195739861
Energy-Aware RFID Authentication in Edge Computing
Internet of Things (IoT) devices are basic units in edge computing. Denial of service (DoS) attack is a great threat to low-cost IoT devices, even worse in privacy-preserving authentication protocols for radio frequency identification (RFID) tags. During DoS attacks, the attacker consumes the legal states in a target tag by continuous scanning and further observes its behavior in authentication to break privacy. Due to lack of adequate energy and computing power, it is hard for passive backscattering RFID tags to defend against DoS attacks. In this work, we cast a new insight on the DoS attacks to RFID tags and leverage the malicious scanning behavior as a new energy source. In this way, a passive tag gains more and more energy and can afford more and more complex cryptography computation under a DoS attack. Finally, the victim tag with adequate energy achieves to complete the complicated public key cryptographic computations and defend against the DoS attack. We further propose a protocol, namely the RUND protocol. We define the tracking privacy model and introduce in the notion of tracking interval to define the tracking privacy other than indistinguishable privacy. To guarantee the security and tracking privacy properties of our protocol, we propose 3 rules as designing guidelines. The analysis shows that our approach can achieve $O$ (1) efficiency while providing DoS-defending privacy-preserving authentication. Furthermore, with proper parameters our approach can save about 40% boosting time at least, compared to the directly charging for public key cryptographic computation method.
3986590
OTrack: Order tracking for luggage in mobile RFID systems
In many logistics applications of RFID technology, goods attached with tags are placed on moving conveyor belts for processing. It is important to figure out the order of goods on the belts so that further actions like sorting can be accurately taken on proper goods. Due to arbitrary goods placement or the irregularity of wireless signal propagation, neither of the order of tag identification nor the received signal strength provides sufficient evidence on their relative positions on the belts. In this study, we observe, from experiments, a critical region of reading rate when a tag gets close enough to a reader. This phenomenon, as well as other signal attributes, yields the stable indication of tag order. We establish a probabilistic model for recognizing the transient critical region and propose the OTrack protocol to continuously monitor the order of tags. To validate the protocol, we evaluate the accuracy and effectiveness through a one-month experiment conducted through a working conveyor at Beijing Capital International Airport.
8494194
PLACE: Physical Layer Cardinality Estimation for Large-Scale RFID Systems
Estimating the number of RFID tags is a fundamental operation in RFID systems and has recently attracted wide attentions. Despite the subtleties in their designs, previous methods estimate the tag cardinality from the slot measurements, which distinguish idle and busy slots and based on that derive the cardinality following some probability models. In order to fundamentally improve the counting efficiency, in this paper we introduce PLACE, a physical layer based cardinality estimator. We show that it is possible to extract more information and infer integer states from the same slots in RFID communications. We propose a joint estimator that optimally combines multiple sub-estimators, each of which independently counts the number of tags with different inferred PHY states. Extensive experiments based on the GNURadio/USRP platform and the large-scale simulations demonstrate that PLACE achieves approximately 3 ~ 4× performance improvement over state-of-the-art cardinality estimation approaches.
18244725
Tagoram: real-time tracking of mobile RFID tags to high precision using COTS devices
In many applications, we have to identify an object and then locate the object to within high precision (centimeter- or millimeter-level). Legacy systems that can provide such accuracy are either expensive or suffering from performance degradation resulting from various impacts, e.g., occlusion for computer vision based approaches. In this work, we present an RFID-based system, Tagoram, for object localization and tracking using COTS RFID tags and readers. Tracking mobile RFID tags in real time has been a daunting task, especially challenging for achieving high precision. Our system achieves these three goals by leveraging the phase value of the backscattered signal, provided by the COTS RFID readers, to estimate the location of the object. In Tagoram, we exploit the tag's mobility to build a virtual antenna array by using readings from a few physical antennas over a time window. To illustrate the basic idea of our system, we firstly focus on a simple scenario where the tag is moving along a fixed track known to the system. We propose Differential Augmented Hologram (DAH) which will facilitate the instant tracking of the mobile RFID tag to a high precision. We then devise a comprehensive solution to accurately recover the tag's moving trajectories and its locations, relaxing the assumption of knowing tag's track function in advance. We have implemented the Tagoram system using COTS RFID tags and readers. The system has been tested extensively in the lab environment and used for more than a year in real airline applications. For lab environment, we can track the mobile tags in real time with a millimeter accuracy to a median of 5mm and 7.29mm using linear and circular track respectively. In our year- long large scale baggage sortation systems deployed in two airports, our results from real deployments show that Tagoram can achieve a centimeter-level accuracy to a median of 6.35cm in these real deployments.
62211697
CBID: A Customer Behavior Identification System Using Passive Tags
Different from online shopping, in-store shopping has few ways to collect the customer behaviors before purchase. In this paper, we present the design and implementation of an on-site Customer Behavior Identification system based on passive RFID tags, named CBID. By collecting and analyzing wireless signal features, CBID can detect and track tag movements and further infer corresponding customer behaviors. We model three main objectives of behavior identification by concrete problems and solve them using novel protocols and algorithms. The design innovations of this work include a Doppler effect based protocol to detect tag movements, an accurate Doppler frequency estimation algorithm, a multi-RSS based tag localization protocol, and a tag clustering algorithm using cosine similarity. We have implemented a prototype of CBID in which all components are built by off-the-shelf devices. We have deployed CBID in real environments and conducted extensive experiments to demonstrate the accuracy and efficiency of CBID in customer behavior identification.
