Connectionists: Post-Doctoral Position in Malware Detection at Royal Holloway, University of London: Deadline Nov 30 @ 11:59pm (GMT)

[ilia]

-----Original Message-----
 From: Lorenzo Cavallaro [mailto:lorenzo.cavallaro at rhul.ac.uk]
Sent: 02 November 2015 22:29
To: staff at cs.rhul.ac.uk
Subject: Post-Doctoral Position in Malware Detection at Royal Holloway, 
University of London: Deadline Nov 30 @ 11:59pm (GMT)

Dear CS Staff,

(apologies for multiple copies, please forward to whomever you believe
could be interested)

The recently-established Systems Security Research Lab (S2Lab,
http://s2lab.isg.rhul.ac.uk), led by Dr Lorenzo Cavallaro within the
Information Security Group (ISG) at Royal Holloway, University of
London, is seeking to appoint 1 Post-Doctoral Research Assistant
(PDRA) to work on the EPSRC-funded project “Mining the Network
Behaviour of Bots”, part of the CEReS call
(http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/K033344/1).

The project aims at building on machine learning techniques to
characterize the core network behaviors of malware, with a particular
emphasis on bot-like threats. Most of the machine learning-based
approaches applied to this context so far report high performance
metrics although marginal, if any, effort has been put on providing
quality metrics to assess the actual machine learning tasks and
provide supporting evidence on its actual strengths (or weaknesses)
once deployed in the wild. Within the project, we have been working
towards addressing such shortcomings and are building detection models
to classify and detect bot-like behaviors with (statistical)
confidence, by analysing different network data sources, such as
passive DNS traffic (to characterize DGA-based botnets), and
malicious/benign network traces.

The PI research expertise is in systems security and malware analysis
and detection; in addition, 4 co-investigators and 1 PDRA with
expertise in machine learning, bioinformatics, and network analysis,
make up the whole team.

The ideal candidate must have earned (or close to defend) a PhD in
Computer Science or related discipline, with a particular emphasis on
Computer Security. In addition, the candidate must have a strong
research track record and a proven ability to find innovative
solutions. The co-investigators and the machine learning PDRA are
focused on devising novel machine learning technique, while the ideal
candidate for this post must further be self-motivated, possess
development skills, and be experienced in systems security and malware
analysis / detection. Having explored machine learning in particular
to tackle security aspects is highly desirable.

The main responsibilities of the post are:

    - Developing novel analysis to mine and model network and host 
behaviors
    - Developing novel techniques to detect malicious network behavior
    - Developing research objectives and publishing research
    - Planning own day to day research activity
    - Attending project meetings, discussing research with
      collaborative partners, especially within the Systems Security 
Research Lab
    - Limited supervision by the PI
    - Attending conferences and presenting reearch papers
    - Providing input to project web sites and other dissemination and 
engagement forums;

The Systems Security Research Lab is currently exploring a number of
research projects, including Android security and techniques to
automatically generate exploit for memory corruption vulnerabilities.
Such projects inherently build on machine learning (and program
analysis) and further collaboration between this project and S2Lab
research activities at large is, of course, encouraged.

This is a full time post, available from Dec 14, 2015 or shortly
thereafter, for a fixed term period of 12 months. This post is based
in Egham, Surrey, where Royal Holloway, University of London is
situated in a beautiful, leafy campus near to Windsor Great Park and
within commuting distance from central London.

Royal Holloway University of London is an Academic Centre of
Excellence in Cyber Security Research and Education only one of the
two Higher Education institutions awarded with a Centre for Doctoral
Training in Cyber Security.

For an informal discussion about the post, please contact the PI, Dr
Lorenzo Cavallaro, at lorenzo.cavallaro at rhul.ac.uk or +44 (0)1784
414381.

Please apply online at https://goo.gl/RjYcZ2 --- applications must
inlcude (i) a CV, (ii) a cover letter outlining how you fit into the
project, and (iii) a personal research statement. Applications with
missing documentation may not be fully considered.

To view further details of this post and to apply please visit
https://jobs.royalholloway.ac.uk. The RHUL Recruitment Team can be
contacted with queries by email at: recruitment at rhul.ac.uk or via
telephone on: +44 (0)1784 41 4241.

Please quote the reference: 1115-336

Closing Date: Midnight (GMT), 30 November 2015

Interview Date: 7 December 2015

Cheers,
Lorenzo