263 research outputs found

    A P2P based usage control enforcement scheme resilient to re-injection attacks

    Full text link

    Study of Peer-to-Peer Network Based Cybercrime Investigation: Application on Botnet Technologies

    Full text link
    The scalable, low overhead attributes of Peer-to-Peer (P2P) Internet protocols and networks lend themselves well to being exploited by criminals to execute a large range of cybercrimes. The types of crimes aided by P2P technology include copyright infringement, sharing of illicit images of children, fraud, hacking/cracking, denial of service attacks and virus/malware propagation through the use of a variety of worms, botnets, malware, viruses and P2P file sharing. This project is focused on study of active P2P nodes along with the analysis of the undocumented communication methods employed in many of these large unstructured networks. This is achieved through the design and implementation of an efficient P2P monitoring and crawling toolset. The requirement for investigating P2P based systems is not limited to the more obvious cybercrimes listed above, as many legitimate P2P based applications may also be pertinent to a digital forensic investigation, e.g, voice over IP, instant messaging, etc. Investigating these networks has become increasingly difficult due to the broad range of network topologies and the ever increasing and evolving range of P2P based applications. In this work we introduce the Universal P2P Network Investigation Framework (UP2PNIF), a framework which enables significantly faster and less labour intensive investigation of newly discovered P2P networks through the exploitation of the commonalities in P2P network functionality. In combination with a reference database of known network characteristics, it is envisioned that any known P2P network can be instantly investigated using the framework, which can intelligently determine the best investigation methodology and greatly expedite the evidence gathering process. A proof of concept tool was developed for conducting investigations on the BitTorrent network.Comment: This is a thesis submitted in fulfilment of a PhD in Digital Forensics and Cybercrime Investigation in the School of Computer Science, University College Dublin in October 201

    k-Trustee: Location Injection Attack-resilient Anonymization for Location Privacy

    Get PDF
    Cloaking-based location privacy preserving mechanisms have been widely adopted to protect users' location privacy when using location-based services. A fundamental limitation of such mechanisms is that users and their location information in the system are inherently trusted by the Anonymization Server without any verification. In this paper, we show that such an issue could lead to a new class of attacks called location injection attacks which can successfully violate users' in-distinguishability (guaranteed by k-Anonymity) among a set of users. We propose and characterize location injection attacks by presenting a set of attack models and quantify the costs associated with them. We then propose and evaluate k-Trustee, a trust-aware location cloaking mechanism that is resilient to location injection attacks and guarantees a lower bound on the user's in-distinguishability. k-Trustee guarantees that each user in a given cloaked region can achieve the required privacy level of k-Anonymity by including at least k-1 other trusted users in the cloaked region. We demonstrate the effectiveness of k-Trustee through extensive experiments in a real-world geographic map and our experimental results show that the proposed cloaking algorithm guaranteeing k-Trustee is effective against various location injection attacks