3987134
Perceiving the Slightest Tag Motion beyond Localization
Existing methods in RFID systems often employ presence or absence fashion to detect the tags' motions, so they cannot meet motion detection requirement in many applications. Our recent observations suggest that the signal strength backscattered from the tag is hypersensitive to its position, inspiring us to perceive the tag motion through its radio signal strength changes. Motion perception is not trivial and challenged by weak stability of strength in that any other interference or noise may incur significant changes as well, resulting in high false positives. To tackle this issue, we propose to model the strength via the Mixture of Gaussian Model (MoG). The problem is thus converted to foreground segment in computer vision with the help of Strength Image, where the technique of MoG based background subtraction is employed. We then implement a prototype using commercial off-the-shelf products. The evaluation results show that the slightest tag motion (~10 cm) can be precisely perceived, and the accuracy is up to 92.34 percent while the false positive is suppressed under 0.5 percent.
2395236
Design of a Passively-Powered, Programmable Sensing Platform for UHF RFID Systems
This paper presents a wireless, battery-free, platform for sensing and computation that is powered and read by a standards compliant ultra-high frequency (UHF) radio frequency identification (RFID) reader. The WISP (wireless identification and sensing platform) includes a fully-programmable 16 bit microcontroller with analog-to-digital converter. The microcontroller firmware implements portions of the electronic product code (EPC) class 1 generation 1 protocol. When queried, the platform communicates arbitrary sensor data by emulating an EPC tag whose ID encodes the desired sensor data; the required 16-bit CRC is computed dynamically by the microcontroller. The RFID reader reports the received tag ID to application software which can interpret the information contained in the tag ID. The programmability of the WISP along with its implementation as a PCB allows for flexible integration of arbitrary low-power sensors. Furthermore, sensors are also exclusively powered from the RFID reader resulting in a completely battery free device. Sensors integrated into the WISP platform so far include light, temperature, and rectified voltage, and are shown experimentally to have an operating range of up to 4.5m. To the authors' knowledge, WISP is the first fully programmable computing platform that can operate using power transmitted from a long-range (UHF) RFID reader and communicate arbitrary, multi-bit data in a single response packet.
13242205
Hash Functions and RFID Tags: Mind the Gap
The security challenges posed by RFID-tag deployments are well-known. In response there is a rich literature on new cryptographic protocols and an on-tag hash function is often assumed by protocol designers. Yet cheap tags pose severe implementation challenges and it is far from clear that a suitable hash function even exists. In this paper we consider the options available, including constructions based around compact block ciphers. While we describe the most compact hash functions available today, our work serves to highlight the difficulties in designing lightweight hash functions and (echoing [17]) we urge caution when routinely appealing to a hash function in an RFID-tag protocol.
11883503
Privacy-Friendly Authentication in RFID Systems: On Sublinear Protocols Based on Symmetric-Key Cryptography
The recent advent of ubiquitous technologies has raised an important concern for citizens: the need to protect their privacy. So far, this wish was not heard of industrials, but national and international regulation authorities, as the European Commission recently published some guidelines to enforce customers' privacy in RFID systems: "Privacy by designâ is the way to be followed as stated in EC Recommendation of 12.5.2009. Research on privacy is an active domain but there is still a wide gap between theory and everyday life's applications. Filling this gap will require academia to design protocols and algorithms that fit the real-life constraints. In this paper, we provide a comprehensive analysis of privacy-friendly authentication protocols devoted to RFID that: 1) are based on well-established symmetric-key cryptographic building blocks; 2) require a reader complexity lower than O(N) where N is the number of provers in the system. These two properties are sine qua non conditions for deploying privacy-friendly authentication protocols in large-scale applications, for example, access control in mass transportation. We describe existing protocols fulfilling these requirements and point out their drawbacks and weaknesses. We especially introduce attacks on CHT, CTI,YA-TRAP*, and the variant of OSK/AO with mutual authentication. We also raise that some protocols, such as O-RAP, O-FRAP, and OSK/BF, are not resistant to timing attacks. Finally, we select some candidates that are, according to our criteria, the most appropriate ones for practical uses.
6800444
Reducing Time Complexity in RFID Systems
Radio frequency identification systems based on low-cost computing devices is the new plaything that every company would like to adopt. Its goal can be either to improve the productivity or to strengthen the security. Specific identification protocols based on symmetric challenge-response have been developed in order to assure the privacy of the device bearers. Although these protocols fit the devices' constraints, they always suffer from a large time complexity. Existing protocols require O(n) cryptographic operations to identify one device among n. 
 
Molnar and Wagner suggested a method to reduce this complexity to O(log n). We show that their technique could degrade the privacy if the attacker has the possibility to tamper with at least one device. Because low-cost devices are not tamper-resistant, such an attack could be feasible. We give a detailed analysis of their protocol and evaluate the threat. Next, we extend an approach based on time-memory trade-offs whose goal is to improve Ohkubo, Suzuki, and Kinoshita's protocol. We show that in practice this approach reaches the same performances as Molnar and Wagner's method, without degrading privacy.
18870506
A Secure High-Speed Identification Scheme for RFID Using Bloom Filters
As pervasive computing environments become popular, RFID tags are introduced into our daily life. However, there exists a privacy problem that an adversary can trace users' behavior by linking the tag's ID. Although a Hash-chain scheme can solve this privacy problem, the scheme needs a long identification time or a large amount of memory. In this paper, we propose an efficient identification scheme using Bloom filters, which are space-efficient probabilistic data structures. Our Bloom pre-calculation scheme provides a high-speed identification with a small amount of memory by storing pre-calculated outputs of the tags in Bloom filters.
