Cryptographic Protocols, Sensor Network Key Management, and RFID Authentication

This thesis includes my research on efficient cryptographic protocols, sensor network key management, and radio frequency identification (RFID) authentication protocols. Key exchange, identification, and public key encryption are among the fundamental protocols studied in cryptography. There are two important requirements for these protocols: efficiency and security. Efficiency is evaluated using the computational overhead to execute a protocol. In modern cryptography, one way to ensure the security of a protocol is by means of provable security. Provable security consists of a security model that specifies the capabilities and the goals of an adversary against the protocol, one or more cryptographic assumptions, and a reduction showing that breaking the protocol within the security model leads to breaking the assumptions. Often, efficiency and provable security are not easy to achieve simultaneously. The design of efficient protocols in a strict security model with a tight reduction is challenging. Security requirements raised by emerging applications bring up new research challenges in cryptography. One such application is pervasive communication and computation systems, including sensor networks and radio frequency identification (RFID) systems. Specifically, sensor network key management and RFID authentication protocols have drawn much attention in recent years. In the cryptographic protocol part, we study identification protocols, key exchange protocols, and ElGamal encryption and its variant. A formal security model for challenge-response identification protocols is proposed, and a simple identification protocol is proposed and proved secure in this model. Two authenticated key exchange (AKE) protocols are proposed and proved secure in the extended Canetti-Krawczyk (eCK) model. The proposed AKE protocols achieve tight security reduction and efficient computation. We also study the security of ElGamal encryption and its variant, Damgard’s ElGamal encryption (DEG). Key management is the cornerstone of the security of sensor networks. A commonly recommended key establishment mechanism is based on key predistribution schemes (KPS). Several KPSs have been proposed in the literature. A KPS installs pre-assigned keys to sensor nodes so that two nodes can communicate securely if they share a key. Multi-path key establishment (MPKE) is one component of KPS which enables two nodes without a shared key to establish a key via multiple node-disjoint paths in the network. In this thesis, methods to compute the k-connectivity property of several representative key predistribution schemes are developed. A security model for MPKE and efficient and secure MPKE schemes are proposed. Scalable, privacy-preserving, and efficient authentication protocols are essential for the success of RFID systems. Two such protocols are proposed in this thesis. One protocol uses finite field polynomial operations to solve the scalability challenge. Its security is based on the hardness of the polynomial reconstruction problem. The other protocol improves a randomized Rabin encryption based RFID authentication protocol. It reduces the hardware cost of an RFID tag by using a residue number system in the computation, and it provides provable security by using secure padding schemes

Physically Uncloneable Functions in the Stand-Alone and Universally Composable Framework

In this thesis, we investigate the possibility of basing cryptographic primitives on Physically Uncloneable Functions (PUF). A PUF is a piece of hardware that can be seen as a source of randomness. When a PUF is evaluated on a physical stimulus, it answers with a noisy output. PUFs are unpredictable such that even if a chosen stimulus is given, it should be infeasible to predict the corresponding output without physically evaluating the PUF. Furthermore, PUFs are uncloneable, which means that even if all components of the system are known, it is computational infeasible to model their behavior. In the course of this dissertation, we discuss PUFs in the context of their implementation, their mathematical description, as well as their usage as a cryptographic primitive and in cryptographic protocols. We first give an overview of the most prominent PUF constructions in order to derive subsequently an appropriate mathematical PUF model. It turns out that this is a non- trivial task, because it is not certain which common security properties are generally necessary and achievable due to the numerous PUF implementations. Next, we consider PUFs in security applications. Due to the properties of PUFs, these hardware tokens are good to build authentication protocols that rely on challenge/response pairs. If the number of potential PUF-based challenge/response pairs is large enough, an adversary cannot measure all PUF responses. Therefore, the at- tacker will most likely not be able to answer the challenge of the issuing party even if he had physical access to the PUF for a short time. However, we show that some of the previously suggested protocols are not fully secure in the attacker model where the adversary has physical control of the PUF and the corresponding reader during a short time. Finally, we analyze PUFs in the universally composable (UC) framework for the first time. Although hardware tokens have been considered before in the UC framework, designing PUF-based protocols is fundamentally different from other hardware token approaches. One reason is that the manufacturer of the PUF creates a physical object that outputs pseudorandom values, but where no specific code is running. In fact, the functional behavior of the PUF is unpredictable even for the PUF creator. Thus, only the party in possession of the PUF has full access to the secrets. After formalizing PUFs in the UC framework, we derive efficient UC-secure protocols for basic tasks like oblivious transfer, commitments, and key exchange