    ADDRESSING SELFISHNESS IN THE DESIGN OF COOPERATIVE SYSTEMS

    Get PDF
    I sistemi distribuiti cooperativi, tra cui in particolare i sistemi peer-to-peer, sono oggi alla base di applicazioni Internet di larga diffusione come file-sharing e media streaming, nonch\ue9 di tecnologie emergenti quali Blockchain e l'Internet of Things. Uno dei fattori chiave per il successo di un sistema cooperativo \ue8 che i nodi che vi partecipano mettano a disposizione della comunit\ue0 una parte delle proprie risorse (es. capacit\ue0 di calcolo, banda, spazio disco). Alcuni nodi, poich\ue9 controllati da agenti autonomi e indipendenti, potrebbero tuttavia agire egoisticamente e scegliere di non condividere alcuna risorsa, spinti dall'obiettivo di massimizzare la propria utilit\ue0 anche se a danno delle prestazioni dell'intero sistema. Affrontare l'egoismo dei nodi rappresenta dunque un'attivit\ue0 imprescindibile per lo sviluppo di un sistema cooperativo affidabile e performante. Nonostante il grande numero di tecniche ed approcci presenti in letteratura, tale attivit\ue0 richiede elaborazioni complesse, manuali e laboriose, nonch\ue9 conoscenze approfondite in vari domini di applicazione. Obiettivo di questa tesi \ue8 di fornire strumenti sia pratici che teorici per semplificare lo studio e il contrasto dei comportamenti egoistici nei sistemi cooperativi. Il primo contributo, basato su un'analisi esaustiva dello stato dell'arte sull'egoismo in sistemi distribuiti, presenta un framework di classificazione finalizzato all'identificazione e comprensione dei comportamenti egoistici pi\uf9 importanti su cui concentrarsi durante la progettazione di un sistema cooperativo. Come secondo contributo, presentiamo RACOON, un framework per la progettazione e configurazione di sistemi cooperativi resilienti all'egoismo dei nodi. L'obiettivo di RACOON \ue8 di semplificare tali attivit\ue0 fornendo una metodologia generale e semi-automatica, capace di integrare in un dato sistema pratici meccanismi di incentivo alla cooperazione, attentamente calibrati in modo da raggiungere gli obiettivi di resilienza e performance desiderati. A tal fine, RACOON impiega sia strumenti analitici appartenenti alla teoria dei giochi che metodi simulativi, che vengono utilizzati per fare previsioni sul comportamento del sistema in presenza di nodi egoisti. In questa tesi presentiamo inoltre una versione estesa del framework, chiamata RACOON++, sviluppata per migliorare l'accuratezza, flessibilit\ue0 e usabilit\ue0 del framework originale. Infine, come ultimo contributo del lavoro di tesi, presentiamo SEINE, un framework per la rapida modellazione e analisi sperimentale di vari tipi di comportamenti egoistici in un dato sistema cooperativo. Il framework \ue8 basato su un nuovo linguaggio specifico di dominio (SEINE-L) sviluppato per la descrizione degli scenari di egoismo da analizzare. SEINE fornisce inoltre supporto semi-automatico per l'implementazione e lo studio di tali scenari in un simulatore di sistemi distribuiti selezionato dallo stato dell'arte.Cooperative distributed systems, particularly peer-to-peer systems, are the basis of several mainstream Internet applications (e.g., file-sharing, media streaming) and the key enablers of new and emerging technologies, including blockchain and the Internet of Things. Essential to the success of cooperative systems is that nodes are willing to cooperate with each other by sharing part of their resources, e.g., network bandwidth, CPU capability, storage space. However, as nodes are autonomous entities, they may be tempted to behave in a selfish manner by not contributing their fair share, potentially causing system performance degradation and instability. Addressing selfish nodes is, therefore, key to building efficient and reliable cooperative systems. Yet, it is a challenging task, as current techniques for analysing selfishness and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. In this thesis, we aim to provide practical and conceptual tools to help system designers in dealing with selfish nodes. First, based on a comprehensive survey of existing work on selfishness, we develop a classification framework to identify and understand the most important selfish behaviours to focus on when designing a cooperative system. Second, we propose RACOON, a unifying framework for the selfishness-aware design and configuration of cooperative systems. RACOON provides a semi-automatic methodology to integrate a given system with practical and finely tuned mechanisms to meet specified resilience and performance objectives, using game theory and simulations to predict the behaviour of the system when subjected to selfish nodes. An extension of the framework (RACOON++) is also proposed to improve the accuracy, flexibility, and usability of RACOON. Finally, we propose SEINE, a framework for fast modelling and evaluation of various types of selfish behaviour in a given cooperative system. SEINE relies on a domain-specific language for describing the selfishness scenario to evaluate and provides semi-automatic support for its implementation and study in a state-of-the-art simulator.Les syst\ue8mes distribu\ue9s collaboratifs, en particulier les syst\ue8mes pair-\ue0-pair, forment l\u2019infrastructure sous-jacente de nombreuses applications Internet, certaines parmi les plus populaires (ex\ua0: partage de fichiers, streaming multim\ue9dia). Ils se situent \ue9galement \ue0 la base d\u2019un ensemble de technologies \ue9mergentes telles que la blockchain et l\u2019Internet des Objets. Le succ\ue8s de ces syst\ue8mes repose sur la contribution volontaire, de la part des n\u153uds participants, aux ressources partag\ue9es (ex : bande passante r\ue9seau, puissance de calcul, stockage de donn\ue9es). Or ces n\u153uds sont des entit\ue9s autonomes qui peuvent consid\ue9rer comme plus avantageux de se comporter de mani\ue8re \ue9go\uefste, c\u2019est-\ue0- dire de refuser de collaborer. De tels comportements peuvent fortement impacter les performances et la stabilit\ue9 op\ue9rationnelles du syst\ue8me cible. Prendre en compte et pr\ue9venir les comportements \ue9go\uefstes des n\u153uds est donc essentiel pour garantir l\u2019efficacit\ue9 et la fiabilit\ue9 des syst\ue8mes coop\ue9ratifs. Cependant, cela exige du d\ue9veloppeur, en d\ue9pit de la grande quantit\ue9 de techniques et d\u2019approches propos\ue9es dans la litt\ue9rature, des connaissances multisectorielles approfondies. L'objectif de cette th\ue8se est de concevoir et \ue9tudier de nouveaux outils th\ue9oriques et pratiques pour aider les concepteurs de syst\ue8mes distribu\ue9s collaboratifs \ue0 faire face \ue0 des n\u153uds \ue9go\uefstes. La premi\ue8re contribution, bas\ue9e sur une analyse exhaustive de la litt\ue9rature sur les comportements \ue9go\uefstes dans les syst\ue8mes distribu\ue9s, propose un mod\ue8le de classification pour identifier et analyser les comportements \ue9go\uefstes les plus importants sur lesquels il est important de se concentrer lors de la conception d'un syst\ue8me coop\ue9ratif. Dans la deuxi\ue8me contribution, nous proposons RACOON, un framework pour la conception et la configuration de syst\ue8mes coop\ue9ratifs r\ue9silients aux comportements \ue9go\uefstes. Outre un ensemble de m\ue9canismes d'incitation \ue0 la coop\ue9ration, RACOON fournit une m\ue9thodologie semi-automatique d\u2019int\ue9gration et de calibration de ces m\ue9canismes de mani\ue8re \ue0 garantir le niveau de performance souhait\ue9. RACOON s\u2019appuie sur une analyse du syst\ue8me cible fond\ue9e sur la th\ue9orie des jeux et sur des simulations pour pr\ue9dire l\u2019existence de n\u153uds \ue9go\uefstes dans le syst\ue8me. RACOON a \ue9t\ue9 \ue9tendu en un deuxi\ue8me framework, RACOON++. Plus pr\ue9cis, plus flexible, RACOON++ offre \ue9galement une plus grande facilit\ue9 d'utilisation. Une derni\ue8re contribution, SEINE, propose un framework pour la mod\ue9lisation et l'analyse des diff\ue9rents types de comportements \ue9go\uefstes dans un syst\ue8me coop\ue9ratif. Bas\ue9 sur un langage d\ue9di\ue9, d\ue9velopp\ue9 pour d\ue9crire les sc\ue9narios de comportement \ue9go\uefstes, SEINE fournit un support semi-automatique pour la mise en \u153uvre et l'\ue9tude de ces sc\ue9narios dans un simulateur choisi sur la base de l\u2019\ue9tat de l\u2019art (PeerSim)

