HOR-INTERN-2020-02: ML-based IoT anomaly detection and notification on the home gateway.

HOR-INTERN-2020-02: ML-based IoT anomaly detection and notification on the home gateway

To apply, please complete the Internships Application Form.

Closing date

Applications must be made before 30th April 2020 and are assessed on an ongoing basis.

Location

Imperial College London reporting to Dr Hamed Haddadi; this programme is administered by Horizon at the University of Nottingham as part of the EPSRC DADA project (EP/R03351X/1) involving Cambridge, Edinburgh and Imperial as well as Nottingham.

Proposed dates

Internships run for up to 12 weeks and are available for successful candidates to start anytime. Please indicate your availability on the application form, where requested.

Overview

The internship will focus on ML-based methods for detecting undesired network activity or anomalous behaviours from IoT devices, using edge processing techniques (e.g., through the Databox https://www.databoxproject.uk/ . We wish to instrument and emulate a number of household devices and understand their “normal” behaviours through studying them and their companion apps, and enable edge-based notification systems through the Databox (and perhaps blocking the device or its unintended network connections). The candidate will use our 2 testbeds with over 100 IoT devices ( https://moniotrlab.ccis.neu.edu/imc19/ ) in addition to working alongside the postdoctoral researchers working in this project. A number of heuristic-based and ML-driven approaches could be evaluated in this project.

Who should apply?

Ideal applicants should be studying for an undergraduate or a postgraduate degree in networking, ML, HCI, computer science or related discipline and have experience with networked systems and user interactions.

Applicants must outline their area of interest, experience and skills. Information regarding Horizon, DADA and Databox may be found at http://www.horizon.ac.uk/, https://www.horizon.ac.uk/project/defence-against-dark-artefacts/ and https://www.databoxproject.uk/.

Required skills

  • Knowledge of networked systems

  • Knowledge on Machine Learning applications

  • Programming (Python or Go preferably)

  • Ability to work independently as well as part of a team.

 Desirable skills

  • Experience with IoT systems

  • Experience with anomaly detection and intrusion detection

  • Experience with networked systems

  • Experience with academic writing.

Eligibility and Financial Aspects

These are full-time internships for up to 12 weeks, for postgraduate and undergraduate students, a casual wage of £425 per week will be available, and this may be subject to tax deductions depending on the successful candidate’s circumstances and stipend stipulations.

In general, PhD students from The University of Nottingham are able to apply on the understanding they suspend their stipend, this is due to the nature of the funding source. For International students a Visa must be in place, covering the duration of the internship.

Informal enquiries

Informal enquiries may be made to Dr Hamed Haddadi h.haddadi@imperial.ac.uk at Imperial College London, however applications should be made using the following web link. Applications to this email address will not be accepted.

To apply, please complete the Internships Application Form.