On the security of mobile sensors

PhD ThesisThe age of sensor technology is upon us. Sensor-rich mobile devices are ubiquitous. Smart-phones, tablets, and wearables are increasingly equipped with sensors such as GPS, accelerometer, Near Field Communication (NFC), and ambient sensors. Data provided by such sensors, combined with the fast-growing computational capabilities on mobile platforms, offer richer and more personalised apps. However, these sensors introduce new security challenges to the users, and make sensor management more complicated. In this PhD thesis, we contribute to the field of mobile sensor security by investigating a wide spectrum of open problems in this field covering attacks and defences, standardisation and industrial approaches, and human dimensions. We study the problems in detail and propose solutions. First, we propose “Tap-Tap and Pay” (TTP), a sensor-based protocol to prevent the Mafia attack in NFC payment. The Mafia attack is a special type of Man-In-The-Middle attack which charges the user for something more expensive than what she intends to pay by relaying transactions to a remote payment terminal. In TTP, a user initiates the payment by physically tapping her mobile phone against the reader. We observe that this tapping causes transient vibrations at both devices which are measurable by the embedded accelerometers. Our observations indicate that these sensor measurements are closely correlated within the same tapping, and different if obtained from different tapping events. By comparing the similarity between the two measurements, the bank can distinguish the Mafia fraud apart from a legitimate NFC transaction. The experimental results and the user feedback suggest the practical feasibility of TTP. As compared with previous sensor-based solutions, ours is the only one that works even when the attacker and the user are in nearby locations or share similar ambient environments. Second, we demonstrate an in-app attack based on a real world problem in contactless payment known as the card collision or card clash. A card collision happens when more than one card (or NFC-enabled device) are presented to the payment terminal’s field, and the terminal does not know which card to choose. By performing experiments, we observe that the implementation of contactless terminals in practice matches neither EMV nor ISO standards (the two primary standards for smart card payment) on card collision. Based on this inconsistency, we propose “NFC Payment Spy”, a malicious app that tracks the user’s contactless payment transactions. This app, running on a smart phone, simulates a card which requests the payment information (amount, time, etc.) from the terminal. When the phone and the card are both presented to a contactless terminal (given that many people use mobile case wallets to travel light and keep wallet essentials close to hand), our app can effectively win the race condition over the card. This attack is the first privacy attack on contactless payments based on the problem of card collision. By showing the feasibility of this attack, we raise awareness of privacy and security issues in contactless payment protocols and implementation, specifically in the presence of new technologies for payment such as mobile platforms. Third, we show that, apart from attacking mobile devices by having access to the sensors through native apps, we can also perform sensor-based attacks via mobile browsers. We examine multiple browsers on Android and iOS platforms and study their policies in granting permissions to JavaScript code with respect to access to motion and orientation sensor data. Based on our observations, we identify multiple vulnerabilities, and propose “TouchSignatures” and “PINLogger.js”, two novel attacks in which malicious JavaScript code listens to such sensor data measurements. We demonstrate that, despite the much lower sampling rate (comparing to a native app), a remote attacker is able to learn sensitive user information such as physical activities, phone call timing, touch actions (tap, scroll, hold, zoom), and PINs based on these sensor data. This is the first report of such a JavaScript-based attack. We disclosed the above vulnerability to the community and major mobile browser vendors classified the problem as high-risk and fixed it accordingly. Finally, we investigate human dimensions in the problem of sensor management. Although different types of attacks via sensors have been known for many years, the problem of data leakage caused by sensors has remained unsolved. While working with W3C and browser vendors to fix the identified problem, we came to appreciate the complexity of this problem in practice and the challenge of balancing security, usability, and functionality. We believe a major reason for this is that users are not fully aware of these sensors and the associated risks to their privacy and security. Therefore, we study user understanding of mobile sensors, specifically their risk perceptions. This is the only research to date that studies risk perceptions for a comprehensive list of mobile sensors (25 in total). We interview multiple participants from a range of backgrounds by providing them with multiple self-declared questionnaires. The results indicate that people in general do not have a good understanding of the complexities of these sensors; hence making security judgements about these sensors is not easy for them. We discuss how this observation, along with other factors, renders many academic and industry solutions ineffective. This makes the security and privacy issues of mobile sensors and other sensorenabled technologies an important topic to be investigated further

