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Victor Zhu

dblp:272/8311 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Web and mobile security · 44% Digital forensics and information hiding · 44% Network security · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Digital forensics and information hiding
digital forensics
0.412020
TARDIS: Rolling Back The Clock On CMS-Targeting Cyber Attacks · SP 2020
Web and mobile security
web security
0.412020
TARDIS: Rolling Back The Clock On CMS-Targeting Cyber Attacks · SP 2020
Network security › intrusion detection and prevention › intrusion detection › attack detection
multi-stage attack detection
0.112020
TARDIS: Rolling Back The Clock On CMS-Targeting Cyber Attacks · SP 2020

Methods — techniques the papers use, named apart from their topics

provenance inference · 0.4backup analysis · 0.4
YearPublicationVenuePosition
2020 TARDIS: Rolling Back The Clock On CMS-Targeting Cyber Attacks
abstract
Over 55% of the world's websites run on Content Management Systems (CMS). Unfortunately, this huge user population has made CMS-based websites a high-profile target for hackers. Worse still, the vast majority of the website hosting industry has shifted to a "backup and restore" model of security, which relies on error-prone AV scanners to prompt users to roll back to a pre-infection nightly snapshot. This research had the opportunity to study these nightly backups for over 300,000 unique production websites. In doing so, we measured the attack landscape of CMS-based websites and assessed the effectiveness of the backup and restore protection scheme. To our surprise, we found that the evolution of tens of thousands of attacks exhibited clear long-lived multi-stage attack patterns. We now propose TARDIS, an automated provenance inference technique, which enables the investigation and remediation of CMS-targeting attacks based on only the nightly backups already being collected by website hosting companies. With the help of our industry collaborator, we applied TARDIS to the nightly backups of those 300K websites and found 20,591 attacks which lasted from 6 to 1,694 days, some of which were still yet to be detected.
Ranjita Pai Kasturi, Yiting Sun, Ruian Duan, Omar Alrawi, Ehsan Asdar, Victor Zhu, Yonghwi Kwon 0001, Brendan Saltaformaggio
SP6