Curriculum Vitae

Xin Meng

Contact

Address: A309, College Building, City University London EC1V 0HB

Email: Xin.Meng.1@city.ac.uk

Education

PhD researcher at City University, London

Sept 2012 - Current

Mobile Security Research

Research on the mobile Botnet detection on Android platform. Became familiar with JAVA and Android development technique. Provided analysis of the traffic network pass through the mobile device by using machine learning classification. A mobile Botnet detection framework (MBotCS) is developed on the Android platform.

Master of Science in Computer Application Technology

Sept 2010 - July 2012

Major: Cloud Computing, University of Aeronautics and Astronautics, Nanjing

Thesis: “Virtual Resource Management in Cloud” Advisor: Prof. Yi Zhuang

Mark: 87.98/100

Undergraduate Degree in Computer Science and Technology

Sept 2006 - July 2010

highest honor, University of Aeronautics and Astronautics, Nanjing

Thesis: “UCON Based FTP Access Monitoring System” Advisor: Yi Zhuang

Gpa: 4.0/5

Work Experience

Teaching Assistant at City University , London

May 2014 - Current, Education

Provided teaching assistant for the undergraduate course including Mathematics for Computing, Computation and Reasoning and Object-Oriented Analysis and Design. Meanwhile, I got involved in the Second Maker for Individual Project. Gained experience of communication and logical thinking.

Co-founder & Chief Technology Officer at IDAOYOO.COM , London

May 2013 - May 2015, Research & Development

Provided technical support, in particular the software development for the company including the website(www.idaoyoo.com) and the applications on iOS&Android platform. Became familiar with the web technology of PHP, HTML and CSS and mastered the mobile project design. Gained proficiency in the website hosed and maintenance technology.

QA Intern at Trend Micro Developing Centre, Nanjing

May 2009 - May 2010 Mobile Security Application Quality Assurance

Received offer from software development competition as a result of the very positive review. Rated “truly distinctive” for software testing skills and teamwork. Mastered the systematic software testing and the virtual machine technique for mobile application.

Key Transferable Skills

Problem Solving:

To achieve the target of my Ph.D. project, I had to solve a series of problems including how to distinct the malware and normal applications and which features could be used for detection. According to a lot of experiments, I found that it is feasible to detect the malware by analysing some specific features of traffic.

Learning Capability:

During the period of Ph.D., I learnt a lot of knowledge by myself for the research. Such as learning Linux shell script to monitor system calls on the Android platform and learning VBA script to analyse huge data automatically. I am good at studying and taking advantage of the new technology and existing toolkit. Such as to implement analysis of PCAP file, I made use of JNetPcap, which is a powerful open-source Java library for network analysis. I also learnt the L ATEX to write my publication and thesis.

Data Analysis:

Machine Learning and statistic analysis play an important role in my research. These techniques are essential for data analysis. Such as I used the machine learning classification to analyse the traffic data on the mobile device to find the distinction between normal and abnormal. I also performed T-Test and ANOVA to analyse the differences among different groups data.

Computer Skills

  1. Basic Knowledge: python, Matlab
  2. Intermediate Knowledge: Html, C, C++, CSS, Linux, MS Office, Adobe Photoshop, Git, L ATEX, mysql
  3. Advance Knowledge: JAVA, VBA, PHP, Machine Learning

Scholarships and Certificates

  1. Sep. 2012 Full Scholarship for PhD students from City University (£50,400 )
  2. Oct. 2011 Excellence awards in Google Android Competition in East China
  3. Jul. 2009 Awarded China National Motivational Scholarships(¥6,000 )
  4. Jul. 2008 Awarded China National Scholarship (¥8,000 )
  5. Nov. 2012 IELTS®: 6.5 (Listening:7.5;Reading:7.0;Writing:5.5;Speaking:6.0)

Publication

July 2015 MBotCS: A mobile Botnet detection system based on machine learning 10th International Conference on Risks and Security of Internet and Systems

Languages

  1. Chinese: Mothertongue
  2. English: Fluent
  3. French: Basic Knowledge

Interests and Activities

Novel Technology, Open-Source, Programming

Reading, Magic Cube

Cycling, Football, Travelling