Secure Communication in Disaster Scenarios

Während Naturkatastrophen oder terroristischer Anschläge ist die bestehende Kommunikationsinfrastruktur häufig überlastet oder fällt komplett aus. In diesen Situationen können mobile Geräte mithilfe von drahtloser ad-hoc- und unterbrechungstoleranter Vernetzung miteinander verbunden werden, um ein Notfall-Kommunikationssystem für Zivilisten und Rettungsdienste einzurichten. Falls verfügbar, kann eine Verbindung zu Cloud-Diensten im Internet eine wertvolle Hilfe im Krisen- und Katastrophenmanagement sein. Solche Kommunikationssysteme bergen jedoch ernsthafte Sicherheitsrisiken, da Angreifer versuchen könnten, vertrauliche Daten zu stehlen, gefälschte Benachrichtigungen von Notfalldiensten einzuspeisen oder Denial-of-Service (DoS) Angriffe durchzuführen. Diese Dissertation schlägt neue Ansätze zur Kommunikation in Notfallnetzen von mobilen Geräten vor, die von der Kommunikation zwischen Mobilfunkgeräten bis zu Cloud-Diensten auf Servern im Internet reichen. Durch die Nutzung dieser Ansätze werden die Sicherheit der Geräte-zu-Geräte-Kommunikation, die Sicherheit von Notfall-Apps auf mobilen Geräten und die Sicherheit von Server-Systemen für Cloud-Dienste verbessert

Identifying and Preventing Large-scale Internet Abuse

The widespread access to the Internet and the ubiquity of web-based services make it easy to communicate and interact globally. Unfortunately, the software and protocols implementing the functionality of these services are often vulnerable to attacks. In turn, an attacker can exploit them to compromise, take over, and abuse the services for her own nefarious purposes. In this dissertation, we aim to better understand such attacks, and we develop methods and algorithms to detect and prevent them, which we evaluate on large-scale datasets.First, we detail Meerkat, a system to detect a visible way in which websites are being compromised, namely website defacements. They can inflict significant harm on the websites’ operators through the loss of sales, the loss in reputation, or because of legal ramifications. Meerkat requires no prior knowledge about the websites’ content or their structure, but only the Uniform Resource Identifier (URI) at which they can be reached. By design, Meerkat mimics how a human analyst decides if a website was defaced when viewing it in a browser, by using computer vision techniques. Thus, it tackles the problem of detecting website defacements through their attention-seeking nature, their goal and purpose, rather than code or data artifacts that they might exhibit. In turn, it is much harder for an attacker to evade our system, as she needs to change her modus operandi. When Meerkat detects a website as defaced, the website can automatically be put into maintenance mode or restored to a known good state.An attacker, however, is not limited to abuse a compromised website in a way that is visible to the website’s visitors. Instead, she can misuse the website to infect its visitors with malicious software (malware). Although malware is well studied, identifying malicious websites remains a major challenge in today’s Internet. Second, we introduce Delta, a novel, purely static analysis approach that extracts change-related features between two versions of the same website, uses machine learning to derive a model of website changes, detects if an introduced change was malicious or benign, identifies the underlying infection vector based on clustering, and generates an identifying signature. Furthermore, due to the way Delta clusters campaigns, it can uncover infection campaigns that leverage specific vulnerable applications as a distribution channel, and it can greatly reduce the human labor necessary to uncover the application responsible for a service’s compromise.Third, we investigate the practicality and impact of domain takeover attacks, which an attacker can similarly abuse to spread misinformation or malware, and we present a defense on how such takeover attacks can be rendered toothless. Specifically, the new elasticity of Internet resources, in particular Internet protocol (IP) addresses in the context of Infrastructure-as-a-Service cloud service providers, combined with previously made protocol assumptions can lead to security issues. In Cloud Strife, we show that this dynamic component paired with recent developments in trust-based ecosystems (e.g., Transport Layer Security (TLS) certificates) creates so far unknown attack vectors. For example, a substantial number of stale domain name system (DNS) records points to readily available IP addresses in clouds, yet, they are still actively attempted to be accessed. Often, these records belong to discontinued services that were previously hosted in the cloud. We demonstrate that it is practical, and time and cost-efficient for attackers to allocate the IP addresses to which stale DNS records point. Further considering the ubiquity of domain validation in trust ecosystems, an attacker can impersonate the service by obtaining and using a valid certificate that is trusted by all major operating systems and browsers, which severely increases the attackers’ capabilities. The attacker can then also exploit residual trust in the domain name for phishing, receiving and sending emails, or possibly distributing code to clients that load remote code from the domain (e.g., loading of native code by mobile apps, or JavaScript libraries by websites). To prevent such attacks, we introduce a new authentication method for trust-based domain validation that mitigates staleness issues without incurring additional certificate requester effort by incorporating existing trust into the validation process.Finally, the analyses of Delta, Meerkat, and Cloud Strife have made use of large-scale measurements to assess our approaches’ impact and viability. Indeed, security research in general has made extensive use of exhaustive Internet-wide scans over the recent years, as they can provide significant insights into the state of security of the Internet (e.g., if classes of devices are behaving maliciously, or if they might be insecure and could turn malicious in an instant). However, the address space of the Internet’s core addressing protocol (Internet Protocol version 4; IPv4) is exhausted, and a migration to its successor (Internet Protocol version 6; IPv6), the only accepted long-term solution, is inevitable. In turn, to better understand the security of devices connected to the Internet, in particular Internet of Things devices, it is imperative to include IPv6 addresses in security evaluations and scans. Unfortunately, it is practically infeasible to iterate through the entire IPv6 address space, as it is 296 times larger than the IPv4 address space. Without enumerating hosts prior to scanning, we will be unable to retain visibility into the overall security of Internet-connected devices in the future, and we will be unable to detect and prevent their abuse or compromise. To mitigate this blind spot, we introduce a novel technique to enumerate part of the IPv6 address space by walking DNSSEC-signed IPv6 reverse zones. We show (i) that enumerating active IPv6 hosts is practical without a preferential network position contrary to common belief, (ii) that the security of active IPv6 hosts is currently still lagging behind the security state of IPv4 hosts, and (iii) that unintended default IPv6 connectivity is a major security issue

