this.
  • Context dataset analysis: Datasets are sources of information that can be used to manipulate data and draw usefull conclusions (e.g., Twitter, flickr datasets). In this project you will perform experiments on a specific dataset that contains context information (e.g., timestamp, location).
  • Andreas Dimitriou, MSc student, Privacy protection in Android devices, expected completion: Dec. 2017.
  • Iosif Ioannou MSc student, LinkedUSDL Privacy for universal description of privacy properties in services, completed: May 2017.