Analytical and Empirical Analysis of Countermeasures to Traffic Analysis Attacks

This paper studies countermeasures to traffic analysis attacks. A common strategy for such countermeasures is traffic padding. We consider systems where payload traffic may be padded to have either constant inter-arrival times or variable inter-arrival times for their packets. The adversary applies statistical recognition techniques to detect the payload traffic rates and may use statistical measures, such as sample mean, sample variance, or sample entropy, to perform such a detection. We evaluate quantitatively the ability of the adversary to make a correct detection. We derive closed-form formulas for the detection rate based on analytical models we establish. Extensive experiments were carried out to validate the system performance predicted by the analytical method. Based on the systematic evaluations, we develop design guidelines that allow a manager to properly configure a system in order to minimize the detection rate.

Private and censorship-resistant communication over public networks

Society’s increasing reliance on digital communication networks is creating unprecedented opportunities for wholesale surveillance and censorship. This thesis investigates the use of public networks such as the Internet to build robust, private communication systems that can resist monitoring and attacks by powerful adversaries such as national governments. We sketch the design of a censorship-resistant communication system based on peer-to-peer Internet overlays in which the participants only communicate directly with people they know and trust. This ‘friend-to-friend’ approach protects the participants’ privacy, but it also presents two significant challenges. The first is that, as with any peer-to-peer overlay, the users of the system must collectively provide the resources necessary for its operation; some users might prefer to use the system without contributing resources equal to those they consume, and if many users do so, the system may not be able to survive. To address this challenge we present a new game theoretic model of the problem of encouraging cooperation between selfish actors under conditions of scarcity, and develop a strategy for the game that provides rational incentives for cooperation under a wide range of conditions. The second challenge is that the structure of a friend-to-friend overlay may reveal the users’ social relationships to an adversary monitoring the underlying network. To conceal their sensitive relationships from the adversary, the users must be able to communicate indirectly across the overlay in a way that resists monitoring and attacks by other participants. We address this second challenge by developing two new routing protocols that robustly deliver messages across networks with unknown topologies, without revealing the identities of the communication endpoints to intermediate nodes or vice versa. The protocols make use of a novel unforgeable acknowledgement mechanism that proves that a message has been delivered without identifying the source or destination of the message or the path by which it was delivered. One of the routing protocols is shown to be robust to attacks by malicious participants, while the other provides rational incentives for selfish participants to cooperate in forwarding messages

Performance Optimization With An Integrated View Of Compiler And Application Knowledge

Compiler optimization is a long-standing research field that enhances program performance with a set of rigorous code analyses and transformations. Traditional compiler optimization focuses on general programs or program structures without considering too much high-level application operations or data structure knowledge. In this thesis, we claim that an integrated view of the application and compiler is helpful to further improve program performance. Particularly, we study integrated optimization opportunities for three kinds of applications: irregular tree-based query processing systems such as B+ tree, security enhancement such as buffer overflow protection, and tensor/matrix-based linear algebra computation. The performance of B+ tree query processing is important for many applications, such as file systems and databases. Latch-free B+ tree query processing is efficient since the queries are processed in batches without locks. To avoid long latency, the batch size can not be very large. However, modern processors provide opportunities to process larger batches parallel with acceptable latency. From studying real-world data, we find that there are many redundant and unnecessary queries especially when the real-world data is highly skewed. We develop a query sequence transformation framework Qtrans to reduce the redundancies in queries by applying classic dataflow analysis to queries. To further confirm the effectiveness, we integrate Qtrans into an existing BSP-based B+ tree query processing system, PALM tree. The evaluations show that the throughput can be improved up to 16X. Heap overflows are still the most common vulnerabilities in C/C++ programs. Common approaches incur high overhead since it checks every memory access. By analyzing dozens of bugs, we find that all heap overflows are related to arrays. We only need to check array-related memory accesses. We propose Prober to efficiently detect and prevent heap overflows. It contains Prober-Static to identify the array-related allocations and Prober-Dynamic to protect objects at runtime. In this thesis, our contributions lie on the Prober-Static side. The key challenge is to correctly identify the array-related allocations. We propose a hybrid method. Some objects can be identified as array-related (or not) by static analysis. For the remaining ones, we instrument the basic allocation type size statically and then determine the real allocation size at runtime. The evaluations show Prober-Static is effective. Tensor algebra is widely used in many applications, such as machine learning and data analytics. Tensors representing real-world data are usually large and sparse. There are many sparse tensor storage formats, and the kernels are different with varied formats. These different kernels make performance optimization for sparse tensor algebra challenging. We propose a tensor algebra domain-specific language and a compiler to automatically generate kernels for sparse tensor algebra computations, called SPACe. This compiler supports a wide range of sparse tensor formats. To further improve the performance, we integrate the data reordering into SPACe to improve data locality. The evaluations show that the code generated by SPACe outperforms state-of-the-art sparse tensor algebra compilers