Fast Internet-Wide Scanning: A New Security Perspective

Techniques like passive observation and random sampling let researchers understand many aspects of Internet day-to-day operation, yet these methodologies often focus on popular services or a small demographic of users, rather than providing a comprehensive view of the devices and services that constitute the Internet. As the diversity of devices and the role they play in critical infrastructure increases, so does understanding the dynamics of and securing these hosts. This dissertation shows how fast Internet-wide scanning provides a near-global perspective of edge hosts that enables researchers to uncover security weaknesses that only emerge at scale. First, I show that it is possible to efficiently scan the IPv4 address space. ZMap: a network scanner specifically architected for large-scale research studies can survey the entire IPv4 address space from a single machine in under an hour at 97% of the theoretical maximum speed of gigabit Ethernet with an estimated 98% coverage of publicly available hosts. Building on ZMap, I introduce Censys, a public service that maintains up-to-date and legacy snapshots of the hosts and services running across the public IPv4 address space. Censys enables researchers to efficiently ask a range of security questions. Next, I present four case studies that highlight how Internet-wide scanning can identify new classes of weaknesses that only emerge at scale, uncover unexpected attacks, shed light on previously opaque distributed systems on the Internet, and understand the impact of consequential vulnerabilities. Finally, I explore how in- creased contention over IPv4 addresses introduces new challenges for performing large-scale empirical studies. I conclude with suggested directions that the re- search community needs to consider to retain the degree of visibility that Internet-wide scanning currently provides.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138660/1/zakir_1.pd

The Dilemma of Security Smells and How to Escape It

A single mobile app can now be more complex than entire operating systems ten years ago, thus security becomes a major concern for mobile apps. Unfortunately, previous studies focused rather on particular aspects of mobile application security and did not provide a holistic overview of security issues. Therefore, they could not accurately understand the fundamental flaws to propose effective solutions to common security problems. In order to understand these fundamental flaws, we followed a hybrid strategy, i.e., we collected reported issues from existing work, and we actively identified security-related code patterns that violate best practices in software development. We further introduced the term ``security smell,'' i.e., a security issue that could potentially lead to a vulnerability. As a result, we were able to establish comprehensive security smell catalogues for Android apps and related components, i.e., inter-component communication, web communication, app servers, and HTTP clients. Furthermore, we could identify a dilemma of security smells, because most security smells require unique fixes that increase the code complexity, which in return increases the risk of introducing more security smells. With this knowledge, we investigate the interaction of our security smells with the 192 Mitre CAPEC attack mechanism categories of which the majority could be mitigated with just a few additional security measures. These measures, a String class with behavior and the more thorough use of secure default values and paradigms, would simplify the application logic and at the same time largely increase security if implemented appropriately. We conclude that application security has to focus on the String class, which has not largely changed over the last years, and secure default values and paradigms since they are the smallest common denominator for a strong foundation to build resilient applications. Moreover, we provide an initial implementation for a String class with behavior, however the further exploration remains future work. Finally, the term ``security smell'' is now widely used in academia and eases the communication among security researchers

