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Authors: Chih-Chun Liu 1 ; Hsu-Chun Hsiao 1 and Tiffany Hyun-Jin Kim 2

Affiliations: 1 National Taiwan University, Taiwan ; 2 HRL Laboratories, LLC, U.S.A.

Keyword(s): JavaScript Injection Detection, Website Behavior Fingerprint, Browser-based DDoS.

Abstract: JavaScript injection attacks enable man-in-the-middle adversaries to not only exploit innocent users to launch browser-based DDoS but also expose them to unwanted advertisements. Despite ongoing efforts to address the critical JavaScript injection attacks, prior solutions have several practical limitations, including the lack of deployment incentives and the difficulty to configure security policies. An interesting observation is that the injected JavaScript oftentimes changes the website’s behavior, significantly increasing the additional requests to previously unseen domains. Hence, this paper presents the design and implementation of a lightweight system called FALCO to detect JavaScript injection with mismatched website behavior fingerprints. We extract a website’s behavior fingerprint from its dependency on external domains, which yields compact fingerprint representations with reasonable detection accuracy. Our experiments show that FALCO can detect 96.98% of JavaScript-based a ttacks in simulation environments. FALCO requires no cooperation with servers and users can easily add an extension on their browsers to use our service without privacy concerns. (More)

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Paper citation in several formats:
Liu, C.; Hsiao, H. and Kim, T. (2020). FALCO: Detecting Superfluous JavaScript Injection Attacks using Website Fingerprints. In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - SECRYPT; ISBN 978-989-758-446-6; ISSN 2184-7711, SciTePress, pages 180-191. DOI: 10.5220/0009835101800191

@conference{secrypt20,
author={Chih{-}Chun Liu. and Hsu{-}Chun Hsiao. and Tiffany Hyun{-}Jin Kim.},
title={FALCO: Detecting Superfluous JavaScript Injection Attacks using Website Fingerprints},
booktitle={Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - SECRYPT},
year={2020},
pages={180-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009835101800191},
isbn={978-989-758-446-6},
issn={2184-7711},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - SECRYPT
TI - FALCO: Detecting Superfluous JavaScript Injection Attacks using Website Fingerprints
SN - 978-989-758-446-6
IS - 2184-7711
AU - Liu, C.
AU - Hsiao, H.
AU - Kim, T.
PY - 2020
SP - 180
EP - 191
DO - 10.5220/0009835101800191
PB - SciTePress

- Science and Technology Publications, Lda.
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