Design and Analysis of a True Random Number Generator Based on GSR Signals for Body Sensor Networks

This article belongs to the Section Internet of ThingsToday, medical equipment or general-purpose devices such as smart-watches or smart-textiles can acquire a person's vital signs. Regardless of the type of device and its purpose, they are all equipped with one or more sensors and often have wireless connectivity. Due to the transmission of sensitive data through the insecure radio channel and the need to ensure exclusive access to authorised entities, security mechanisms and cryptographic primitives must be incorporated onboard these devices. Random number generators are one such necessary cryptographic primitive. Motivated by this, we propose a True Random Number Generator (TRNG) that makes use of the GSR signal measured by a sensor on the body. After an exhaustive analysis of both the entropy source and the randomness of the output, we can conclude that the output generated by the proposed TRNG behaves as that produced by a random variable. Besides, and in comparison with the previous proposals, the performance offered is much higher than that of the earlier works.This work was supported by the Spanish Ministry of Economy and Competitiveness under the contract ESP-2015-68245-C4-1-P, by the MINECO grant TIN2016-79095-C2-2-R (SMOG-DEV), and by the Comunidad de Madrid (Spain) under the project CYNAMON (P2018/TCS-4566), co-financed by European Structural Funds (ESF and FEDER). This research was also supported by the Interdisciplinary Research Funds (HTC, United Arab Emirates) under the grant No. 103104

A survey on physiological-signal-based security for medical devices

Implantable Medical Devices (IMDs) are used to monitor and control patients with chronic diseases. A growing number of IMDs are equipped with a wireless interface that allows non-invasive monitoring and reprogramming through an external device, also known as device programmer. However, this wireless interface also brings important security and privacy risks that may lead to remote attacks. In this domain, the use of cryptography is challenging due to the inherent tensions between security vs accessibility and security vs energy cost. A well-studied problem yet unsolved is how to establish (and manage) cryptographic keys between the device programmer and the IMD. Recent work has investigated how Physiological Signals (PS) extracted from the patient can be used for key agreement or authentication between the devices. This paper surveys some of the proposed countermeasures in the field of medical device security, with a special focus on those that use patient\u27s physiological signals for key establishment or authentication between the devices. We point out that most of the existing solutions, including those relying on PS, take assumptions that do not necessarily hold in practical scenarios. Furthermore, we show that the H2H protocol and the Biosec protocol have serious security weaknesses and design flaws which make them vulnerable to attacks. Based on our analysis, we define some of the challenges that need be addressed before adopting these solutions. Furthermore, we investigate how to use physiological-signal-based protocols in cryptography, possibly in combination with other solutions, such as pre-installed factory keys, to achieve higher security protection