Internet of Things (IoT) Applications With Diverse Direct Communication Methods

Title from PDF of title page viewed August 28, 2017Dissertation advisor: Baek-Young ChoiVitaIncludes bibliographical references (pages 124-138)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2016Internet of Things (IoT) is a network of physical objects or things that are embedded with electronics, software, sensors, and network connectivity - which enable the object to collect and exchange data. Rapid proliferation of IoT is driving the intelligence in things used daily in homes, workplaces and industry. The IoT devices typically communicate via radio frequency (RF), such as WiFi and Bluetooth. In this dissertation we deeply analyze the various characteristics of different wireless communication methods in terms of range, energy-efficiency, and radiation pattern. We find that a well-established communication method might not be the most efficient, and other alternate communication methods with the desired properties for a particular application could exist. We exploit radically alternative, innovative, and complimentary wireless communication methods, including radio frequency, infrared (IR), and visible lights, through the IoT applications we have designed and built with those. We have developed various IoT applications which provide security and authentication, enable vehicular communications with smartphones or other smart devices, provide energy-efficient and accurate positioning to smart devices, and enable energy-efficient communications in Industrial Internet of Things (IIoT).Introduction -- Optical wireless authentication for SMART devices using an onboard ambient light sensor -- Smartphome based CAR2X-communication with wifi beacon stuffing for vulnerable road user safety -- Energy-efficient cooperative opportunistic positioning heterogeneous Smart devices -- Reducing and balancing energy consumption in Indistrial Internet of Things (IIoT) -- Optical wireless unlocking for Smart door locks using Smartphones -- Summary and future direction

Private set intersection: A systematic literature review

Secure Multi-party Computation (SMPC) is a family of protocols which allow some parties to compute a function on their private inputs, obtaining the output at the end and nothing more. In this work, we focus on a particular SMPC problem named Private Set Intersection (PSI). The challenge in PSI is how two or more parties can compute the intersection of their private input sets, while the elements that are not in the intersection remain private. This problem has attracted the attention of many researchers because of its wide variety of applications, contributing to the proliferation of many different approaches. Despite that, current PSI protocols still require heavy cryptographic assumptions that may be unrealistic in some scenarios. In this paper, we perform a Systematic Literature Review of PSI solutions, with the objective of analyzing the main scenarios where PSI has been studied and giving the reader a general taxonomy of the problem together with a general understanding of the most common tools used to solve it. We also analyze the performance using different metrics, trying to determine if PSI is mature enough to be used in realistic scenarios, identifying the pros and cons of each protocol and the remaining open problems.This work has been partially supported by the projects: BIGPrivDATA (UMA20-FEDERJA-082) from the FEDER Andalucía 2014– 2020 Program and SecTwin 5.0 funded by the Ministry of Science and Innovation, Spain, and the European Union (Next Generation EU) (TED2021-129830B-I00). The first author has been funded by the Spanish Ministry of Education under the National F.P.U. Program (FPU19/01118). Funding for open access charge: Universidad de Málaga/CBU

Critical Perspectives on Provable Security: Fifteen Years of Another Look Papers

We give an overview of our critiques of “proofs” of security and a guide to our papers on the subject that have appeared over the past decade and a half. We also provide numerous additional examples and a few updates and errata

Proximity detection protocols for IoT devices

In recent years, we have witnessed the growth of the Internet of Things paradigm, with its increased pervasiveness in our everyday lives. The possible applications are diverse: from a smartwatch able to measure heartbeat and communicate it to the cloud, to the device that triggers an event when we approach an exhibit in a museum. Present in many of these applications is the Proximity Detection task: for instance the heartbeat could be measured only when the wearer is near to a well defined location for medical purposes or the touristic attraction must be triggered only if someone is very close to it. Indeed, the ability of an IoT device to sense the presence of other devices nearby and calculate the distance to them can be considered the cornerstone of various applications, motivating research on this fundamental topic. The energy constraints of the IoT devices are often in contrast with the needs of continuous operations to sense the environment and to achieve high accurate distance measurements from the neighbors, thus making the design of Proximity Detection protocols a challenging task