publication . Article . 2020

The Named Data Networking Flow Filter: Towards Improved Security over Information Leakage Attacks

Daishi Kondo; Vassilis Vassiliades; Thomas Silverston; Hideki Tode; Tohru Asami;
English
  • Published: 22 May 2020 Journal: Computer Networks, volume 173, page 107,187 (issn: 13891286, Copyright policy)
Abstract
Named Data Networking (NDN) has the potential to create a more secure future Internet. It is therefore crucial to investigate its vulnerabilities in order to make it safer against information leakage attacks. In NDN, malware inside an enterprise can encode condential information into Interest names and send it to the attacker. One of the countermeasures is to inspect a name in the Interest using a name lter and identify it as legitimate or anomalous. Although the name lter can dramatically decrease the information leakage throughput per Interest, it has a serious disadvantage: it does not consider a ow of Interests. This means that the malware can not only cause...
Subjects
free text keywords: Computer Networks and Communications, Computer science, SAFER, Malware, computer.software_genre, computer, ENCODE, Information leakage, The Internet, business.industry, business, Throughput, Computer network, Support vector machine, Anomaly detection
Related Organizations
Funded by
EC| RISE
Project
RISE
Research Center on Interactive Media, Smart System and Emerging Technologies
  • Funder: European Commission (EC)
  • Project Code: 739578
  • Funding stream: H2020 | SGA-CSA
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