Towards end-to-end security in internet of things based healthcare

Healthcare IoT systems are distinguished in that they are designed to serve human beings, which primarily raises the requirements of security, privacy, and reliability. Such systems have to provide real-time notifications and responses concerning the status of patients. Physicians, patients, and other caregivers demand a reliable system in which the results are accurate and timely, and the service is reliable and secure. To guarantee these requirements, the smart components in the system require a secure and efficient end-to-end communication method between the end-points (e.g., patients, caregivers, and medical sensors) of a healthcare IoT system. The main challenge faced by the existing security solutions is a lack of secure end-to-end communication. This thesis addresses this challenge by presenting a novel end-to-end security solution enabling end-points to securely and efficiently communicate with each other. The proposed solution meets the security requirements of a wide range of healthcare IoT systems while minimizing the overall hardware overhead of end-to-end communication. End-to-end communication is enabled by the holistic integration of the following contributions. The first contribution is the implementation of two architectures for remote monitoring of bio-signals. The first architecture is based on a low power IEEE 802.15.4 protocol known as ZigBee. It consists of a set of sensor nodes to read data from various medical sensors, process the data, and send them wirelessly over ZigBee to a server node. The second architecture implements on an IP-based wireless sensor network, using IEEE 802.11 Wireless Local Area Network (WLAN). The system consists of a IEEE 802.11 based sensor module to access bio-signals from patients and send them over to a remote server. In both architectures, the server node collects the health data from several client nodes and updates a remote database. The remote webserver accesses the database and updates the webpage in real-time, which can be accessed remotely. The second contribution is a novel secure mutual authentication scheme for Radio Frequency Identification (RFID) implant systems. The proposed scheme relies on the elliptic curve cryptography and the D-Quark lightweight hash design. The scheme consists of three main phases: (1) reader authentication and verification, (2) tag identification, and (3) tag verification. We show that among the existing public-key crypto-systems, elliptic curve is the optimal choice due to its small key size as well as its efficiency in computations. The D-Quark lightweight hash design has been tailored for resource-constrained devices. The third contribution is proposing a low-latency and secure cryptographic keys generation approach based on Electrocardiogram (ECG) features. This is performed by taking advantage of the uniqueness and randomness properties of ECG's main features comprising of PR, RR, PP, QT, and ST intervals. This approach achieves low latency due to its reliance on reference-free ECG's main features that can be acquired in a short time. The approach is called Several ECG Features (SEF)-based cryptographic key generation. The fourth contribution is devising a novel secure and efficient end-to-end security scheme for mobility enabled healthcare IoT. The proposed scheme consists of: (1) a secure and efficient end-user authentication and authorization architecture based on the certificate based Datagram Transport Layer Security (DTLS) handshake protocol, (2) a secure end-to-end communication method based on DTLS session resumption, and (3) support for robust mobility based on interconnected smart gateways in the fog layer. Finally, the fifth and the last contribution is the analysis of the performance of the state-of-the-art end-to-end security solutions in healthcare IoT systems including our end-to-end security solution. In this regard, we first identify and present the essential requirements of robust security solutions for healthcare IoT systems. We then analyze the performance of the state-of-the-art end-to-end security solutions (including our scheme) by developing a prototype healthcare IoT system

Improving Security for the Internet of Things: Applications of Blockchain, Machine Learning and Inter-Pulse Interval

The Internet of Things (IoT) is a concept where physical objects of various sizes can seamlessly connect and communicate with each other without human intervention. The concept covers various applications, including healthcare, utility services, automotive/vehicular transportation, smart agriculture and smart city. The number of interconnected IoT devices has recently grown rapidly as a result of technological advancement in communications and computational systems. Consequently, this trend also highlights the need to address issues associated with IoT, the biggest risk of which is commonly known to be security. This thesis focuses on three selected security challenges from the IoT application areas of connected and autonomous vehicles (CAVs), Internet of Flying Things (IoFT), and human body interface and control systems (HBICS). For each of these challenges, a novel and innovative solution is proposed to address the identified problems. The research contributions of this thesis to the literature can be summarised as follows: • A blockchain-based conditionally anonymised pseudonym management scheme for CAVs, supporting multi-jurisdictional road networks. • A Sybil attack detection scheme for IoFT using machine learning carried out on intrinsically generated physical layer data of radio signals. • A potential approach of using inter-pulse interval (IPI) biometrics for frequency hopping to mitigate jamming attacks on HBICS devices