14577100
Cryptographic Approach to “Privacy-Friendly” Tags
Radio frequency identification (RFID) is expected to become an important and ubiquitous infrastructure technology. As RFID tags are affixed to everyday items, they may be used to support various useful services. However, widespread deployment of RFID tags may create new threats to user privacy, due to the powerful tracking capability of the tags. There are several important technical points when constructing an RFID scheme. Particularly important is ensuring forward security, i.e., data transmitted today will still be secure even if secret tag information is revealed by tampering in the future. Low cost implementation is another key RFID requirement. This paper discusses and clarifies the requirements and restrictions of RFID systems. This paper also examines the features and issues pertinent to several existing RFID schemes. Finally, this paper suggests the use of our previously proposed scheme, which protects user privacy using a low-cost hash chain mechanism.
3075720
MAP: Towards Authentication for Multiple Tags
The prevalence of Radio Frequency Identification (RFID) technology requires Privacy-Preserving Authentication (PPA) protocols to prevent privacy leakage during authentication. Existing PPA protocols employ the per-tag authentication, in which the reader has to sequentially authenticate the tags within the detecting region. Such a processing pattern becomes a bottleneck in current RFID enabled systems, especially for those batch-type processing applications. In this paper, we propose an efficient authentication protocol, which leverages the collaboration among multiple tags for accelerating the authentication speed. We also find that the collision, usually being considered as a negative factor, is helpful media to enable collaborative authentication among tags. Our protocol, termed as Multiple-tags privacy-preserving Authentication Protocol (MAP), authenticates a batch of tags concurrently with strong privacy and high efficiency. The analytical and simulation results show that the efficiency of MAP is better than O( log N ) and asymptotically approaches O(1).
3526499
Attack gives me power: DoS-defending constant-time privacy-preserving authentication of low-cost devices such as backscattering RFID tags
Denial of service (DoS) attack is a great threaten to privacy-preserving authentication protocols for low-cost devices such as RFID. During such attack, the legal internal states can be consumed by the DoS attack. Then the attacker can observe the behavior of the attacked tag in authentication to break privacy. Due to the inadequate energy and computing power, the low cost devices can hardly defend against the DoS attacks. In this paper, we propose a new insight of the DoS attack on tags and leverage the attacking behavior as a new source of power harvesting. In this way, a low-cost device such as a tag grows more and more powerful under DoS attack. Finally, it can defend against the DoS attack. We further propose a protocol that enables DoS-defending constant-time privacy-preserving authentication.
10840680
Time Measurement Threatens Privacy-Friendly RFID Authentication Protocols
Privacy is one of the most important security concerns in radio frequency identification. The publication of hundred RFID-based authentication protocols during the last decade raised the need of designing a dedicated privacy model. An important step has been done with the model of Vaudenay that combines early models into a unified and powerful one. In particular, this model addresses the case where an adversary is able to know whether or not the protocol execution succeeded. This modelizes the fact that the adversary may get information from a side channel about the termination of the protocol, e.g., she notices that the access is granted to the RFID-tag holder. We go one step forward in this paper and stress that the adversary may also have access to a side channel that leaks the computational time of the reader. This modelizes an adversary who measures how long it takes to grant the access. Although this channel could be seen as an implementation flaw, we consider that it is always risky to require the implementation to solve what the design should deal with. This new channel enables to demonstrate that many key-reference protocols are not as privacy-friendly as they claim to be, e.g., WSRE, OSK, C2, O-FRAP, O-FRAKE,... We then introduce the TIMEFUL oracle in the model of Vaudenay, which allows to analyze the resistance of the protocols to time-based attacks as soon as the design phase. Finally, we suggest some methods that make RFID-based authentication protocols immune to such attacks.
20721117
QoS Prediction for Web Service Recommendation with Network Location-Aware Neighbor Selection
Web service recommendation is one of the key problems in service computing, especially in the case of a large number of service candidates. The QoS (quality of service) values are usually leveraged to recommend services that best satisfy a user’s demand. There are many existing methods using collaborative filtering (CF) to predict QoS missing values, but very limited works can leverage the network location information in the user side and service side. In real-world service invocation scenario, the network location of a user or a service makes great impact on QoS. In this paper, we propose a novel collaborative recommendation framework containing three novel prediction models, which are based on two techniques, i.e. matrix factorization (MF) and network location-aware neighbor selection. We first propose two individual models that have the capability of using the user and service information, respectively. Then we propose a unified model that combines the results of the two individual models. We conduct sufficient experiments on a real-world dataset. The experimental results demonstrate that our models achieve higher prediction accuracy than baseline models, and are not sensitive to the parameters.
7959942
Rethinking RFID: awareness and control for interaction with RFID systems
People now routinely carry radio frequency identification (RFID) tags - in passports, driver's licenses, credit cards, and other identifying cards - from which nearby RFID readers can access privacy-sensitive information. The problem is that people are often unaware of security and privacy risks associated with RFID, likely because the technology remains largely invisible and uncontrollable for the individual. To mitigate this problem, we introduce a collection of novel yet simple and inexpensive tag designs. Our tags provide reader awareness, where people get visual, audible, or tactile feedback as tags come into the range of RFID readers. Our tags also provide information control, where people can allow or disallow access to the information stored on the tag by how they touch, orient, move, press or illuminate the tag.
