Anonymity in Bitcoin and Bitmessage

This report describes two projects created by the author which are based on ideas which originate from the Bitcoin community. The first, bmd, is a re-implementation of the Bitmessage protocol in go. Bitmessage is an anonymous and secure messaging system invented by Jonathan Warren, who was inspired by the design of Bitcoin's p2p network. [WARR1] The second is Shufflepuff, an implementation of a protocol called CoinShuffle[RUFF1] which allows several people to construct a Bitcoin transaction with an input and an output for each participant without any participant knowing who owns which output. CoinShuffle was invented by Tim Ruffing et al, and it is an upgrade of a protocol called CoinJoin, invented by Gregory Maxwell. This paper discusses the background, properties, applications, and design of bmd and Shufflepuff. There is also a report of a performance analysis on bmd.Electrical and Computer Engineerin

Extending the Strand Space Method with Timestamps: Part I the Theor

In this paper, we present two extensions of the strand space method to model Kerberos V. First, we include time and timestamps to model security protocols with timestamps: we relate a key to a crack time and com-bine it with timestamps in order to define a notion of recency. Therefore, we can check replay attacks in this new framework. Second, we extend the classic strand space theory to model protocol mixture. The main idea is to introduce a new relation a to model the causal relation between one primary protocol session and one of its following secondary protocol session. Accordingly, we also extend the definition of unsolicited authen-tication test

Efficient Resource Management Mechanism for 802.16 Wireless Networks Based on Weighted Fair Queuing

Wireless Networking continues on its path of being one of the most commonly used means of communication. The evolution of this technology has taken place through the design of various protocols. Some common wireless protocols are the WLAN, 802.16 or WiMAX, and the emerging 802.20, which specializes in high speed vehicular networks, taking the concept from 802.16 to higher levels of performance. As with any large network, congestion becomes an important issue. Congestion gains importance as more hosts join a wireless network. In most cases, congestion is caused by the lack of an efficient mechanism to deal with exponential increases in host devices. This can effectively lead to very huge bottlenecks in the network causing slow sluggish performance, which may eventually reduce the speed of the network. With continuous advancement being the trend in this technology, the proposal of an efficient scheme for wireless resource allocation is an important solution to the problem of congestion. The primary area of focus will be the emerging standard for wireless networks, the 802.16 or “WiMAX”. This project, attempts to propose a mechanism for an effective resource management mechanism between subscriber stations and the corresponding base station

Mobile IP movement detection optimisations in 802.11 wireless LANs

The IEEE 802.11 standard was developed to support the establishment of highly flexible wireless local area networks (wireless LANs). However, when an 802.11 mobile node moves from a wireless LAN on one IP network to a wireless LAN on a different network, an IP layer handoff occurs. During the handoff, the mobile node's IP settings must be updated in order to re-establish its IP connectivity at the new point of attachment. The Mobile IP protocol allows a mobile node to perform an IP handoff without breaking its active upper-layer sessions. Unfortunately, these handoffs introduce large latencies into a mobile node's traffic, during which packets are lost. As a result, the mobile node's upper-layer sessions and applications suffer significant disruptions due to this handoff latency. One of the main components of a Mobile IP handoff is the movement detection process, whereby a mobile node senses that it is attached to a new IP network. This procedure contributes significantly to the total Mobile IP handover latency and resulting disruption. This study investigates different mechanisms that aim to lower movement detection delays and thereby improve Mobile IP performance. These mechanisms are considered specifically within the context of 802.11 wireless LANs. In general, a mobile node detects attachment to a new network when a periodic IP level broadcast (advertisement) is received from that network. It will be shown that the elimination of this dependence on periodic advertisements, and the reliance instead on external information from the 802.11 link layer, results in both faster and more efficient movement detection. Furthermore, a hybrid system is proposed that incorporates several techniques to ensure that movement detection performs reliably within a variety of different network configurations. An evaluation framework is designed and implemented that supports the assessment of a wide range of movement detection mechanisms. This test bed allows Mobile IP handoffs to be analysed in detail, with specific focus on the movement detection process. The performance of several movement detection optimisations is compared using handoff latency and packet loss as metrics. The evaluation framework also supports real-time Voice over IP (VoIP) traffic. This is used to ascertain the effects that different movement detection techniques have on the output voice quality. These evaluations not only provide a quantitative performance analysis of these movement detection mechanisms, but also a qualitative assessment based on a VoIP application