Cybersecurity in implantable medical devices

Mención Internacional en el título de doctorImplantable Medical Devices (IMDs) are electronic devices implanted within the body to treat a medical condition, monitor the state or improve the functioning of some body part, or just to provide the patient with a capability that he did not possess before [86]. Current examples of IMDs include pacemakers and defibrillators to monitor and treat cardiac conditions; neurostimulators for deep brain stimulation in cases such as epilepsy or Parkinson; drug delivery systems in the form of infusion pumps; and a variety of biosensors to acquire and process different biosignals. Some of the newest IMDs have started to incorporate numerous communication and networking functions—usually known as “telemetry”—, as well as increasingly more sophisticated computing capabilities. This has provided implants with more intelligence and patients with more autonomy, as medical personnel can access data and reconfigure the implant remotely (i.e., without the patient being physically present in medical facilities). Apart from a significant cost reduction, telemetry and computing capabilities also allow healthcare providers to constantly monitor the patient’s condition and to develop new diagnostic techniques based on an Intra Body Network (IBN) of medical devices [25, 26, 201]. Evolving from a mere electromechanical IMD to one with more advanced computing and communication capabilities has many benefits but also entails numerous security and privacy risks for the patient. The majority of such risks are relatively well known in classical computing scenarios, though in many respects their repercussions are far more critical in the case of implants. Attacks against an IMD can put at risk the safety of the patient who carries it, with fatal consequences in certain cases. Causing an intentional malfunction of an implant can lead to death and, as recognized by the U.S. Food and Drug Administration (FDA), such deliberate attacks could be far more difficult to detect than accidental ones [61]. Furthermore, these devices store and transmit very sensitive medical information that requires protection, as dictated by European (e.g., Directive 95/46/ECC) and U.S. (e.g., CFR 164.312) Directives [94, 204]. The wireless communication capabilities present in many modern IMDs are a major source of security risks, particularly while the patient is in open (i.e., non-medical) environments. To begin with, the implant becomes no longer “invisible”, as its presence could be remotely detected [48]. Furthermore, it facilitates the access to transmitted data by eavesdroppers who simply listen to the (insecure) channel [83]. This could result in a major privacy breach, as IMDs store sensitive information such as vital signals, diagnosed conditions, therapies, and a variety of personal data (e.g., birth date, name, and other medically relevant identifiers). A vulnerable communication channel also makes it easier to attack the implant in ways similar to those used against more common computing devices [118, 129, 156], i.e., by forging, altering, or replying previously captured messages [82]. This could potentially allow an adversary to monitor and modify the implant without necessarily being close to the victim [164]. In this regard, the concerns of former U.S. vice-president Dick Cheney constitute an excellent example: he had his Implantable Cardioverter Defibrillator (ICD) replaced by another without WiFi capability [219]. While there are still no known real-world incidents, several attacks on IMDs have been successfully demonstrated in the lab [83, 133, 143]. These attacks have shown how an adversary can disable or reprogram therapies on an ICD with wireless connectivity, and even inducing a shock state to the patient [65]. Other attacks deplete the battery and render the device inoperative [91], which often implies that the patient must undergo a surgical procedure to have the IMD replaced. Moreover, in the case of cardiac implants, they have a switch that can be turned off merely by applying a magnetic field [149]. The existence of this mechanism is motivated by the need to shield ICDs to electromagnetic fields, for instance when the patient undergoes cardiac surgery using electrocautery devices [47]. However, this could be easily exploited by an attacker, since activating such a primitive mechanism does not require any kind of authentication. In order to prevent attacks, it is imperative that the new generation of IMDs will be equipped with strong mechanisms guaranteeing basic security properties such as confidentiality, integrity, and availability. For example, mutual authentication between the IMD and medical personnel is essential, as both parties must be confident that the other end is who claims to be. In the case of the IMD, only commands coming from authenticated parties should be considered, while medical personnel should not trust any message claiming to come from the IMD unless sufficient guarantees are given. Preserving the confidentiality of the information stored in and transmitted by the IMD is another mandatory aspect. The device must implement appropriate security policies that restrict what entities can reconfigure the IMD or get access to the information stored in it, ensuring that only authorized operations are executed. Similarly, security mechanisms have to be implemented to protect the content of messages exchanged through an insecure wireless channel. Integrity protection is equally important to ensure that information has not