Revisiting unpredictability-based RFID privacy models

A*Star SERC in Singapor

Trusted and Privacy-preserving Embedded Systems: Advances in Design, Analysis and Application of Lightweight Privacy-preserving Authentication and Physical Security Primitives

Radio Frequency Identification (RFID) enables RFID readers to perform fully automatic wireless identification of objects labeled with RFID tags and is widely deployed to many applications, such as access control, electronic tickets and payment as well as electronic passports. This prevalence of RFID technology introduces various risks, in particular concerning the privacy of its users and holders. Despite the privacy risk, classical threats to authentication and identification systems must be considered to prevent the adversary from impersonating or copying (cloning) a tag. This thesis summarizes the state of the art in secure and privacy-preserving authentication for RFID tags with a particular focus on solutions based on Physically Unclonable Functions (PUFs). It presents advancements in the design, analysis and evaluation of secure and privacy-preserving authentication protocols for RFID systems and PUFs. Formalizing the security and privacy requirements on RFID systems is essential for the design of provably secure and privacy-preserving RFID protocols. However, existing RFID security and privacy models in the literature are often incomparable and in part do not reflect the capabilities of real-world adversaries. We investigate subtle issues such as tag corruption aspects that lead to the impossibility of achieving both mutual authentication and any reasonable notion of privacy in one of the most comprehensive security and privacy models, which is the basis of many subsequent works. Our results led to the refinement of this privacy model and were considered in subsequent works on privacy-preserving RFID systems. A promising approach to enhance the privacy in RFID systems without lifting the computational requirements on the tags are anonymizers. These are special devices that take off the computational workload from the tags. While existing anonymizer-based protocols are subject to impersonation and denial-of-service attacks, existing RFID security and privacy models do not include anonymizers. We present the first security and privacy framework for anonymizer-enabled RFID systems and two privacy-preserving RFID authentication schemes using anonymizers. Both schemes achieve several appealing features that were not simultaneously achieved by any previous proposal. The first protocol is very efficient for all involved entities, achieves privacy under tag corruption. It is secure against impersonation attacks and forgeries even if the adversary can corrupt the anonymizers. The second scheme provides for the first time anonymity and untraceability of tags against readers as well as secure tag authentication against collisions of malicious readers and anonymizers using tags that cannot perform public-key cryptography (i.e., modular exponentiations). The RFID tags commonly used in practice are cost-efficient tokens without expensive hardware protection mechanisms. Physically Unclonable Functions (PUFs) promise to provide an effective security mechanism for RFID tags to protect against basic hardware attacks. However, existing PUF-based RFID authentication schemes are not scalable, allow only for a limited number of authentications and are subject to replay, denial-of-service and emulation attacks. We present two scalable PUF-based authentication schemes that overcome these problems. The first protocol supports tag and reader authentication, is resistant to emulation attacks and highly scalable. The second protocol uses a PUF-based key storage and addresses an open question on the feasibility of destructive privacy, i.e., the privacy of tags that are destroyed during tag corruption. The security of PUFs relies on assumptions on physical properties and is still under investigation. PUF evaluation results in the literature are difficult to compare due to varying test conditions and different analysis methods. We present the first large-scale security analysis of ASIC implementations of the five most popular electronic PUF types, including Arbiter, Ring Oscillator, SRAM, Flip-Flop and Latch PUFs. We present a new PUF evaluation methodology that allows a more precise assessment of the unpredictability properties than previous approaches and we quantify the most important properties of PUFs for their use in cryptographic schemes. PUFs have been proposed for various applications, including anti-counterfeiting and authentication schemes. However, only rudimentary PUF security models exist, limiting the confidence in the security claims of PUF-based security mechanisms. We present a formal security framework for PUF-based primitives, which has been used in subsequent works to capture the properties of image-based PUFs and in the design of anti-counterfeiting mechanisms and physical hash functions

Are RNGs Achilles’ heel of RFID Security and Privacy Protocols ?

Security and privacy concerns have been growing with the increased usage of the RFID technology in our daily lives. To mitigate these issues, numerous privacy-friendly authentication protocols have been published in the last decade. Random number generators (RNGs) are commonly used in RFID tags to provide security and privacy of RFID protocols. RNGs might be weak spot of a protocol scheme and misusing of RNGs causes security and privacy problems. However, having a secure RNG with large entropy might be a trade-off between security and cost for low-cost RFID tags. Furthermore, a RNG used in RFID tag may not work properly in time. Therefore, we claim that vulnerability of using a RNG may deeply influence the security and privacy level of the system. To the best of our knowledge, this concern has not been considered in RFID literature. Motivated by this need, in this study, we first revisit Vaudenay\u27s privacy model which combines the early models and presents a new mature and elegant privacy model with different adversary classes. Then, we enhance the model by introducing a new oracle, which allows analyzing the usage of RNGs in RFID protocols. We also analyze a couple of proposed protocols under our improved model

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Calibrating spatial interaction models from GPS tracking data: an example of retail behaviour