Retrofitting privacy controls to stock Android

Android ist nicht nur das beliebteste Betriebssystem für mobile Endgeräte, sondern auch ein ein attraktives Ziel für Angreifer. Um diesen zu begegnen, nutzt Androids Sicherheitskonzept App-Isolation und Zugangskontrolle zu kritischen Systemressourcen. Nutzer haben dabei aber nur wenige Optionen, App-Berechtigungen gemäß ihrer Bedürfnisse einzuschränken, sondern die Entwickler entscheiden über zu gewährende Berechtigungen. Androids Sicherheitsmodell kann zudem nicht durch Dritte angepasst werden, so dass Nutzer zum Schutz ihrer Privatsphäre auf die Gerätehersteller angewiesen sind. Diese Dissertation präsentiert einen Ansatz, Android mit umfassenden Privatsphäreeinstellungen nachzurüsten. Dabei geht es konkret um Techniken, die ohne Modifikationen des Betriebssystems oder Zugriff auf Root-Rechte auf regulären Android-Geräten eingesetzt werden können. Der erste Teil dieser Arbeit etabliert Techniken zur Durchsetzung von Sicherheitsrichtlinien für Apps mithilfe von inlined reference monitors. Dieser Ansatz wird durch eine neue Technik für dynamic method hook injection in Androids Java VM erweitert. Schließlich wird ein System eingeführt, das prozessbasierte privilege separation nutzt, um eine virtualisierte App-Umgebung zu schaffen, um auch komplexe Sicherheitsrichtlinien durchzusetzen. Eine systematische Evaluation unseres Ansatzes konnte seine praktische Anwendbarkeit nachweisen und mehr als eine Million Downloads unserer Lösung zeigen den Bedarf an praxisgerechten Werkzeugen zum Schutz der Privatsphäre.Android is the most popular operating system for mobile devices, making it a prime target for attackers. To counter these, Android’s security concept uses app isolation and access control to critical system resources. However, Android gives users only limited options to restrict app permissions according to their privacy preferences but instead lets developers dictate the permissions users must grant. Moreover, Android’s security model is not designed to be customizable by third-party developers, forcing users to rely on device manufacturers to address their privacy concerns. This thesis presents a line of work that retrofits comprehensive privacy controls to the Android OS to put the user back in charge of their device. It focuses on developing techniques that can be deployed to stock Android devices without firmware modifications or root privileges. The first part of this dissertation establishes fundamental policy enforcement on thirdparty apps using inlined reference monitors to enhance Android’s permission system. This approach is then refined by introducing a novel technique for dynamic method hook injection on Android’s Java VM. Finally, we present a system that leverages process-based privilege separation to provide a virtualized application environment that supports the enforcement of complex security policies. A systematic evaluation of our approach demonstrates its practical applicability, and over one million downloads of our solution confirm user demand for privacy-enhancing tools

Secure Information Sharing with Distributed Ledgers

In 2009, blockchain technology was first introduced as the supporting database technology for digital currencies. Since then, more advanced derivations of the technology have been developed under the broader term Distributed Ledgers, with improved scalability and support for general-purpose application logic. As a distributed database, they are able to support interorganizational information sharing while assuring desirable information security attributes like non-repudiation, auditability and transparency. Based on these characteristics, researchers and practitioners alike have begun to identify a plethora of disruptive use cases for Distributed Ledgers in existing application domains. While these use cases are promising significant efficiency improvements and cost reductions, practical adoption has been slow in the past years. This dissertation focuses on improving three aspects contributing to slow adoption. First, it attempts to identify application areas and substantiated use cases where Distributed Ledgers can considerably advance the security of information sharing. Second, it considers the security aspects of the technology itself, identifying threats to practical applications and detection approaches for these threats. And third, it investigates success factors for successful interorganizational collaborations using Distributed Ledgers

