PhD student SpySpot: Visualization of Advanced Persistent Threats
Specifications - (explanation)
| Function types | PhD positions |
|---|---|
| Scientific fields | Engineering |
| Hours | 36.0 - 40.0 hours per week |
| Education | University Graduate |
| Job number | V32.1786 |
| Translations | nl en |
| About employer | Eindhoven University of Technology (TU/e) |
| Short link | www.academictransfer.com/19124 |
Job description
Project Description: Cyber-attacks
have grown in number and sophistication, achieving unprecedented
success in reaching their targets. Advanced Persistent Threats (APTs)
such as data exfiltration attacks are both dangerous and difficult to
detect. These targeted and stealthy attacks using specifically developed
malware circumvent classical detection systems based on signatures or
statistical anomalies in network traffic. Only by looking in detail at
the actual content of communication would it be possible to detect APTs.
A method is thus needed to analyse the huge amount of data involved in
an effective way.
SpySpot proposes a solution which combines deep packet analysis with visualization of the analysis results enabling an end user to easily spot anomalies created by APTS like digital espionage. In the deep packet analysis the meaning of communication is recovered using protocol syntax and semantics, abstraction brings additional structure to this meaning and anomaly detection finds patterns deviating from the norm. While automated analysis is needed to manage the huge amount of data, no automatic method can match the ability of the human mind in recognizing deviations and evaluating these. The analysis will thus support visualization of results for human-based evaluation and be able to take into account feedback on the discovered anomalies, such as discarding harmless ones in future traffic.
As a PhD student your tasks concern the following activities:
SpySpot proposes a solution which combines deep packet analysis with visualization of the analysis results enabling an end user to easily spot anomalies created by APTS like digital espionage. In the deep packet analysis the meaning of communication is recovered using protocol syntax and semantics, abstraction brings additional structure to this meaning and anomaly detection finds patterns deviating from the norm. While automated analysis is needed to manage the huge amount of data, no automatic method can match the ability of the human mind in recognizing deviations and evaluating these. The analysis will thus support visualization of results for human-based evaluation and be able to take into account feedback on the discovered anomalies, such as discarding harmless ones in future traffic.
As a PhD student your tasks concern the following activities:
- carry out research within the project, in cooperation with the other parties involved;
- report on the results in papers and conference contributions;
- finishing a PhD thesis in four years;
- a small contribution to the teaching activities of the Visualization group may be asked.
Requirements
Requirements:We are looking for a candidate who meets the following requirements:
- a Master degree in Computer Science, Mathematics, or closely related discipline;
- a strong interest in information visualization, human computer interaction, and security;
- excellent analytic, creative, and implementation skills;
- ability to work in a team, cooperate both with academic and industrial partners;
- fluent in spoken and written English.
Conditions of employment
Appointment and salary:We offer:
- a full-time temporary appointment for a period of 4 years, with an intermediate evaluation after 9 months;
- a gross salary of € 2,062 per month in the first year increasing up to € 2,638 per month in the fourth year;
- a broad package of fringe benefits (e.g. excellent technical infrastructure, the possibility of child daycare and excellent sport facilities).
Additional information
Information:
!!Submit your application using the “APPLY NOW” button!! ---> GO to this website: https://www.academictransfer.com/employer/TUE/vacancy/19124/lang/en/
- For more information about the project, please contact prof.dr.ir. J.J. van Wijk, e-mail: J.J.v.Wijk@tue.nl .
- For information about employment conditions, please contact mr. C. Kuiters HR-advisor TU/e, e-mail: pzwin@tue.nl.
Application:The application should consist of the following parts:
- a cover letter explaining your motivation and qualifications for the position;
- a detailed Curriculum Vitae (and if applicable a list of publications);
- contact information of two references;
- copies of diplomas (including list of courses and grades);
- proof of English language skills (if applicable).
!!Submit your application using the “APPLY NOW” button!! ---> GO to this website: https://www.academictransfer.com/employer/TUE/vacancy/19124/lang/en/
