Towards Applying Cryptographic Security Models to Real-World Systems

The cryptographic methodology of formal security analysis usually works in three steps: choosing a security model, describing a system and its intended security properties, and creating a formal proof of security. For basic cryptographic primitives and simple protocols this is a well understood process and is performed regularly. For more complex systems, as they are in use in real-world settings it is rarely applied, however. In practice, this often leads to missing or incomplete descriptions of the security properties and requirements of such systems, which in turn can lead to insecure implementations and consequent security breaches. One of the main reasons for the lack of application of formal models in practice is that they are particularly difficult to use and to adapt to new use cases. With this work, we therefore aim to investigate how cryptographic security models can be used to argue about the security of real-world systems. To this end, we perform case studies of three important types of real-world systems: data outsourcing, computer networks and electronic payment. First, we give a unified framework to express and analyze the security of data outsourcing schemes. Within this framework, we define three privacy objectives: \emph{data privacy}, \emph{query privacy}, and \emph{result privacy}. We show that data privacy and query privacy are independent concepts, while result privacy is consequential to them. We then extend our framework to allow the modeling of \emph{integrity} for the specific use case of file systems. To validate our model, we show that existing security notions can be expressed within our framework and we prove the security of CryFS---a cryptographic cloud file system. Second, we introduce a model, based on the Universal Composability (UC) framework, in which computer networks and their security properties can be described We extend it to incorporate time, which cannot be expressed in the basic UC framework, and give formal tools to facilitate its application. For validation, we use this model to argue about the security of architectures of multiple firewalls in the presence of an active adversary. We show that a parallel composition of firewalls exhibits strictly better security properties than other variants. Finally, we introduce a formal model for the security of electronic payment protocols within the UC framework. Using this model, we prove a set of necessary requirements for secure electronic payment. Based on these findings, we discuss the security of current payment protocols and find that most are insecure. We then give a simple payment protocol inspired by chipTAN and photoTAN and prove its security within our model. We conclude that cryptographic security models can indeed be used to describe the security of real-world systems. They are, however, difficult to apply and always need to be adapted to the specific use case

Malware-Resistant Protocols for Real-World Systems

Cryptographic protocols are widely used to protect real-world systems from attacks. Paying for goods in a shop, withdrawing money or browsing the Web; all these activities are backed by cryptographic protocols. However, in recent years a potent threat became apparent. Malware is increasingly used in attacks to bypass existing security mechanisms. Many cryptographic protocols that are used in real-world systems today have been found to be susceptible to malware attacks. One reason for this is that most of these protocols were designed with respect to the Dolev-Yao attack model that assumes an attacker to control the network between computer systems but not the systems themselves. Furthermore, most real-world protocols do not provide a formal proof of security and thus lack a precise definition of the security goals the designers tried to achieve. This work tackles the design of cryptographic protocols that are resilient to malware attacks, applicable to real-world systems, and provably secure. In this regard, we investigate three real-world use cases: electronic payment, web authentication, and data aggregation. We analyze the security of existing protocols and confirm results from prior work that most protocols are not resilient to malware. Furthermore, we provide guidelines for the design of malware-resistant protocols and propose such protocols. In addition, we formalize security notions for malware-resistance and use a formal proof of security to verify the security guarantees of our protocols. In this work we show that designing malware-resistant protocols for real-world systems is possible. We present a new security notion for electronic payment and web authentication, called one-out-of-two security, that does not require a single device to be trusted and ensures that a protocol stays secure as long as one of two devices is not compromised. Furthermore, we propose L-Pay, a cryptographic protocol for paying at the point of sale (POS) or withdrawing money at an automated teller machine (ATM) satisfying one-out-of-two security, FIDO2 With Two Displays (FIDO2D) a cryptographic protocol to secure transactions in the Web with one-out-of-two security and Secure Aggregation Grouped by Multiple Attributes (SAGMA), a cryptographic protocol for secure data aggregation in encrypted databases. In this work, we take important steps towards the use of malware-resistant protocols in real-world systems. Our guidelines and protocols can serve as templates to design new cryptographic protocols and improve security in further use cases

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

Passenger Flows in Underground Railway Stations and Platforms, MTI Report 12-43

Urban rail systems are designed to carry large volumes of people into and out of major activity centers. As a result, the stations at these major activity centers are often crowded with boarding and alighting passengers, resulting in passenger inconvenience, delays, and at times danger. This study examines the planning and analysis of station passenger queuing and flows to offer rail transit station designers and transit system operators guidance on how to best accommodate and manage their rail passengers. The objectives of the study are to: 1) Understand the particular infrastructural, operational, behavioral, and spatial factors that affect and may constrain passenger queuing and flows in different types of rail transit stations; 2) Identify, compare, and evaluate practices for efficient, expedient, and safe passenger flows in different types of station environments and during typical (rush hour) and atypical (evacuations, station maintenance/ refurbishment) situations; and 3) Compile short-, medium-, and long-term recommendations for optimizing passenger flows in different station environments

Engineering Division

The objectives of the Engineering Division are to provide an association for those having an interest in library and information science as they apply to engineering and the physical sciences and to promote the use of materials and knowledge for the benefit of libraries and other educational organizations