Visible to the public An eye for deception: A case study in utilizing the human-as-a-security-sensor paradigm to detect zero-day semantic social engineering attacks

TitleAn eye for deception: A case study in utilizing the human-as-a-security-sensor paradigm to detect zero-day semantic social engineering attacks
Publication TypeConference Paper
Year of Publication2017
AuthorsHeartfield, R., Loukas, G., Gan, D.
Conference Name2017 IEEE 15th International Conference on Software Engineering Research, Management and Applications (SERA)
Date Publishedjun
PublisherIEEE
ISBN Number978-1-5090-5756-6
Keywordsapplication spoofing, Browsers, Computer crime, cyber security, defense, Electronic mail, feature extraction, Human Behavior, human factors, human-as-a-security-sensor paradigm, Human-as-a-Sensor, information security scenarios, learning (artificial intelligence), machine learning, multimedia masquerading, phishing, Predictive models, pubcrawl, reliability, security, security measures, semantic attacks, semantic social engineering attacks, Semantics, Social Engineering, Spear-phishing, technical security countermeasures, threat detection, user deception threat, Zero day attacks, zero-day semantic social engineering attack detection
Abstract

In a number of information security scenarios, human beings can be better than technical security measures at detecting threats. This is particularly the case when a threat is based on deception of the user rather than exploitation of a specific technical flaw, as is the case of spear-phishing, application spoofing, multimedia masquerading and other semantic social engineering attacks. Here, we put the concept of the human-as-a-security-sensor to the test with a first case study on a small number of participants subjected to different attacks in a controlled laboratory environment and provided with a mechanism to report these attacks if they spot them. A key challenge is to estimate the reliability of each report, which we address with a machine learning approach. For comparison, we evaluate the ability of known technical security countermeasures in detecting the same threats. This initial proof of concept study shows that the concept is viable.

URLhttp://ieeexplore.ieee.org/document/7965754/
DOI10.1109/SERA.2017.7965754
Citation Keyheartfield_eye_2017