    Consensus-based approach to peer-to-peer electricity markets with product differentiation

    Full text link
    With the sustained deployment of distributed generation capacities and the more proactive role of consumers, power systems and their operation are drifting away from a conventional top-down hierarchical structure. Electricity market structures, however, have not yet embraced that evolution. Respecting the high-dimensional, distributed and dynamic nature of modern power systems would translate to designing peer-to-peer markets or, at least, to using such an underlying decentralized structure to enable a bottom-up approach to future electricity markets. A peer-to-peer market structure based on a Multi-Bilateral Economic Dispatch (MBED) formulation is introduced, allowing for multi-bilateral trading with product differentiation, for instance based on consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is described to solve the MBED in fully decentralized manner. A set of realistic case studies and their analysis allow us showing that such peer-to-peer market structures can effectively yield market outcomes that are different from centralized market structures and optimal in terms of respecting consumers preferences while maximizing social welfare. Additionally, the RCI solving approach allows for a fully decentralized market clearing which converges with a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System

    Protecting data privacy with decentralized self-emerging data release systems

    Get PDF
    In the age of Big Data, releasing private data at a future point in time is critical for various applications. Such self-emerging data release requires the data to be protected until a prescribed data release time and be automatically released to the target recipient at the release time. While straight-forward centralized approaches such as cloud storage services may provide a simple way to implement self-emerging data release, unfortunately, they are limited to a single point of trust and involves a single point of control. This dissertation proposes new decentralized designs of self-emerging data release systems using large-scale peer-to-peer (P2P) networks as the underlying infrastructure to eliminate a single point of trust or control. The first part of the dissertation presents the design of decentralized self-emerging data release systems using two different P2P network infrastructures, namely Distributed Hash Table (DHT) and blockchain. The second part of this dissertation proposes new mechanisms for supporting two key functionalities of self-emerging data release, namely (i) enabling the release of self-emerging data to blockchain-based smart contracts for facilitating a wide range of decentralized applications and (ii) supporting a cost-effective gradual release of self-emerging data in the decentralized infrastructure. We believe that the outcome of this dissertation would contribute to the development of decentralized security primitives and protocols in the context of timed release of private data