7081617
ECC Is Ready for RFID - A Proof in Silicon
This paper presents the silicon chip ECCon, an Elliptic Curve Cryptography processor for application in Radio-Frequency Identification. The circuit is fabricated on a 180 nm CMOS technology. ECCon features small silicon size (15K GE) and has low power consumption (8.57 μW). It computes 163-bit ECC point-multiplications in 296k cycles and has an ISO 18000-3 RFID interface. ECCon's very low and nearly constant power consumption makes it the first ECC chip that can be powered passively. This major breakthrough is possible because of a radical change in hardware architecture. The ECCon datapath operates on 16-bit words, which is similar to ECC instruction-set extensions. A number of innovations on the algorithmic and on the architectural level substantially increased the efficiency of 163-bit ECC. ECCon is the first demonstration that the proof of origin via electronic signatures can be realized on RFID tags in 180 nm CMOS and below.
14195263
Idetic: A high-level synthesis approach for enabling long computations on transiently-powered ASICs
We develop Idetic, a set of mechanisms to enable long computations on ultra-low power Application Specific Integrated Circuits (ASICs) with energy harvesting sources. We address the power transiency and unpredictability problem by optimally inserting checkpoints. Idetic targets highlevel synthesis designs and automatically locates and embeds the checkpoints at the register-transfer level. We define an objective function that aims to find the checkpoints which incur minimum overhead and minimize recomputation energy cost. We develop and exploit a dynamic programming technique to solve the optimization problem. For real time operation, Idetic adaptively adjusts the checkpointing rate based on the available energy level in the system. Idetic is deployed and evaluated on cryptographic benchmark circuits. The test platform harvests RF power through an RFID-reader and stores the energy in a 3.3μF capacitor. For storage of checkpointed data, we evaluate and compare the effectiveness of various non-volatile memories including NAND Flash, PCM, and STTM. Extensive evaluations show that Idetic reliably enables execution of long computations under different source power patterns with low overhead. Our benchmark evaluations demonstrate that the area and energy overheads corresponding to the checkpoints are less than 5% and 11% respectively.
8900624
Dewdrop: An Energy-Aware Runtime for Computational RFID
Computational RFID (CRFID) tags embed sensing and computation into the physical world. The operation of the tags is limited by the RF energy that can be harvested from a nearby power source. We present a CRFID run-time, Dewdrop, that makes effective use of the harvested energy. Dewdrop treats iterative tasks as a scheduling problem to balance task demands with available energy, both of which vary over time. It adapts the start time of the next task iteration to consistently run well over a range of distances between tags and a power source, for different numbers of tags in the vicinity, and for light and heavy tasks. We have implemented Dewdrop on top of the WISP CRFID tag. Our experiments show that, compared to normal WISP operation, Dewdrop doubles the operating range for heavy tasks and significantly increases the task rate for tags receiving the least energy, all without decreasing the rate in other situations. Using offline testing, we find that Dewdrop runs tasks at better than 90% of the best rate possible.
207185520
Mementos: system support for long-running computation on RFID-scale devices
Transiently powered computing devices such as RFID tags, kinetic energy harvesters, and smart cards typically rely on programs that complete a task under tight time constraints before energy starvation leads to complete loss of volatile memory. Mementos is a software system that transforms general-purpose programs into interruptible computations that are protected from frequent power losses by automatic, energy-aware state checkpointing. Mementos comprises a collection of optimization passes for the LLVM compiler infrastructure and a linkable library that exercises hardware support for energy measurement while managing state checkpoints stored in nonvolatile memory. We evaluate Mementos against diverse test cases in a trace-driven simulator of transiently powered RFID-scale devices. Although Mementos's energy checks increase run time when energy is plentiful, they allow Mementos to safely suspend execution when energy dwindles, effectively spreading computation across zero or more power failures. This paper's contributions are: a study of the runtime environment for programs on RFID-scale devices; an energy-aware state checkpointing system for these devices that is implemented for the MSP430 family of microcontrollers; and a trace-driven simulator of transiently powered RFID-scale devices.
31072823
Clank: Architectural support for intermittent computation
The processors that drive embedded systems are getting smaller; meanwhile, the batteries used to provide power to those systems have stagnated. If we are to realize the dream of ubiquitous computing promised by the Internet of Things, processors must shed large, heavy, expensive, and high maintenance batteries and, instead, harvest energy from their environment. One challenge with this transition is that harvested energy is insufficient for continuous operation. Unfortunately, existing programs fail miserably when executed intermittently. This paper presents Clank: lightweight architectural support for correct and efficient execution of long-running applications on harvested energy-without programmer intervention or extreme hardware modifications. Clank is a set of hardware buffers and memory-access monitors that dynamically maintain idempotency. Essentially, Clank dynamically decomposes program execution into a stream of restartable sub-executions connected via lightweight checkpoints. To validate Clank's ability to correctly stretch program execution across frequent, random power cycles, and to explore the associated hardware and software overheads, we implement Clank in Verilog, formally verify it, and then add it to an ARM Cortex M0+ processor which we use to run a set of 23 embedded systems benchmarks. Experiments show run-time overheads as low as 2.5%, with run-time overheads of 6% for a version of Clank that adds 1.7% hardware. Clank minimizes checkpoints so much that re-execution time becomes the dominate contributor to run-time overhead.