The Dilemma of Security Smells and How to Escape It

A single mobile app can now be more complex than entire operating systems ten years ago, thus security becomes a major concern for mobile apps. Unfortunately, previous studies focused rather on particular aspects of mobile application security and did not provide a holistic overview of security issues. Therefore, they could not accurately understand the fundamental flaws to propose effective solutions to common security problems. In order to understand these fundamental flaws, we followed a hybrid strategy, i.e., we collected reported issues from existing work, and we actively identified security-related code patterns that violate best-practices in software development. Based on these findings, we compiled a list of security smells, i.e., security issues that could potentially lead to a vulnerability. As a result, we were able to establish comprehensive security smell catalogues for Android apps and related components, i.e., inter-component communication, web communication, app servers, and HTTP clients. Furthermore, we could identify a dilemma of security smells, because most security smells require unique fixes that increase the code complexity, which in return increases the risk of introducing more security smells. With this knowledge, we investigate the interaction of our security smells with the 192 Mitre CAPEC attack mechanism categories of which the majority could be mitigated with just a few additional security measures. These measures, a String class with behavior and the more thorough use of secure default values and paradigms, would simplify the application logic and at the same time largely increase security if implemented appropriately. We conclude that application security has to focus on the String class, which has not largely changed over the last years, and secure default values and paradigms since they are the smallest common denominator for a strong foundation to build resilient applications. Moreover, we provide an initial implementation for a String class with behavior, however the further exploration remains future work. Finally, the term "security smell" is now widely used in academia and eases the communication among security researchers

Cloud-edge hybrid applications

Many modern applications are designed to provide interactions among users, including multi- user games, social networks and collaborative tools. Users expect application response time to be in the order of milliseconds, to foster interaction and interactivity. The design of these applications typically adopts a client-server model, where all interac- tions are mediated by a centralized component. This approach introduces availability and fault- tolerance issues, which can be mitigated by replicating the server component, and even relying on geo-replicated solutions in cloud computing infrastructures. Even in this case, the client-server communication model leads to unnecessary latency penalties for geographically close clients and high operational costs for the application provider. This dissertation proposes a cloud-edge hybrid model with secure and ecient propagation and consistency mechanisms. This model combines client-side replication and client-to-client propagation for providing low latency and minimizing the dependency on the server infras- tructure, fostering availability and fault tolerance. To realize this model, this works makes the following key contributions. First, the cloud-edge hybrid model is materialized by a system design where clients maintain replicas of the data and synchronize in a peer-to-peer fashion, and servers are used to assist clients’ operation. We study how to bring most of the application logic to the client-side, us- ing the centralized service primarily for durability, access control, discovery, and overcoming internetwork limitations. Second, we dene protocols for weakly consistent data replication, including a novel CRDT model (∆-CRDTs). We provide a study on partial replication, exploring the challenges and fundamental limitations in providing causal consistency, and the diculty in supporting client- side replicas due to their ephemeral nature. Third, we study how client misbehaviour can impact the guarantees of causal consistency. We propose new secure weak consistency models for insecure settings, and algorithms to enforce such consistency models. The experimental evaluation of our contributions have shown their specic benets and limitations compared with the state-of-the-art. In general, the cloud-edge hybrid model leads to faster application response times, lower client-to-client latency, higher system scalability as fewer clients need to connect to servers at the same time, the possibility to work oine or disconnected from the server, and reduced server bandwidth usage. In summary, we propose a hybrid of cloud-and-edge which provides lower user-to-user la- tency, availability under server disconnections, and improved server scalability – while being ecient, reliable, and secure.Muitas aplicações modernas são criadas para fornecer interações entre utilizadores, incluindo jogos multiutilizador, redes sociais e ferramentas colaborativas. Os utilizadores esperam que o tempo de resposta nas aplicações seja da ordem de milissegundos, promovendo a interação e interatividade. A arquitetura dessas aplicações normalmente adota um modelo cliente-servidor, onde todas as interações são mediadas por um componente centralizado. Essa abordagem apresenta problemas de disponibilidade e tolerância a falhas, que podem ser mitigadas com replicação no componente do servidor, até com a utilização de soluções replicadas geogracamente em infraestruturas de computação na nuvem. Mesmo neste caso, o modelo de comunicação cliente-servidor leva a penalidades de latência desnecessárias para clientes geogracamente próximos e altos custos operacionais para o provedor das aplicações. Esta dissertação propõe um modelo híbrido cloud-edge com mecanismos seguros e ecientes de propagação e consistência. Esse modelo combina replicação do lado do cliente e propagação de cliente para cliente para fornecer baixa latência e minimizar a dependência na infraestrutura do servidor, promovendo a disponibilidade e tolerância a falhas. Para realizar este modelo, este trabalho faz as seguintes contribuições principais. Primeiro, o modelo híbrido cloud-edge é materializado por uma arquitetura do sistema em que os clientes mantêm réplicas dos dados e sincronizam de maneira ponto a ponto e onde os servidores são usados para auxiliar na operação dos clientes. Estudamos como trazer a maior parte da lógica das aplicações para o lado do cliente, usando o serviço centralizado principalmente para durabilidade, controlo de acesso, descoberta e superação das limitações inter-rede. Em segundo lugar, denimos protocolos para replicação de dados fracamente consistentes, incluindo um novo modelo de CRDTs (∆-CRDTs). Fornecemos um estudo sobre replicação parcial, explorando os desaos e limitações fundamentais em fornecer consistência causal e a diculdade em suportar réplicas do lado do cliente devido à sua natureza efémera. Terceiro, estudamos como o mau comportamento da parte do cliente pode afetar as garantias da consistência causal. Propomos novos modelos seguros de consistência fraca para congurações inseguras e algoritmos para impor tais modelos de consistência. A avaliação experimental das nossas contribuições mostrou os benefícios e limitações em comparação com o estado da arte. Em geral, o modelo híbrido cloud-edge leva a tempos de resposta nas aplicações mais rápidos, a uma menor latência de cliente para cliente e à possibilidade de trabalhar oine ou desconectado do servidor. Adicionalmente, obtemos uma maior escalabilidade do sistema, visto que menos clientes precisam de estar conectados aos servidores ao mesmo tempo e devido à redução na utilização da largura de banda no servidor. Em resumo, propomos um modelo híbrido entre a orla (edge) e a nuvem (cloud) que fornece menor latência entre utilizadores, disponibilidade durante desconexões do servidor e uma melhor escalabilidade do servidor – ao mesmo tempo que é eciente, conável e seguro