been modified in transit. For example, if the information sent by the implant to the Programmer is altered, the doctor might make a wrong decision. Conversely, if a command sent to the implant is forged, modified, or simply contains errors, its execution could result in a compromise of the patient’s physical integrity. Technical security mechanisms should be incorporated in the design phase and complemented with appropriate legal and administrative measures. Current legislation is rather permissive in this regard, allowing the use of implants like ICDs that do not incorporate any security mechanisms. Regulatory authorities like the FDA in the U.S or the EMA (European Medicines Agency) in Europe should promote metrics and frameworks for assessing the security of IMDs. These assessments should be mandatory by law, requiring an adequate security level for an implant before approving its use. Moreover, both the security measures supported on each IMD and the security assessment results should be made public. Prudent engineering practices well known in the safety and security domains should be followed in the design of IMDs. If hardware errors are detected, it often entails a replacement of the implant, with the associated risks linked to a surgery. One of the main sources of failure when treating or monitoring a patient is precisely malfunctions of the device itself. These failures are known as “recalls” or “advisories”, and it is estimated that they affect around 2.6% of patients carrying an implant. Furthermore, the software running on the device should strictly support the functionalities required to perform the medical and operational tasks for what it was designed, and no more [66, 134, 213]. In Chapter 1, we present a survey of security and privacy issues in IMDs, discuss the most relevant mechanisms proposed to address these challenges, and analyze their suitability, advantages, and main drawbacks. In Chapter 2, we show how the use of highly compressed electrocardiogram (ECG) signals (only 24 coefficients of Hadamard Transform) is enough to unequivocally identify individuals with a high performance (classification accuracy of 97% and with identification system errors in the order of 10−2). In Chapter 3 we introduce a new Continuous Authentication scheme that, contrarily to previous works in this area, considers ECG signals as continuous data streams. The proposed ECG-based CA system is intended for real-time applications and is able to offer an accuracy up to 96%, with an almost perfect system performance (kappa statistic > 80%). In Chapter 4, we propose a distance bounding protocol to manage access control of IMDs: ACIMD. ACIMD combines two features namely identity verification (authentication) and proximity verification (distance checking). The authentication mechanism we developed conforms to the ISO/IEC 9798-2 standard and is performed using the whole ECG signal of a device holder, which is hardly replicable by a distant attacker. We evaluate the performance of ACIMD using ECG signals of 199 individuals over 24 hours, considering three adversary strategies. Results show that an accuracy of 87.07% in authentication can be achieved. Finally, in Chapter 5 we extract some conclusions and summarize the published works (i.e., scientific journals with high impact factor and prestigious international conferences).Los Dispositivos Médicos Implantables (DMIs) son dispositivos electrónicos implantados dentro del cuerpo para tratar una enfermedad, controlar el estado o mejorar el funcionamiento de alguna parte del cuerpo, o simplemente para proporcionar al paciente una capacidad que no poseía antes [86]. Ejemplos actuales de DMI incluyen marcapasos y desfibriladores para monitorear y tratar afecciones cardíacas; neuroestimuladores para la estimulación cerebral profunda en casos como la epilepsia o el Parkinson; sistemas de administración de fármacos en forma de bombas de infusión; y una variedad de biosensores para adquirir y procesar diferentes bioseñales. Los DMIs más modernos han comenzado a incorporar numerosas funciones de comunicación y redes (generalmente conocidas como telemetría) así como capacidades de computación cada vez más sofisticadas. Esto ha propiciado implantes con mayor inteligencia y pacientes con más autonomía, ya que el personal médico puede acceder a los datos y reconfigurar el implante de forma remota (es decir, sin que el paciente esté físicamente presente en las instalaciones médicas). Aparte de una importante reducción de costos, las capacidades de telemetría y cómputo también permiten a los profesionales de la atención médica monitorear constantemente la condición del paciente y desarrollar nuevas técnicas de diagnóstico basadas en una Intra Body Network (IBN) de dispositivos médicos [25, 26, 201]. Evolucionar desde un DMI electromecánico a uno con capacidades de cómputo y de comunicación más avanzadas tiene muchos beneficios pero también conlleva numerosos riesgos de seguridad y privacidad para el paciente. La mayoría de estos riesgos son relativamente bien conocidos en los escenarios clásicos de comunicaciones entre dispositivos, aunque en muchos aspectos sus repercusiones son mucho más críticas en el caso de los implantes. Los ataques contra un DMI pueden poner en riesgo la seguridad del paciente que lo porta, con consecuencias fatales en ciertos casos. Causar un mal funcionamiento intencionado en un implante puede causar la muerte y, tal como lo reconoce la Food and Drug Administration (FDA) de EE.UU, tales ataques deliberados podrían ser mucho más difíciles de detectar