3946858
Timely Execution on Intermittently Powered Batteryless Sensors
Tiny intermittently powered computers can monitor objects in hard to reach places maintenance free for decades by leaving batteries behind and surviving off energy harvested from the environment--- avoiding the cost of replacing and disposing of billions or trillions of dead batteries. However, creating programs for these sensors is difficult. Energy harvesting is inconsistent, energy storage is scarce, and batteryless sensors can lose power at any point in time--- causing volatile memory, execution progress, and time to reset. In response to these disruptions, developers must write unwieldy programs attempting to protect against failures, instead of focusing on sensing goals, defining tasks, and generating useful data in a timely manner. To address these shortcomings, we have designed Mayfly, a language and runtime for timely execution of sensing tasks on tiny, intermittently-powered, energy harvesting sensing devices. Mayfly is a coordination language and runtime built on top of Embedded-C that combines intermittent execution fragments to form coherent sensing schedules---maintaining forward progress, data consistency, data freshness, and data utility across multiple power failures. Mayfly makes the passing of time explicit, binding data to the time it was gathered, and keeping track of data and time through power failures. We evaluated Mayfly against state-of-the art systems, conducted a user study, and implemented multiple real world applications across application domains in inventory tracking, and wearables.
8176633
Maximalist Cryptography and Computation on the WISP UHF RFID Tag
With continuous improvements in the ef?ciency of microelectronics, it is now possible to power a general-purpose microcontroller wirelessly at a reasonable range. Our implementation of RC5-32/18/16 on the WISP UHF RFID tag shows that conventional cryptography is no longer beyond the reach of a general-purpose UHF tag. In this paper, (1) we provide preliminary experimental data on how much computation is available on a TI MSP430F2132 microcontroller-based RFID tag containing approximately 8 KBytes of ?ash and 512 bytes of RAM, and (2) we show that symmetric cryptography is feasible on an RF-powered, general-purpose RFID tag — providing the ?rst implementation of conventional cryptography on an RF-powered UHF RFID tag as far as we are aware
3975833
Identification-free batch authentication for RFID tags
Cardinality estimation and tag authentication are two major issues in large-scale Radio Frequency Identification (RFID) systems. While there exist both per-tag and probabilistic approaches for the cardinality estimation, the RFID-oriented authentication protocols are mainly per-tag based: the reader authenticates one tag at each time. For a batch of tags, current RFID systems have to identify them and then authenticate each tag sequentially, incurring large volume of authentication data and huge communication cost. We study the RFID batch authentication issue and propose the first probabilistic approach, termed as Single Echo based Batch Authentication (SEBA), to meet the requirement of prompt and reliable batch authentications in large scale RFID applications, e.g., the anti-counterfeiting solution. Without the need of identifying tags, SEBA provides a provable probabilistic guarantee that the percentage of potential counterfeit products is under the user-defined threshold. The experimental result demonstrates the effectiveness of SEBA in fast batch authentications and significant improvement compared to existing approaches.
67336635
Proactive Batch Authentication: Fishing Counterfeit RFID Tags in Muddy Waters
Radio frequency identification technology has been recently employed as an effective solution for anti-counterfeiting. By attaching a tag on each product, a reader can provide a fast and automatic authentication. However, most of existing approaches adopt a per-tag approach to validate each product, which will incur a long scanning time and communication traffic when there are many products to be concurrently authenticated. To address these issues, batch authentication, e.g., SEBA, is proposed in recent literature. Batch authentication is an identification-free and probabilistic approach and aims to authenticate the validity of a batch of tags. Unfortunately, the existing batch authentication still suffers a serious scalability problem where the system cost linearly depends on the total number of genuine tags, e.g.,  ${\mathcal {O}(N)}$ . Its efficiency will significantly decrease and even be worse than the per-tag approach when there is a large number of genuine tags in the system. This limitation hinders the batch authentication to be widely used in practice because there are up to millions of total genuine tags in usual. In this paper, we propose FISH, which is also probabilistic batch authentication-based, to overcome the scalability problem by reducing the dependence to  ${\mathcal {O}(\log (N))}$ . Moreover, FISH owns the following two salient advantages: 1) FISH can identify the genuine products when there is no counterfeit product in the batch although it is identification-free in essence and 2) FISH can defend against silence attack by utilizing Pearson Chi-square test. Last, we also conduct the theoretical analysis and extensive simulation with the real logistics trace
4805152
Optimal Key-Trees for Tree-Based Private Authentication
Key-tree based private authentication has been proposed by Molnar and Wagner as a neat way to efficiently solve the problem of privacy preserving authentication based on symmetric key cryptography. However, in the key-tree based approach, the level of privacy provided by the system to its members may decrease considerably if some members are compromised. In this paper, we analyze this problem, and show that careful design of the tree can help to minimize this loss of privacy. First, we introduce a benchmark metric for measuring the resistance of the system to a single compromised member. This metric is based on the well-known concept of anonymity sets. Then, we show how the parameters of the key-tree should be chosen in order to maximize the system's resistance to single member compromise under some constraints on the authentication delay. In the general case, when any member can be compromised, we give a lower bound on the level of privacy provided by the system. We also present some simulation results that show that this lower bound is quite sharp. The results of this paper can be directly used by system designers to construct optimal key-trees in practice; indeed, we consider this as the main contribution of our work.
14035953
Reducing RFID reader load with the meet-in-the-middle strategy
When tag privacy is required in radio frequency identification (ID) system, a reader needs to identify, and optionally authenticate, a multitude of tags without revealing their IDs. One approach for identification with lightweight tags is that each tag performs pseudo-random function with his unique embedded key. In this case, a reader (or a back-end server) needs to perform a brute-force search for each tag-reader interaction, whose cost gets larger when the number of tags increases. In this paper, we suggest a simple and efficient identification technique that reduces readers computation to O(√N log N) without increasing communication cost. Our technique is based on the well-known "meet-in-the- middle" strategy used in the past to attack symmetric ciphers.