Effizientes Programmiermodell für OpenMP auf einem Cluster-basierten Many-Core-System

Da die Komplexität „System-on-Chip“ (SoC) auch weiterhin zunimmt, wird man die Herausforderungen aufgrund der Konvergenz der Software- und Hardwareentwicklung nicht ignorieren können. Dies gilt auch für den Umgang mit dem hierarchischen Design, in dem die Prozessorkerne in Clustern oder sogenannten „Tiles“ angeordnet werden, um mittels eines schnellen lokalen Speicherzugriffs eine geringe Latenz und eine hohe Bandbreite der lokalen Kommunikation zu gewährleisten. Aus der Sicht eines Programmierers ist es wünschenswert, sich diese Eigenheiten der Hardware zunutze zu machen und sie bei der Ausgestaltung der abstrakten Parallel-Programmierung gewissenhaft und zielführend zu berücksichtigen. Diese Dissertation überwindet viele Engpässe in Bezug auf die Skalierbarkeit Cluster-basierter Many-Core-Systeme und führt das Programmiermodell OpenMP zur Vereinfachung der Anwendungsentwicklung ein. OpenMP abstrahiert von der Sichtweise des Programmierers – und es werden Richtlinien eingeführt, mit denen Schleifen in Programmsequenzen eingeteilt werden, als Basis für die parallele Programmierung. In dieser Arbeit wird das OpenMP-Modell bespielhaft in einem konkreten Cluster-basierten Many-Core-System umgesetzt; dem Intel Single-Chip Cloud Computer (SCC). Es wird eine schlanke und hoch-optimierte Laufzeitschicht für die Ausführung von OpenMP sowie ein Speichermodell vorgestellt. Auf Basis dieser Laufzeitschicht wird der parallele Code automatisch von einem nativen Backend-Compiler (GCC 4.6) erzeugt, der mit der Laufzeitbibliothek verknüpft ist. Im Rahmen der Arbeit wird auf einen effizienten Designansatz für die OpenMP-Programmierung eingegangen, wobei der Intel SCC als Beispiel für Cluster-basierte Systeme zum Einsatz kommt. In nicht-Cache-kohärenten Systemen dient die SCC OpenMP Laufzeitbibliothek primär dazu, die folgenden Herausforderungen zu bewältigen: 1. Die Ausführung von unmodifizierten, bestehenden OpenMP Programmen auf solchen Systemen. 2. Die Portierung des OpenMP-Speichermodells auf den SCC. 3. Die Synchronisation der parallelen Threads, auf die ein beträchtlicher Anteil der Ausführungszeit einer Anwendung entfällt. Eine Reihe weiterer Beispiele, basierend auf verschiedenen gebräuchlichen Kernen und realen Anwendungen, untermauert die Tauglichkeit von OpenMP – und eine Reihe von Experimenten zeigt, wie dieses Modell zu einer deutlichen Beschleunigung (bis zu 48-fach) in verschiedenen parallelen Anwendungen führt.As the complexity of systems-on-chip (SoCs) continues to increase, it is no longer possible to ignore the challenges caused by the convergence of software and hardware development. This involves attempts to deal with the hierarchical design – in which several cores are grouped in clusters or tiles – to ensure low-latency, high-bandwidth local communication by relying on fast local memories. From a programmer’s perspec- tive, it is desirable to make use of these peculiarities of the hardware, which must be clearly and carefully taken into account when designing the support for high-level parallel programming models. This dissertation overcomes many scalability bottlenecks in cluster-based many-core systems and introduces the OpenMP programming model as a means of simplifying application development. OpenMP represents an abstraction of the programmer’s view by providing abundant directives that decompose loops in sequential programs and lead to parallel programs. In this work, the full OpenMP model is implemented on a specific instance of a cluster-based many-core system: the Intel Single-chip Cloud Computer (SCC). In this thesis, a lightweight and highly optimized runtime layer for OpenMP execution and memory model by generating the parallel code that is automatically compiled by native back-end compiler (GCC 4.6) that linked with the runtime library. In this dissertation, I will address an efficient design approach of the OpenMP pro- gramming model for the Intel SCC as an example for cluster-based systems. The SCC OpenMP runtime library is designed to cope with three main challenges in a non-cache coherent system: 1. Executing unmodified legacy OpenMP programs on such system. 2. Landing OpenMP memory model on the SCC. 3. Synchronization in the work of parallel threads accounts for a sizeable fraction of an application’s execution time. Furthermore, the effectiveness of OpenMP is demonstrated on a set of widely used kernels and real-world applications. An extensive set of experiments shows how this model achieves significant parallel speedups up to 48x in several applications