How\u27s My Network - Incentives and Impediments of Home Network Measurements

Gathering meaningful information from Home Networking (HN) environments has presented researchers with measurement strategy challenges. A measurement platform is typically designed around the process of gathering data from a range of devices or usage statistics in a network that are specifically behind the HN firewall. HN studies require a fine balance between incentives and impediments to promote usage and minimize efforts for user participation with the focus on gathering robust datasets and results. In this dissertation we explore how to gather data from the HN Ecosystem (e.g. devices, apps, permissions, configurations) and feedback from HN users across a multitude of HN infrastructures, leveraging low impediment and low/high incentive methods to entice user participation. We look to understand the trade-offs of using a variety of approach types (e.g. Java Applet, Mobile app, survey) for data collections, user preferences, and how HN users react and make changes to the HN environment when presented with privacy/security concerns, norms of comparisons (e.g. comparisons to the local environment and to other HNs) and other HN results. We view that the HN Ecosystem is more than just “the network” as it also includes devices and apps within the HN. We have broken this dissertation down into the following three pillars of work to understand incentives and impediments of user participation and data collections. These pillars include: 1) preliminary work, as part of the How\u27s My Network (HMN) measurement platform, a deployed signed Java applet that provided a user-centered network measurement platform to minimize user impediments for data collection, 2) a HN user survey on preference, comfort, and usability of HNs to understand incentives, and 3) the creation and deployment of a multi-faceted How\u27s My Network Mobile app tool to gather and compare attributes and feedback with high incentives for user participation; as part of this flow we also include related approaches and background work. The HMN Java applet work demonstrated the viability of using a Web browser to obtain network performance data from HNs via a user-centric network measurement platform that minimizes impediments for user participation. The HMN HN survey work found that users prefer to leverage a Mobile app for HN data collections, and can be incentivized to participate in a HN study by providing attributes and characteristics of the HN Ecosystem. The HMN Mobile app was found to provide high incentives, with minimal impediments, for participation with focus on user Privacy and Security concerns. The HMN Mobile app work found that 84\% of users reported a change in perception of privacy and security, 32\% of users uninstalled apps, and 24\% revoked permissions in their HN. As a by-product of this work we found it was possible to gather sensitive information such as previously attached networks, installed apps and devices on the network. This information exposure to any installed app with minimal or no granted permissions is a potential privacy concern