Ziqiang Wang (Southeast University), Xuewei Feng (Tsinghua University), Qi Li (Tsinghua University), Kun Sun (George Mason University), Yuxiang Yang (Tsinghua University), Mengyuan Li (University of Toronto), Ganqiu Du (China Software Testing Center), Ke Xu (Tsinghua University), Jianping Wu (Tsinghua University)

In this paper, we unveil a fundamental side channel in Wi-Fi networks, specifically the observable frame size, which can be exploited by attackers to conduct TCP hijacking attacks.

Despite the various security mechanisms (e.g., WEP and WPA2/WPA3) implemented to safeguard Wi-Fi networks, our study reveals that an off-path attacker can still extract sufficient information from the frame size side channel to hijack the victim's TCP connection.

Our side channel attack is based on two significant findings: (i) response packets (e.g., ACK and RST) generated by TCP receivers vary in size, and (ii) the encrypted frames containing these response packets have consistent and distinguishable sizes.

By observing the size of the victim's encrypted frames, the attacker can detect and hijack the victim's TCP connections.

We validate the effectiveness of this side channel attack through two case studies, i.e., SSH DoS and web traffic manipulation.

Precisely, our attack can terminate the victim's SSH session in 19 seconds and inject malicious data into the victim's web traffic within 28 seconds.

Furthermore, we conduct extensive measurements to evaluate the impact of our attack on real-world Wi-Fi networks. We test 30 popular wireless routers from 9 well-known vendors, and none of these routers can protect victims from our attack. Besides, we implement our attack in 80 real-world Wi-Fi networks and successfully hijack the victim's TCP connections in 75 (93.75%) evaluated Wi-Fi networks.

We have responsibly disclosed the vulnerability to the Wi-Fi Alliance and proposed several mitigation strategies to address this issue.

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A Comprehensive Memory Safety Analysis of Bootloaders

Jianqiang Wang (CISPA Helmholtz Center for Information Security), Meng Wang (CISPA Helmholtz Center for Information Security), Qinying Wang (Zhejiang University), Nils Langius (Leibniz Universität Hannover), Li Shi (ETH Zurich), Ali Abbasi (CISPA Helmholtz Center for Information Security), Thorsten Holz (CISPA Helmholtz Center for Information Security)

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Panel on “Security and Privacy Issues in New 5G...

Moderator: Arupjyoti (Arup) Bhuyan, Ph.D. Director, Wireless Security Institute, Idaho National Laboratory Panelists: Ted K. Woodward, Ph.D. Technical Director for FutureG, OUSD (R&E) Phillip Porras, Program Director, Internet Security Research, SRI Donald McBride, Senior Security Researcher, Bell Laboratories, Nokia

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UI-CTX: Understanding UI Behaviors with Code Contexts for Mobile...

Jiawei Li (Beihang University & National University of Singapore), Jiahao Liu (National University of Singapore), Jian Mao (Beihang University), Jun Zeng (National University of Singapore), Zhenkai Liang (National University of Singapore)

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The (Un)usual Suspects – Studying Reasons for Lacking Updates...

Maria Hellenthal (CISPA Helmholtz Center for Information Security), Lena Gotsche (CISPA Helmholtz Center for Information Security), Rafael Mrowczynski (CISPA Helmholtz Center for Information Security), Sarah Kugel (Saarland University), Michael Schilling (CISPA Helmholtz Center for Information Security), Ben Stock (CISPA Helmholtz Center for Information Security)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)