Global Positioning System (GPS) technology has changed the world. We now depend on it for navigating vehicles, for route finding and we use it in our everyday lives to extract information about our locations and to track our movements. The latter use offers a potential alternative to more traditional sources of movement data through the construction of trip trajectories and, ultimately, the construction of origin-destination flow matrices. The advantage of being able to use GPS-derived movement data is that such data are potentially much richer than traditional sources of movement data both temporally and spatially. GPS-derived movement data potentially allow the calibration of spatial interaction models specific to very short time intervals, such as daily or even hourly, and for user-specified origins and destinations. Ultimately, it should be possible to calibrate continuously updated models in near real-time. However, the processing of GPS data into trajectories and then origin-destination flow matrices is not straightforward and is not well understood. This paper describes the process of transferring GPS tracking data into matrices that can be used to calibrate spatial interaction models. An example is given using retail behaviour in two towns in Scotland with an origin-constrained spatial interaction model calibrated for each day of the week and under different weather conditions (normal, rainy, windy). Although the study is small in terms of individuals and spatial context, it serves to demonstrate a future for spatial interaction modelling free from the tyranny of temporally static and spatially predefined data sets

E-BOOT: Preventing Boot-Time Entropy

[EN] Due to the impracticability of generating true randomness by running deterministic algorithms in computers, boot-loaders and operating systems undergo the lack of enough supplies of entropy at boot-time. This problem remains a challenge and affects all computer systems, including virtualization technologies. Unfortunately, this situation leads to undesired side effects, affecting the security of important kernel components and causing large blocking waits in the start-up of userland processes. For example, SSHD is delayed up to 4 minutes. In this paper, we analyze the boot-time entropy starvation problem, performing a comprehensive analysis of the Linux kernel boot process revealing that the problem not only affects userland applications but up to 33 kernel functions at boot time. Those functions are weakly fed by random numbers from a non-initialized CSPRNG. To overcome this problem, we propose E-Boot, a novel technique that provides high-quality random numbers to guest virtual machines. E-Boot is the first technique that completely satisfies the entropy demand of virtualized boot-loaders and operating systems at boot time. We have implemented E-Boot in Linux v5.3 and our experiments show that it effectively solves the boot-time entropy starvation problem. Our proposal successfully feeds bootloaders and boot time Linux kernel hardening techniques with high-quality random numbers, reducing also to zero the number of userspace blocks and delays. The total time overhead introduced by E-Boot is around 2 mu s and has zero memory overhead, since the memory is freed before the kernel boot ends, which makes E-boot a practical solution for cloud systems.Vañó-García, F.; Marco-Gisbert, H. (2020). E-BOOT: Preventing Boot-Time Entropy. IEEE Access. 8:61872-61890. https://doi.org/10.1109/ACCESS.2020.2984414S6187261890

Retail Inventory Control Strategies

Despite using computerized merchandise control systems in retail, the rate of stockouts has remained stagnant. The inability to satisfy customer needs has caused a loss of 4% in potential revenue and resulted in dissatisfied customers. The purpose of this qualitative multiple case study was to explore cost-effective inventory control strategies used by discount retail managers. The conceptual framework that grounded the study was chaos theory, which helped identify why some business leaders rely on forecasting techniques or other cost-effective strategies as an attempt to prevent stockouts. The target population was comprised of discount retail managers located throughout northeast Jacksonville, Florida. Purposeful sampling led to selecting 6 retail managers who successfully demonstrated cost-effective inventory control strategies for mitigating stockouts. Data were collected through face-to-face semistructured interviews, company websites, and company documents. Analysis included using nodes to identify similar words and axial-coding to categorize the nodes into themes. Transcript evaluation, member checking, and methodological triangulation strengthened the credibility of the findings. Five themes emerged: (a) internal stockout reduction strategies, (b) external stockout reduction strategies, (c) replenishment system strategies, (d) inventory optimization strategies, and (e) best practices for inventory control. This study may contribute to positive social change by improving inventory management, which may reduce demand fluctuations in the supply chain and reduce logistics costs in the transportation of freight thereby leading to improved customer satisfaction

Attacking and Defending Emerging Computer Systems Using The Memory Remanence Effect

In computer systems, manufacturing variances and hardware effects are typically abstracted away by the software layer. This dissertation explores how these effects, specifically memory remanence, can be used both as an attack vector and a tool to defend emerging computing systems. To achieve this, we show how time-keeping, anonymity, and authenticity can be affected by memory remanence. In terms of attacks, we explore the deanonymizing effect of approximate computing in the context of approximate memory in Probable Cause. We show how data passing through an approximate memory is watermarked with a device specific tag that points the attacker back to the device. In terms of defenses, we first present TARDIS: an approach to provide a notion of time for transiently powered embedded devices without requiring any hardware modification using remanence effect of SRAM. TARDIS allows these devices to keep a coarse-grained notion of time without the need for a running clock. Second, we propose data retention voltage of memory cells as a new type of physical unclonable function that allows for low-cost authentication and counterfeit resistance in computer systems.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136985/1/rahmati_1.pd