Advanced methods for query routing in peer-to-peer information retrieval

One of the most challenging problems in peer-to-peer networks is query routing: effectively and efficiently identifying peers that can return high-quality local results for a given query. Existing methods from the areas of distributed information retrieval and metasearch engines do not adequately address the peculiarities of a peer-to-peer network. The main contributions of this thesis are as follows: 1. Methods for query routing that take into account the mutual overlap of different peers\u27; collections, 2. Methods for query routing that take into account the correlations between multiple terms, 3. Comparative evaluation of different query routing methods. Our experiments confirm the superiority of our novel query routing methods over the prior state-of-the-art, in particular in the context of peer-to-peer Web search.Eines der drängendsten Probleme in Peer-to-Peer-Netzwerken ist Query-Routing: das effektive und effiziente Identifizieren solcher Peers, die qualitativ hochwertige lokale Ergebnisse zu einer gegebenen Anfrage liefern können. Die bisher bekannten Verfahren aus dem Bereich der verteilten Informationssuche sowie der Metasuchmaschinen werden den Besonderheiten von Peer-to-Peer-Netzwerken nicht gerecht. Die Hautbeiträge dieser Arbeit teilen sich in folgende Schwerpunkte: 1. Query-Routing unter Berücksichtigung der gegenseitigen überlappung der Kollektionen verschiedener Peers, 2. Query-Routing unter Berücksichtigung der Korrelationen zwischen verschiedenen Termen, 3. Vergleichende Evaluierung verschiedener Methoden zum Query-Routing. Unsere Experimente bestätigen die Überlegenheit der in dieser Arbeit entwickelten Verfahren gegenüber den bisher bekannten Verfahren, insbesondere im Kontext von Peer-to-Peer-Websuche