Implementation and Performance Evaluation of an NGN prototype using WiMax as an Access Technology

Telecommunications networks have evolved to IP-based networks, commonly known as Next Generation Networks (NGN). The biggest challenge in providing high quality realtime multimedia applications is achieving a Quality of Service (QoS) consistent with user expectations. One of the key additional factors affecting QoS is the existence of different QoS mechanisms on the heterogeneous technologies used on NGN platforms. This research investigates the techniques used to achieve consistent QoS on network technologies that use different QoS techniques. Numerous proposals for solving the end-to-end QoS problem in IP networks have adopted policy-based management, use of signalling protocols for communicating applications QoS requirements across different Network Elements and QoS provisioning in Network Elements. Such solutions are dependent on the use of traffic classification and knowledge of the QoS requirements of applications and services on the networks. This research identifies the practical difficulties involved in meeting the QoS requirements of network traffic between WiMax and an IP core network. In the work, a solution based on the concept of class-of-service mapping is proposed. In the proposed solution, QoS is implemented on the two networks and the concept of class-of-service mapping is used to integrate the two QoS systems. This essentially provides consistent QoS to applications as they traverse the two network domains and hence meet end-user QoS expectations. The work is evaluated through a NGN prototype to determine the capabilities of the networks to deliver real-time media that meets user expectations

A Look Back at "Security Problems in the TCP/IP Protocol Suite"

About fifteen years ago, I wrote a paper on security problems in the TCP/IP protocol suite. In particular, I focused on protocol-level issues, rather than implementation flaws. It is instructive to look back at that paper, to see where my focus and my predictions were accurate, where I was wrong, and where dangers have yet to happen. This is a reprint of the original paper, with added commentary

MapReduce based RDF assisted distributed SVM for high throughput spam filtering

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityElectronic mail has become cast and embedded in our everyday lives. Billions of legitimate emails are sent on a daily basis. The widely established underlying infrastructure, its widespread availability as well as its ease of use have all acted as catalysts to such pervasive proliferation. Unfortunately, the same can be alleged about unsolicited bulk email, or rather spam. Various methods, as well as enabling architectures are available to try to mitigate spam permeation. In this respect, this dissertation compliments existing survey work in this area by contributing an extensive literature review of traditional and emerging spam filtering approaches. Techniques, approaches and architectures employed for spam filtering are appraised, critically assessing respective strengths and weaknesses. Velocity, volume and variety are key characteristics of the spam challenge. MapReduce (M/R) has become increasingly popular as an Internet scale, data intensive processing platform. In the context of machine learning based spam filter training, support vector machine (SVM) based techniques have been proven effective. SVM training is however a computationally intensive process. In this dissertation, a M/R based distributed SVM algorithm for scalable spam filter training, designated MRSMO, is presented. By distributing and processing subsets of the training data across multiple participating computing nodes, the distributed SVM reduces spam filter training time significantly. To mitigate the accuracy degradation introduced by the adopted approach, a Resource Description Framework (RDF) based feedback loop is evaluated. Experimental results demonstrate that this improves the accuracy levels of the distributed SVM beyond the original sequential counterpart. Effectively exploiting large scale, ‘Cloud’ based, heterogeneous processing capabilities for M/R in what can be considered a non-deterministic environment requires the consideration of a number of perspectives. In this work, gSched, a Hadoop M/R based, heterogeneous aware task to node matching and allocation scheme is designed. Using MRSMO as a baseline, experimental evaluation indicates that gSched improves on the performance of the out-of-the box Hadoop counterpart in a typical Cloud based infrastructure. The focal contribution to knowledge is a scalable, heterogeneous infrastructure and machine learning based spam filtering scheme, able to capitalize on collaborative accuracy improvements through RDF based, end user feedback. MapReduce based RDF Assisted Distributed SVM for High Throughput Spam Filterin