April 5, 2024, 4:10 a.m. | Xiaoxiao Liu, Fan Xu, Nan Wang, Qinxin Zhao, Dalin Zhang, Xibin Zhao, Jiqiang Liu

cs.CR updates on arXiv.org arxiv.org

arXiv:2404.03162v1 Announce Type: new
Abstract: Advanced Persistent Threat (APT) is challenging to detect due to prolonged duration, infrequent occurrence, and adept concealment techniques. Existing approaches primarily concentrate on the observable traits of attack behaviors, neglecting the intricate relationships formed throughout the persistent attack lifecycle. Thus, we present an innovative APT detection framework named LTRDetector, implementing an end-to-end holistic operation. LTRDetector employs an innovative graph embedding technique to retain comprehensive contextual information, then derives long-term features from these embedded provenance graphs. …

advanced advanced persistent threat advanced persistent threats apt arxiv attack concealment cs.cr detect detection lifecycle observable persistent persistent threat persistent threats relationship relationships techniques threat threats

Information Security Engineers

@ D. E. Shaw Research | New York City

Technology Security Analyst

@ Halton Region | Oakville, Ontario, Canada

Senior Cyber Security Analyst

@ Valley Water | San Jose, CA

Sr. Staff Firmware Engineer – Networking & Firewall

@ Axiado | Bengaluru, India

Compliance Architect / Product Security Sr. Engineer/Expert (f/m/d)

@ SAP | Walldorf, DE, 69190

SAP Security Administrator

@ FARO Technologies | EMEA-Portugal