Decentralized link analysis in peer-to-peer web search networks

Analyzing the authority or reputation of entities that are connected by a graph structure and ranking these entities is an important issue that arises in the Web, in Web 2.0 communities, and in other applications. The problem is typically addressed by computing the dominant eigenvector of a matrix that is suitably derived from the underlying graph, or by performing a full spectral decomposition of the matrix. Although such analyses could be performed by a centralized server, there are good reasons that suggest running theses computations in a decentralized manner across many peers, like scalability, privacy, censorship, etc. There exist a number of approaches for speeding up the analysis by partitioning the graph into disjoint fragments. However, such methods are not suitable for a peer-to-peer network, where overlap among the fragments might occur. In addition, peer-to-peer approaches need to consider network characteristics, such as peers unaware of other peers' contents, susceptibility to malicious attacks, and network dynamics (so-called churn). In this thesis we make the following major contributions. We present JXP, a decentralized algorithm for computing authority scores of entities distributed in a peer-to-peer (P2P) network that allows peers to have overlapping content and requires no a priori knowledge of other peers' content. We also show the benets of JXP in the Minerva distributed Web search engine. We present an extension of JXP, coined TrustJXP, that contains a reputation model in order to deal with misbehaving peers. We present another extension of JXP, that handles dynamics on peer-to-peer networks, as well as an algorithm for estimating the current number of entities in the network. This thesis also presents novel methods for embedding JXP in peer-to-peer networks and applications. We present an approach for creating links among peers, forming semantic overlay networks, where peers are free to decide which connections they create and which they want to avoid based on various usefulness estimators. We show how peer-to-peer applications, like the JXP algorithm, can greatly benet from these additional semantic relations.Die Berechnung von Autoritäts- oder Reputationswerten für Knoten eines Graphen, welcher verschiedene Entitäten verknüpft, ist von großem Interesse in Web-Anwendungen, z.B. in der Analyse von Hyperlinkgraphen, Web 2.0 Portalen, sozialen Netzen und anderen Anwendungen. Die Lösung des Problems besteht oftmals im Kern aus der Berechnung des dominanten Eigenvektors einer Matrix, die vom zugrunde liegenden Graphen abgeleitet wird. Obwohl diese Analysen in einer zentralisierten Art und Weise berechnet werden können, gibt es gute Gründe, diese Berechnungen auf mehrere Knoten eines Netzwerkes zu verteilen, insbesondere bezüglich Skalierbarkeit, Datenschutz und Zensur. In der Literatur finden sich einige Methoden, welche die Berechnung beschleunigen, indem der zugrunde liegende Graph in nicht überlappende Teilgraphen zerlegt wird. Diese Annahme ist in Peer-to-Peer-System allerdings nicht realistisch, da die einzelnen Peers ihre Graphen in einer nicht synchronisierten Weise erzeugen, was inhärent zu starken oder weniger starken Überlappungen der Graphen führt. Darüber hinaus sind Peer-to-Peer-Systeme per Definition ein lose gekoppelter Zusammenschluss verschiedener Benutzer (Peers), verteilt im ganzen Internet, so dass Netzwerkcharakteristika, Netzwerkdynamik und mögliche Attacken krimineller Benutzer unbedingt berücksichtigt werden müssen. In dieser Arbeit liefern wir die folgenden grundlegenden Beiträge. Wir präsentieren JXP, einen verteilten Algorithmus für die Berechnung von Autoritätsmaßen über Entitäten in einem Peer-to-Peer Netzwerk. Wir präsentieren Trust-JXP, eine Erweiterung von JXP, ausgestattet mit einem Modell zur Berechnung von Reputationswerten, die benutzt werden, um bösartig agierende Benutzer zu identizieren. Wir betrachten, wie JXP robust gegen Veränderungen des Netzwerkes gemacht werden kann und wie die Anzahl der verschiedenen Entitäten im Netzwerk effizient geschätzt werden kann. Darüber hinaus beschreiben wir in dieser Arbeit neuartige Ansätze, JXP in bestehende Peer-to-Peer-Netzwerke einzubinden. Wir präsentieren eine Methode, mit deren Hilfe Peers entscheiden können, welche Verbindungen zu anderen Peers von Nutzen sind und welche Verbindungen vermieden werden sollen. Diese Methode basiert auf verschiedenen Qualitätsindikatoren, und wir zeigen, wie Peer-to-Peer-Anwendungen, zum Beispiel JXP, von diesen zusätzlichen Relationen profitieren können

