2,094 research outputs found

    Entropy/IP: Uncovering Structure in IPv6 Addresses

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    In this paper, we introduce Entropy/IP: a system that discovers Internet address structure based on analyses of a subset of IPv6 addresses known to be active, i.e., training data, gleaned by readily available passive and active means. The system is completely automated and employs a combination of information-theoretic and machine learning techniques to probabilistically model IPv6 addresses. We present results showing that our system is effective in exposing structural characteristics of portions of the IPv6 Internet address space populated by active client, service, and router addresses. In addition to visualizing the address structure for exploration, the system uses its models to generate candidate target addresses for scanning. For each of 15 evaluated datasets, we train on 1K addresses and generate 1M candidates for scanning. We achieve some success in 14 datasets, finding up to 40% of the generated addresses to be active. In 11 of these datasets, we find active network identifiers (e.g., /64 prefixes or `subnets') not seen in training. Thus, we provide the first evidence that it is practical to discover subnets and hosts by scanning probabilistically selected areas of the IPv6 address space not known to contain active hosts a priori.Comment: Paper presented at the ACM IMC 2016 in Santa Monica, USA (https://dl.acm.org/citation.cfm?id=2987445). Live Demo site available at http://www.entropy-ip.com

    Temporal and Spatial Classification of Active IPv6 Addresses

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    There is striking volume of World-Wide Web activity on IPv6 today. In early 2015, one large Content Distribution Network handles 50 billion IPv6 requests per day from hundreds of millions of IPv6 client addresses; billions of unique client addresses are observed per month. Address counts, however, obscure the number of hosts with IPv6 connectivity to the global Internet. There are numerous address assignment and subnetting options in use; privacy addresses and dynamic subnet pools significantly inflate the number of active IPv6 addresses. As the IPv6 address space is vast, it is infeasible to comprehensively probe every possible unicast IPv6 address. Thus, to survey the characteristics of IPv6 addressing, we perform a year-long passive measurement study, analyzing the IPv6 addresses gleaned from activity logs for all clients accessing a global CDN. The goal of our work is to develop flexible classification and measurement methods for IPv6, motivated by the fact that its addresses are not merely more numerous; they are different in kind. We introduce the notion of classifying addresses and prefixes in two ways: (1) temporally, according to their instances of activity to discern which addresses can be considered stable; (2) spatially, according to the density or sparsity of aggregates in which active addresses reside. We present measurement and classification results numerically and visually that: provide details on IPv6 address use and structure in global operation across the past year; establish the efficacy of our classification methods; and demonstrate that such classification can clarify dimensions of the Internet that otherwise appear quite blurred by current IPv6 addressing practices

    Evaluating the Impacts of Detecting X.509 Covert Channels

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    This quasi-experimental before-and-after study examined the performance impacts of detecting X.509 covert channels in the Suricata intrusion detection system. Relevant literature and previous studies surrounding covert channels and covert channel detection, X.509 certificates, and intrusion detection system performance were evaluated. This study used Jason Reaves’ X.509 covert channel proof of concept code to generate malicious network traffic for detection (2018). Various detection rules for intrusion detection systems were created to aid in the detection of the X.509 covert channel. The central processing unit (CPU) and memory utilization impacts that each rule had on the intrusion detection system was studied and analyzed. Statistically significant figures found that the rules do have an impact on the performance of the system, some more than others. Finally, pathways towards future related research in creating efficient covert channel detection mechanisms were identified

    Data Minimisation in Communication Protocols: A Formal Analysis Framework and Application to Identity Management

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    With the growing amount of personal information exchanged over the Internet, privacy is becoming more and more a concern for users. One of the key principles in protecting privacy is data minimisation. This principle requires that only the minimum amount of information necessary to accomplish a certain goal is collected and processed. "Privacy-enhancing" communication protocols have been proposed to guarantee data minimisation in a wide range of applications. However, currently there is no satisfactory way to assess and compare the privacy they offer in a precise way: existing analyses are either too informal and high-level, or specific for one particular system. In this work, we propose a general formal framework to analyse and compare communication protocols with respect to privacy by data minimisation. Privacy requirements are formalised independent of a particular protocol in terms of the knowledge of (coalitions of) actors in a three-layer model of personal information. These requirements are then verified automatically for particular protocols by computing this knowledge from a description of their communication. We validate our framework in an identity management (IdM) case study. As IdM systems are used more and more to satisfy the increasing need for reliable on-line identification and authentication, privacy is becoming an increasingly critical issue. We use our framework to analyse and compare four identity management systems. Finally, we discuss the completeness and (re)usability of the proposed framework

    Library and Tools for Server-Side DNSSEC Implementation

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    Tato práce se zabývá analýzou současných open source řešení pro zabezpečení DNS zón pomocí technologie DNSSEC. Na základě provedené rešerše je navržena a implementována nová knihovna pro použití na autoritativních DNS serverech. Cílem knihovny je zachovat výhody stávajících řešení a vyřešit jejich nedostatky. Součástí návrhu je i sada nástrojů pro správu politiky a klíčů. Funkčnost vytvořené knihovny je ukázána na jejím použití v serveru Knot DNS.This thesis deals with currently available open-source solutions for securing DNS zones using the DNSSEC mechanism. Based on the findings, a new DNSSEC library for an authoritative name server is designed and implemented. The aim of the library is to keep the benefits of existing solutions and to eliminate their drawbacks. Also a set of utilities to manage keys and signing policy is proposed. The functionality of the library is demonstrated by it's use in the Knot DNS server.

    Multicast Mobility in Mobile IP Version 6 (MIPv6) : Problem Statement and Brief Survey

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    Basic Properties of the Persona Model

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    This document proposes a terminology and a model for representation of user data in information systems in the form of "persona'' objects. It provides the mechanisms for evaluation how the personae relate to real-world subjects or to each other. A mechanism how to evaluate some anonymity and identity properties is proposed. This paper also describes the linking of personae by the use of shared identifiers. The local, global, persistent and transient personal linking types are considered. The model is used to describe persona linking in the different practical technologies as the example of model applicability
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