12694258
Scalable RFID Systems: A Privacy-Preserving Protocol with Constant-Time Identification
In RFID literature, most “privacy-preserving” protocols require the reader to search all tags in the system in order to identify a single tag. In another class of protocols, the search complexity is reduced to be logarithmic in the number of tags, but it comes with two major drawbacks: it requires a large communication overhead over the fragile wireless channel, and the compromise of a tag in the system reveals secret information about other, uncompromised, tags in the same system. In this work, we take a different approach to address time complexity of private identification in large-scale RFID systems. We utilize the special architecture of RFID systems to propose a symmetric-key privacy-preserving authentication protocol for RFID systems with constant-time identification. Instead of increasing communication overhead, the existence of a large storage device in RFID systems, the database, is utilized for improving the time efficiency of tag identification.
44089162
Lightweight and Practical Anonymous Authentication Protocol for RFID Systems Using Physically Unclonable Functions
Radio frequency identification (RFID) has been considered one of the imperative requirements for implementation of Internet-of-Things applications. It helps to solve the identification issues of the things in a cost-effective manner, but RFID systems often suffer from various security and privacy issues. To solve those issues for RFID systems, many schemes have been recently proposed by using the cryptographic primitive, called physically uncloneable functions (PUFs), which can ensure a tamper-evident feature. However, to the best of our knowledge, none of them has succeeded to address the problem of privacy preservation with the resistance of DoS attacks in a practical way. For instance, existing schemes need to rely on exhaustive search operations to identify a tag, and also suffer from several security and privacy related issues. Furthermore, a tag needs to store some security credentials (e.g., secret shared keys), which may cause several issues such as loss of forward and backward secrecy and large storage costs. Therefore, in this paper, we first propose a lightweight privacy-preserving authentication protocol for the RFID system by considering the ideal PUF environment. Subsequently, we introduce an enhanced protocol which can support the noisy PUF environment. It is argued that both of our protocols can overcome the limitations of existing schemes, and further ensure more security properties. By analyzing the performance, we have shown that the proposed solutions are secure, efficient, practical, and effective for the resource-constraint RFID tag.
24219558
SLAP: Succinct and Lightweight Authentication Protocol for low-cost RFID system
Data security is crucial for a RFID system. Since the existing RFID mutual authentication protocols encounter the challenges such as security risks, poor performance, an ultra-lightweight authentication protocol named Succinct and Lightweight Authentication Protocol (SLAP) is proposed. SLAP is only composed of bitwise operations like XOR, left rotation and conversion which is easy to implement on a passive tag. The proposed conversion operation as the main security component guarantees the security of RFID system with the properties such as irreversibility, sensibility, full confusion and low complexity, which better performed or even absent in other previous protocols. Security analysis shows that SLAP guarantees the functionalities of mutual authentication as well as resistance to various attacks such as de-synchronization attack, replay attack and traceability attack, etc. Furthermore, performance evaluation also indicates that the proposed scheme outperforms the existing protocols in terms of less computation requirement and fewer communication messages during authentication process.
6730636
Ambient backscatter: wireless communication out of thin air
We present the design of a communication system that enables two devices to communicate using ambient RF as the only source of power. Our approach leverages existing TV and cellular transmissions to eliminate the need for wires and batteries, thus enabling ubiquitous communication where devices can communicate among themselves at unprecedented scales and in locations that were previously inaccessible. To achieve this, we introduce ambient backscatter, a new communication primitive where devices communicate by backscattering ambient RF signals. Our design avoids the expensive process of generating radio waves; backscatter communication is orders of magnitude more power-efficient than traditional radio communication. Further, since it leverages the ambient RF signals that are already around us, it does not require a dedicated power infrastructure as in traditional backscatter communication. To show the feasibility of our design, we prototype ambient backscatter devices in hardware and achieve information rates of 1 kbps over distances of 2.5 feet and 1.5 feet, while operating outdoors and indoors respectively. We use our hardware prototype to implement proof-of-concepts for two previously infeasible ubiquitous communication applications.
14286487
On the limits of effective hybrid micro-energy harvesting on mobile CRFID sensors
Mobile sensing is difficult without power. Emerging Computational RFIDs (CRFIDs) provide both sensing and general-purpose computation without batteries--instead relying on small capacitors charged by energy harvesting. CRFIDs have small form factors and consume less energy than traditional sensor motes. However, CRFIDs have yet to see widespread use because of limited autonomy and the propensity for frequent power loss as a result of the necessarily small capacitors that serve as a microcontroller's power supply. Our results show that hybrid harvesting CRFIDs, which use an ambient energy micro-harvester, can complete a variety of useful workloads--even in an environment with little ambient energy available.
 Our contributions include (1) benchmarks demonstrating that micro-harvesting from ambient energy sources enables greater range and read rate, as well as autonomous operation by hybrid CRFIDs, (2) a measurement study that stresses the limits of effective ambient energy harvesting for diverse workloads, (3) application studies that demonstrate the benefits of hybrid CRFIDs, and (4) a trace-driven simulator to model and evaluate the expected behavior of a CRFID with different capacitor sizes and operating under varying conditions of mobility and solar energy harvesting. Our results show that ambient harvesting can triple the effective communication range of a CRFID, quadruple the read rate, and achieve 95% uptime in RAM retention mode despite long periods of low light.