Decentralized link analysis in peer-to-peer web search networks

Analyzing the authority or reputation of entities that are connected by a graph structure and ranking these entities is an important issue that arises in the Web, in Web 2.0 communities, and in other applications. The problem is typically addressed by computing the dominant eigenvector of a matrix that is suitably derived from the underlying graph, or by performing a full spectral decomposition of the matrix. Although such analyses could be performed by a centralized server, there are good reasons that suggest running theses computations in a decentralized manner across many peers, like scalability, privacy, censorship, etc. There exist a number of approaches for speeding up the analysis by partitioning the graph into disjoint fragments. However, such methods are not suitable for a peer-to-peer network, where overlap among the fragments might occur. In addition, peer-to-peer approaches need to consider network characteristics, such as peers unaware of other peers' contents, susceptibility to malicious attacks, and network dynamics (so-called churn). In this thesis we make the following major contributions. We present JXP, a decentralized algorithm for computing authority scores of entities distributed in a peer-to-peer (P2P) network that allows peers to have overlapping content and requires no a priori knowledge of other peers' content. We also show the benets of JXP in the Minerva distributed Web search engine. We present an extension of JXP, coined TrustJXP, that contains a reputation model in order to deal with misbehaving peers. We present another extension of JXP, that handles dynamics on peer-to-peer networks, as well as an algorithm for estimating the current number of entities in the network. This thesis also presents novel methods for embedding JXP in peer-to-peer networks and applications. We present an approach for creating links among peers, forming semantic overlay networks, where peers are free to decide which connections they create and which they want to avoid based on various usefulness estimators. We show how peer-to-peer applications, like the JXP algorithm, can greatly benet from these additional semantic relations.Die Berechnung von Autoritäts- oder Reputationswerten für Knoten eines Graphen, welcher verschiedene Entitäten verknüpft, ist von großem Interesse in Web-Anwendungen, z.B. in der Analyse von Hyperlinkgraphen, Web 2.0 Portalen, sozialen Netzen und anderen Anwendungen. Die Lösung des Problems besteht oftmals im Kern aus der Berechnung des dominanten Eigenvektors einer Matrix, die vom zugrunde liegenden Graphen abgeleitet wird. Obwohl diese Analysen in einer zentralisierten Art und Weise berechnet werden können, gibt es gute Gründe, diese Berechnungen auf mehrere Knoten eines Netzwerkes zu verteilen, insbesondere bezüglich Skalierbarkeit, Datenschutz und Zensur. In der Literatur finden sich einige Methoden, welche die Berechnung beschleunigen, indem der zugrunde liegende Graph in nicht überlappende Teilgraphen zerlegt wird. Diese Annahme ist in Peer-to-Peer-System allerdings nicht realistisch, da die einzelnen Peers ihre Graphen in einer nicht synchronisierten Weise erzeugen, was inhärent zu starken oder weniger starken Überlappungen der Graphen führt. Darüber hinaus sind Peer-to-Peer-Systeme per Definition ein lose gekoppelter Zusammenschluss verschiedener Benutzer (Peers), verteilt im ganzen Internet, so dass Netzwerkcharakteristika, Netzwerkdynamik und mögliche Attacken krimineller Benutzer unbedingt berücksichtigt werden müssen. In dieser Arbeit liefern wir die folgenden grundlegenden Beiträge. Wir präsentieren JXP, einen verteilten Algorithmus für die Berechnung von Autoritätsmaßen über Entitäten in einem Peer-to-Peer Netzwerk. Wir präsentieren Trust-JXP, eine Erweiterung von JXP, ausgestattet mit einem Modell zur Berechnung von Reputationswerten, die benutzt werden, um bösartig agierende Benutzer zu identizieren. Wir betrachten, wie JXP robust gegen Veränderungen des Netzwerkes gemacht werden kann und wie die Anzahl der verschiedenen Entitäten im Netzwerk effizient geschätzt werden kann. Darüber hinaus beschreiben wir in dieser Arbeit neuartige Ansätze, JXP in bestehende Peer-to-Peer-Netzwerke einzubinden. Wir präsentieren eine Methode, mit deren Hilfe Peers entscheiden können, welche Verbindungen zu anderen Peers von Nutzen sind und welche Verbindungen vermieden werden sollen. Diese Methode basiert auf verschiedenen Qualitätsindikatoren, und wir zeigen, wie Peer-to-Peer-Anwendungen, zum Beispiel JXP, von diesen zusätzlichen Relationen profitieren können