Home > Research > Publications & Outputs > Transformers

Research

Associated organisational units

Electronic data

Keywords

View graph of relations

Transformers: Intrusion Detection Data In Disguise

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Published

Standard

Transformers: Intrusion Detection Data In Disguise. / Boorman, James; Prince, Daniel; Green, Benjamin.
2020. Paper presented at 3rd International Workshop on Attacks and Defences for Internet-of-Things, Surrey, United Kingdom.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Boorman, J, Prince, D & Green, B 2020, 'Transformers: Intrusion Detection Data In Disguise', Paper presented at 3rd International Workshop on Attacks and Defences for Internet-of-Things, Surrey, United Kingdom, 19/09/20 - 19/09/20.

APA

Boorman, J., Prince, D., & Green, B. (2020). Transformers: Intrusion Detection Data In Disguise. Paper presented at 3rd International Workshop on Attacks and Defences for Internet-of-Things, Surrey, United Kingdom.

Vancouver

Boorman J, Prince D, Green B. Transformers: Intrusion Detection Data In Disguise. 2020. Paper presented at 3rd International Workshop on Attacks and Defences for Internet-of-Things, Surrey, United Kingdom.

Author

Boorman, James ; Prince, Daniel ; Green, Benjamin. / Transformers : Intrusion Detection Data In Disguise. Paper presented at 3rd International Workshop on Attacks and Defences for Internet-of-Things, Surrey, United Kingdom.

Bibtex

@conference{de4a1eb91086491e9f9ca3e2b9e16b03,
title = "Transformers: Intrusion Detection Data In Disguise",
abstract = "IoT cyber security deficiencies are an increasing concern for users, operators, and developers. With no immediate and holistic devicelevel fixes in sight, alternative wraparound defensive measures are required. Intrusion Detection Systems (IDS) present one such option, and represent an active field of research within the IoT space. IoT environments offer rich contextual and situational information from their interaction with the physical processes they control, which may be of use to such IDS. This paper uses a comprehensive analysis of the current stateof-the-art in context and situationally aware IoT IDS to define the often misunderstood concepts of context and situational awareness in relation to their use within IoT IDS. Building on this, a unified approach to transforming and exploiting such a rich additional data set is proposed to enhance the efficacy of current IDS approaches.",
keywords = "Internet of Things (IoT), IoT, Intrusion detection, Context Awareness, Situational Awareness",
author = "James Boorman and Daniel Prince and Benjamin Green",
year = "2020",
month = sep,
day = "18",
language = "English",
note = "3rd International Workshop on Attacks and Defences for Internet-of-Things, ADIoT ; Conference date: 19-09-2020 Through 19-09-2020",
url = "http://adiot2020.compute.dtu.dk/",

}

RIS

TY - CONF

T1 - Transformers

T2 - 3rd International Workshop on Attacks and Defences for Internet-of-Things

AU - Boorman, James

AU - Prince, Daniel

AU - Green, Benjamin

PY - 2020/9/18

Y1 - 2020/9/18

N2 - IoT cyber security deficiencies are an increasing concern for users, operators, and developers. With no immediate and holistic devicelevel fixes in sight, alternative wraparound defensive measures are required. Intrusion Detection Systems (IDS) present one such option, and represent an active field of research within the IoT space. IoT environments offer rich contextual and situational information from their interaction with the physical processes they control, which may be of use to such IDS. This paper uses a comprehensive analysis of the current stateof-the-art in context and situationally aware IoT IDS to define the often misunderstood concepts of context and situational awareness in relation to their use within IoT IDS. Building on this, a unified approach to transforming and exploiting such a rich additional data set is proposed to enhance the efficacy of current IDS approaches.

AB - IoT cyber security deficiencies are an increasing concern for users, operators, and developers. With no immediate and holistic devicelevel fixes in sight, alternative wraparound defensive measures are required. Intrusion Detection Systems (IDS) present one such option, and represent an active field of research within the IoT space. IoT environments offer rich contextual and situational information from their interaction with the physical processes they control, which may be of use to such IDS. This paper uses a comprehensive analysis of the current stateof-the-art in context and situationally aware IoT IDS to define the often misunderstood concepts of context and situational awareness in relation to their use within IoT IDS. Building on this, a unified approach to transforming and exploiting such a rich additional data set is proposed to enhance the efficacy of current IDS approaches.

KW - Internet of Things (IoT)

KW - IoT

KW - Intrusion detection

KW - Context Awareness

KW - Situational Awareness

M3 - Conference paper

Y2 - 19 September 2020 through 19 September 2020

ER -