14492274
Chain: tasks and channels for reliable intermittent programs
Energy harvesting computers enable general-purpose computing using energy collected from their environment. Energy-autonomy of such devices has great potential, but their intermittent power supply poses a challenge. Intermittent program execution compromises progress and leaves state inconsistent. This work describes Chain: a new model for programming intermittent devices. A Chain program is a set of programmer-defined tasks that compute and exchange data through channels. Chain guarantees forward progress at task granularity. A task is restartable and never sees inconsistent state, because its input and output channels are separated. Our system supports language features for expressing advanced data exchange patterns and for encapsulating reusable functionality. Chain fundamentally differs from state-of-the-art checkpointing approaches and does not incur the associated overhead. We implement Chain as C language extensions and a runtime library. We used Chain to implement four applications: machine learning, encryption, compression, and sensing. In experiments, Chain ensured consistency where prior approaches failed and improved throughput by 2-7x over the leading state-of-the-art system.
49642163
Toward service selection for workflow reconfiguration: An interface-based computing solution
Abstract Due to the open and diverse features of the Internet, applications need an effective method of performing a workflow reconfiguration to achieve both the functional behaviors and non-functional requirements of workflow changes when a service failure occurs. This paper proposes a service selection method for workflow reconfiguration based on interface operation matching. First, formal models of service workflow and interface operations of Web services are defined, and functional behavior comparisons of service selections are performed to determine the operation coverage set that will fulfill all activities that predefine the form of an abstract process. Second, reconfiguration patterns are introduced to describe different solution types for service patterns, including one-to-one, one-to-many, many-to-many, and many-to-one modes. Third, to consider the quality of service (QoS), the quality of service workflow (QoW) is proposed according to control structures and service interface computing, and the unified QoW formula is then provided to effectively rank each reconfiguration plan to provide a top-k solution recommendation. Fourth, related algorithms and a case study are discussed to show the service selection process during the workflow reconfiguration. To support the engineering implementation, a novel service workflow reconfiguration architecture is designed to provide guidance, which ranges from monitoring to recommendations for project implementation. Finally, experiments are conducted to demonstrate the effectiveness and efficiency of the proposed method.
31357685
Probabilistic Model Checking-Based Service Selection Method for Business Process Modeling
Business process modeling is a way to the organizational change management, which provides abstract workflows to describe business logics for customer demands analysis and IT infrastructures improv...
3760656
Proper RFID Privacy: Model and Protocols
We approach RFID privacy both from modelling and protocol point of view. Our privacy model avoids the drawbacks of several proposed RFID privacy models that either suffer from insufficient generality or put forward unrealistic assumptions regarding the adversary's ability to corrupt tags. Furthermore, our model can handle multiple readers and introduces two new privacy notions to capture the recently discovered insider attackers. We analyse multiple existing RFID protocols, demonstrating the easy applicability of our model, and propose a new wide-forward-insider private RFID authentication protocol. This protocol provides sufficient privacy guarantees for most practical applications and is the most efficient of its kind, it only requires two scalar-EC point multiplications.
10432414
On Privacy Models for RFID
We provide a formal model for identification schemes. Under this model, we give strong definitions for security and privacy. Our model captures the notion of a powerful adversary who can monitor all communications, trace tags within a limited period of time, corrupt tags, and get side channel information on the reader output. Adversaries who do not have access to this side channel are called narrow adversaries. Depending on restrictions on corruption, adversaries are called strong, destructive, forward, or weak adversaries. We derive some separation results: strong privacy is impossible. Narrow-strong privacy implies key agreement. We also prove some constructions: narrow-strong and forward privacy based on a public-key cryptosystem, narrow-destructive privacy based on a random oracle, and weak privacy based on a pseudorandom function.
9215197
Automatic verification of correspondences for security protocols
We present a new technique for verifying correspondences in security protocols. In particular, correspondences can be used to formalize authentication. Our technique is fully automatic, it can handle an unbounded number of sessions of the protocol, and it is efficient in practice. It significantly extends a previous technique for the verification of secrecy. The protocol is represented in an extension of the pi calculus with fairly arbitrary cryptographic primitives. This protocol representation includes the specification of the correspondence to be verified, but no other annotation. This representation is then translated into an abstract representation by Horn clauses, which is used to prove the desired correspondence. Our technique has been proved correct and implemented. We have tested it on various protocols from the literature. The experimental results show that these protocols can be verified by our technique in less than 1 s.
14911411
Physical-layer identification of UHF RFID tags
In this work, we study physical-layer identification of passive UHF RFID tags. We collect signals from a population of 70 tags using a purpose-built reader and we analyze time domain and spectral features of the collected signals. We show that, based on timing features of the signals, UHF RFID tags can be classified, independently of the location and distance to the reader (evaluated up to 6 meters), with an accuracy of approx. 71% (within our population). Additionally, we show that is possible to uniquely identify a maximum of approx. 26 UHF RFID tags independently of the population size. We analyze the implications of these results on tag holder privacy. We further show that, in controlled environments, UHF RFID tags can be uniquely identified based on their signal spectral features with an Equal Error Rate of 0% (within our population); we discuss the application of those techniques to cloning detection in RFID-enabled supply chains.
