Prefix-preserving IP address anonymization: measurement-based security evaluation and a new cryptography-based scheme

Xu, Jun; Fan, Jinliang; Ammar, Mostafa; Moon, Sue

doi:10.1016/j.comnet.2004.03.033

Cited by 156 publications

(88 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These can, of course, be replaced by arbitrary numbers, but such a practice results in the loss of all the topological information embedded in the original addresses (e.g., different addresses that belong to the same subnet). The alternative is to use a prefix-preserving mapping that preserves the topological information [227,559]. However, exposing the topological data may in some cases compromise anonymity.…”

Section: Privacymentioning

confidence: 99%

Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

196

131

View full text Add to dashboard Cite

Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains.

show abstract

Section: Privacymentioning

confidence: 99%

Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

196

131

View full text Add to dashboard Cite

show abstract

“…we use a prefix-preserving anonymization as proposed in [9]. We also note that there is no impact of NAT on our study since we can uniquely identify each device connecting to the network with the anonymized session log.…”

Section: Av-1mentioning

confidence: 99%

Uncovering the footprints of malicious traffic in wireless/mobile networks

Raghuramu

Pathak

Zang

et al. 2016

Computer Communications

View full text Add to dashboard Cite

This paper presents a measurement study that analyzes large-scale traffic data gathered from two different wireless scenarios: cellular and WiFi networks.We first analyze packet traces and security event logs generated by over 2 million devices in a major US-based cellular network, and show that 0.17% of mobile devices are affected by security threats. We then analyze the aggregate network footprint of malicious and benign traffic in the cellular network, and demonstrate that statistical network features (e.g., uplink data transfer volume, IP entropy) can be effectively used to distinguish such malicious and benign traffic. We next investigate over 2.4 TB of WiFi traffic data, which are generated by 27 K distinct users, in a university campus network. Based on the lessons learned from a comprehensive exploration of a large feature space consisting of over 500 statistical attributes derived from network traffic to/from malicious and benign domains, we propose a novel, in-house traffic screening method, which has the capability of effectively identifying potential malicious domains. Our method achieves over 90% accuracy with only using a small set of simple statistical network features, without using any additional specialized datasets (e.g., geolocation database) or resource-intensive solutions (e.g., DPI boxes to collect HTTP traffic.).

show abstract

“…CryptoPAN is an approach developed by Fan et al for creating prefix preserving anonymized addresses without using prefix table [15].…”

Section: Ip Prefix-preservingmentioning

confidence: 99%