Nikolas Pilavakis, Adam Jenkins, Nadin Kokciyan, Kami Vaniea (University of Edinburgh)

When people identify potential malicious phishing emails one option they have is to contact a help desk to report it and receive guidance. While there is a great deal of effort put into helping people identify such emails and to encourage users to report them, there is relatively little understanding of what people say or ask when contacting a help desk about such emails. In this work, we qualitatively analyze a random sample of 270 help desk phishing tickets collected across nine months. We find that when reporting or asking about phishing emails, users often discuss evidence they have observed or gathered, potential impacts they have identified, actions they have or have not taken, and questions they have. Some users also provide clear arguments both about why the email really is phishing and why the organization needs to take action about it.

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WIP: Infrared Laser Reflection Attack Against Traffic Sign Recognition...

Takami Sato (University of California, Irvine), Sri Hrushikesh Varma Bhupathiraju (University of Florida), Michael Clifford (Toyota InfoTech Labs), Takeshi Sugawara (The University of Electro-Communications), Qi Alfred Chen (University of California, Irvine), Sara Rampazzi (University of Florida)

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LOKI: State-Aware Fuzzing Framework for the Implementation of Blockchain...

Fuchen Ma (Tsinghua University), Yuanliang Chen (Tsinghua University), Meng Ren (Tsinghua University), Yuanhang Zhou (Tsinghua University), Yu Jiang (Tsinghua University), Ting Chen (University of Electronic Science and Technology of China), Huizhong Li (WeBank), Jiaguang Sun (School of Software, Tsinghua University)

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Analysing Adversarial Threats to Rule-Based Local-Planning Algorithms for Autonomous...

Andrew Roberts (Tallinn University of Technology), Mohsen Malayjerdi (Tallinn University of Technology), Mauro Bellone (Tallinn University of Technology), Olaf Maennel (The University of Adelaide), Ehsan Malayjerdi (Tallinn University of Technology)

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FCGAT: Interpretable Malware Classification Method using Function Call Graph...

Minami Someya (Institute of Information Security), Yuhei Otsubo (National Police Academy), Akira Otsuka (Institute of Information Security)

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