41139207
Collaborative QoS Prediction for Mobile Service with Data Filtering and SlopeOne Model
The mobile service is a widely used carrier for mobile applications. With the increase of the number of mobile services, for service recommendation and selection, the nonfunctional properties (also known as quality of service, QoS) become increasingly important. However, in many cases, the number of mobile services invoked by a user is quite limited, which leads to the large number of missing QoS values. In recent years, many prediction algorithms, such as algorithms extended from collaborative filtering (CF), are proposed to predict QoS values. However, the ideas of most existing algorithms are borrowed from the recommender system community, not specific for mobile service. In this paper, we first propose a data filtering-extended SlopeOne model (filtering-based CF), which is based on the characteristics of a mobile service and considers the relation with location. Also, using the data filtering technique in FB-CF and matrix factorization (MF), this paper proposes another model FB-MF (filtering-based MF). We also build an ensemble model, which combines the prediction results of FB-CF model and FB-MF model. We conduct sufficient experiments, and the experimental results demonstrate that our models outperform all compared methods and achieve good results in high data sparsity scenario.
132907468
QoS Prediction for Service Recommendation with Deep Feature Learning in Edge Computing Environment
Along with the popularity of intelligent services and mobile services, service recommendation has become a key task, especially the task based on quality-of-service (QoS) in edge computing environment. Most existing service recommendation methods have some serious defects, and cannot be directly adopted in edge computing environment. For example, most of existing methods cannot learn deep features of users or services, but in edge computing environment, there are a variety of devices with different configurations and different functions, and it is necessary to learn deep features behind those complex devices. In order to fully utilize hidden features, this paper proposes a new matrix factorization (MF) model with deep features learning, which integrates a convolutional neural network (CNN). The proposed mode is named Joint CNN-MF (JCM). JCM is capable of using the learned deep latent features of neighbors to infer the features of a user or a service. Meanwhile, to improve the accuracy of neighbors selection, the proposed model contains a novel similarity computation method. CNN learns the neighbors features, forms a feature matrix and infers the features of the target user or target service. We conducted experiments on a real-world service dataset under a batch of cases of data densities, to reflect the complex invocation cases in edge computing environment. The experimental results verify that compared to counterpart methods, our method can consistently achieve higher QoS prediction results.
14104104
Implementation and performance testing of the SQUASH RFID authentication protocol
We implement and test the performance of an RFID hash algorithm recently proposed by Adi Shamir [1] using a C++ simulation. The algorithm, called SQUASH (short for “SQUarehASH”), allows for an RFID tag design that is simple enough to be implemented on low-cost RFID tags. Shamir has proved mathematically that his SQUASH algorithm is at least as secure as the Rabin cryptosystem [2], which has been extensively tested and scrutinized for nearly 30 years. The SQUASH algorithm is designed to minimize processing time and cost without sacrificing security. Shamir's SQUASH algorithm was developed as a lightweight version of a hash function from the Rabin cryptosystem, c = m2 mod n. The SQUASH algorithm is theoretically faster because rather than storing, computing, and transmitting a large ciphertext, the algorithm allows a low cost RFID tag to compute the bits of the ciphertext in real-time, bit by bit, transmitting them as they are calculated. Although the SQUASH algorithm is provably as secure as the Rabin cryptosystem, the performance of the algorithm has not been carefully scrutinized. Shamir writes that the performance of the SQUASH algorithm should scale linearly as the size of a tag's register increases; we attempt to test this specific claim by using a software simulation.
10325079
Analog On-Tag Hashing: Towards Selective Reading as Hash Primitives in Gen2 RFID Systems
Deployment of billions of Commercial Off-The-Shelf (COTS) RFID tags has drawn much of the attention of the research community because of the performance gaps of current systems. In particular, hash-enabled protocol (HEP) is one of the most thoroughly studied topics in the past decade. HEPs are designed for a wide spectrum of notable applications (e.g., missing detection) without need to collect all tags. HEPs assume that each tag contains a hash function, such that a tag can select a random but predicable time slot to reply with a one-bit presence signal that shows its existence. However, the hash function has never been implemented in COTS tags in reality, which makes HEPs a 10-year untouchable mirage. This work designs and implements a group of analog on-tag hash primitives (called Tash) for COTS Gen2-compatible RFID systems, which moves prior HEPs forward from theory to practice. In particular, we design three types of hash primitives, namely, tash function, tash table function and tash operator. All of these hash primitives are implemented through selective reading, which is a fundamental and mandatory functionality specified in Gen2 protocol, without any hardware modification and fabrication. We further apply our hash primitives in two typical HEP applications (i.e., cardinality estimation and missing detection) to show the feasibility and effectiveness of Tash. Results from our prototype, which is composed of one ImpinJ reader and 3,000 Alien tags, demonstrate that the new design lowers 60% of the communication overhead in the air. The tash operator can additionally introduce an overhead drop of 29.7%.
27438370
Collaborative Service Selection via Ensemble Learning in Mixed Mobile Network Environments
Mobile Service selection is an important but challenging problem in service and mobile computing. Quality of service (QoS) predication is a critical step in service selection in 5G network environments. The traditional methods, such as collaborative filtering (CF), suffer from a series of defects, such as failing to handle data sparsity. In mobile network environments, the abnormal QoS data are likely to result in inferior prediction accuracy. Unfortunately, these problems have not attracted enough attention, especially in a mixed mobile network environment with different network configurations, generations, or types. An ensemble learning method for predicting missing QoS in 5G network environments is proposed in this paper. There are two key principles: one is the newly proposed similarity computation method for identifying similar neighbors; the other is the extended ensemble learning model for discovering and filtering fake neighbors from the preliminary neighbors set. Moreover, three prediction models are also proposed, two individual models and one combination model. They are used for utilizing the user similar neighbors and servicing similar neighbors, respectively. Experimental results conducted in two real-world datasets show our approaches can produce superior prediction accuracy.