    Resilience-Building Technologies: State of Knowledge -- ReSIST NoE Deliverable D12

    Get PDF
    This document is the first product of work package WP2, "Resilience-building and -scaling technologies", in the programme of jointly executed research (JER) of the ReSIST Network of Excellenc

    ToR K-Anonymity against deep learning watermarking attacks

    Get PDF
    It is known that totalitarian regimes often perform surveillance and censorship of their communication networks. The Tor anonymity network allows users to browse the Internet anonymously to circumvent censorship filters and possible prosecution. This has made Tor an enticing target for state-level actors and cooperative state-level adversaries, with privileged access to network traffic captured at the level of Autonomous Systems(ASs) or Internet Exchange Points(IXPs). This thesis studied the attack typologies involved, with a particular focus on traffic correlation techniques for de-anonymization of Tor endpoints. Our goal was to design a test-bench environment and tool, based on recently researched deep learning techniques for traffic analysis, to evaluate the effectiveness of countermeasures provided by recent ap- proaches that try to strengthen Tor’s anonymity protection. The targeted solution is based on K-anonymity input covert channels organized as a pre-staged multipath network. The research challenge was to design a test-bench environment and tool, to launch active correlation attacks leveraging traffic flow correlation through the detection of in- duced watermarks in Tor traffic. To de-anonymize Tor connection endpoints, our tool analyses intrinsic time patterns of Tor synthetic egress traffic to detect flows with previ- ously injected time-based watermarks. With the obtained results and conclusions, we contributed to the evaluation of the security guarantees that the targeted K-anonymity solution provides as a countermeasure against de-anonymization attacks.Já foi extensamente observado que em vários países governados por regimes totalitários existe monitorização, e consequente censura, nos vários meios de comunicação utilizados. O Tor permite aos seus utilizadores navegar pela internet com garantias de privacidade e anonimato, de forma a evitar bloqueios, censura e processos legais impostos pela entidade que governa. Estas propriedades tornaram a rede Tor um alvo de ataque para vários governos e ações conjuntas de várias entidades, com acesso privilegiado a extensas zonas da rede e vários pontos de acesso à mesma. Esta tese realiza o estudo de tipologias de ataques que quebram o anonimato da rede Tor, com especial foco em técnicas de correlação de tráfegos. O nosso objetivo é realizar um ambiente de estudo e ferramenta, baseada em técnicas recentes de aprendizagem pro- funda e injeção de marcas de água, para avaliar a eficácia de contramedidas recentemente investigadas, que tentam fortalecer o anonimato da rede Tor. A contramedida que pre- tendemos avaliar é baseada na criação de multi-circuitos encobertos, recorrendo a túneis TLS de entrada, de forma a acoplar o tráfego de um grupo anonimo de K utilizadores. A solução a ser desenvolvida deve lançar um ataque de correlação de tráfegos recorrendo a técnicas ativas de indução de marcas de água. Esta ferramenta deve ser capaz de correla- cionar tráfego sintético de saída de circuitos Tor, realizando a injeção de marcas de água à entrada com o propósito de serem detetadas num segundo ponto de observação. Aplicada a um cenário real, o propósito da ferramenta está enquadrado na quebra do anonimato de serviços secretos fornecidos pela rede Tor, assim como os utilizadores dos mesmos. Os resultados esperados irão contribuir para a avaliação da solução de anonimato de K utilizadores mencionada, que é vista como contramedida para ataques de desanonimi- zação

    A survey on blockchain‐enabled smart grids: advances, applications and challenges

    Get PDF
    Electric power grid infrastructure has revolutionized our world and changed the way of living. So has blockchain technology. The hierarchical electric power grid has been shifting from a centralized structure to a decentralized structure to achieve higher flexibility and stability, and blockchain technology has been widely adopted in the energy sector to deal with grid management, billing, metering, and so on, because of its nature of decentralization. Here, the aim is to provide a multi-dimensional review on the technological advances of the blockchain in smart grids. Its corresponding applications based on these advances, including company projects and use cases, are summarized. Furthermore, the security threat issues in smart grids, Ethereum Virtual Machine (i.e. the operating environment of consensus mechanisms), and smart contracts are analysed, with a brief conclusion to manifest the prior tasks in building secure blockchain-based infrastructures in smart grids. As such, the challenges and features of different protocols and their applicability in each use case are identified to provide an insightful guide for future research studies
    corecore