que los ataques accidentales [61]. Además, estos dispositivos almacenan y transmiten información médica muy delicada que requiere se protegida, según lo dictado por las directivas europeas (por ejemplo, la Directiva 95/46/ECC) y estadunidenses (por ejemplo, la Directiva CFR 164.312) [94, 204]. Si bien todavía no se conocen incidentes reales, se han demostrado con éxito varios ataques contra DMIs en el laboratorio [83, 133, 143]. Estos ataques han demostrado cómo un adversario puede desactivar o reprogramar terapias en un marcapasos con conectividad inalámbrica e incluso inducir un estado de shock al paciente [65]. Otros ataques agotan la batería y dejan al dispositivo inoperativo [91], lo que a menudo implica que el paciente deba someterse a un procedimiento quirúrgico para reemplazar la batería del DMI. Además, en el caso de los implantes cardíacos, tienen un interruptor cuya posición de desconexión se consigue simplemente aplicando un campo magnético intenso [149]. La existencia de este mecanismo está motivada por la necesidad de proteger a los DMIs frete a posibles campos electromagnéticos, por ejemplo, cuando el paciente se somete a una cirugía cardíaca usando dispositivos de electrocauterización [47]. Sin embargo, esto podría ser explotado fácilmente por un atacante, ya que la activación de dicho mecanismo primitivo no requiere ningún tipo de autenticación. Garantizar la confidencialidad de la información almacenada y transmitida por el DMI es otro aspecto obligatorio. El dispositivo debe implementar políticas de seguridad apropiadas que restrinjan qué entidades pueden reconfigurar el DMI o acceder a la información almacenada en él, asegurando que sólo se ejecuten las operaciones autorizadas. De la misma manera, mecanismos de seguridad deben ser implementados para proteger el contenido de los mensajes intercambiados a través de un canal inalámbrico no seguro. La protección de la integridad es igualmente importante para garantizar que la información no se haya modificado durante el tránsito. Por ejemplo, si la información enviada por el implante al programador se altera, el médico podría tomar una decisión equivocada. Por el contrario, si un comando enviado al implante se falsifica, modifica o simplemente contiene errores, su ejecución podría comprometer la integridad física del paciente. Los mecanismos de seguridad deberían incorporarse en la fase de diseño y complementarse con medidas legales y administrativas apropiadas. La legislación actual es bastante permisiva a este respecto, lo que permite el uso de implantes como marcapasos que no incorporen ningún mecanismo de seguridad. Las autoridades reguladoras como la FDA en los Estados Unidos o la EMA (Agencia Europea de Medicamentos) en Europa deberían promover métricas y marcos para evaluar la seguridad de los DMIs. Estas evaluaciones deberían ser obligatorias por ley, requiriendo un nivel de seguridad adecuado para un implante antes de aprobar su uso. Además, tanto las medidas de seguridad implementadas en cada DMI como los resultados de la evaluación de su seguridad deberían hacerse públicos. Buenas prácticas de ingeniería en los dominios de la protección y la seguridad deberían seguirse en el diseño de los DMIs. Si se detectan errores de hardware, a menudo esto implica un reemplazo del implante, con los riesgos asociados y vinculados a una cirugía. Una de las principales fuentes de fallo al tratar o monitorear a un paciente es precisamente el mal funcionamiento del dispositivo. Estos fallos se conocen como “retiradas”, y se estima que afectan a aproximadamente el 2,6 % de los pacientes que llevan un implante. Además, el software que se ejecuta en el dispositivo debe soportar estrictamente las funcionalidades requeridas para realizar las tareas médicas y operativas para las que fue diseñado, y no más [66, 134, 213]. En el Capítulo 1, presentamos un estado de la cuestión sobre cuestiones de seguridad y privacidad en DMIs, discutimos los mecanismos más relevantes propuestos para abordar estos desafíos y analizamos su idoneidad, ventajas y principales inconvenientes. En el Capítulo 2, mostramos cómo el uso de señales electrocardiográficas (ECGs) altamente comprimidas (sólo 24 coeficientes de la Transformada Hadamard) es suficiente para identificar inequívocamente individuos con un alto rendimiento (precisión de clasificación del 97% y errores del sistema de identificación del orden de 10−2). En el Capítulo 3 presentamos un nuevo esquema de Autenticación Continua (AC) que, contrariamente a los trabajos previos en esta área, considera las señales ECG como flujos de datos continuos. El sistema propuesto de AC basado en señales cardíacas está diseñado para aplicaciones en tiempo real y puede ofrecer una precisión de hasta el 96%, con un rendimiento del sistema casi perfecto (estadístico kappa > 80 %). En el Capítulo 4, proponemos un protocolo de verificación de la distancia para gestionar el control de acceso al DMI: ACIMD. ACIMD combina dos características, verificación de identidad (autenticación) y verificación de la proximidad (comprobación de la distancia). El mecanismo de autenticación es compatible con el estándar ISO/IEC 9798-2 y se realiza utilizando la señal ECG con todas sus ondas, lo cual es difícilmente replicable por un atacante que se encuentre distante. Hemos evaluado el rendimiento de ACIMD usando señales ECG de 199 individuos durante 24 horas, y hemos considerando tres estrategias posibles para el adversario. Los resultados muestran que se puede lograr una precisión del 87.07% en la au tenticación. Finalmente, en el Capítulo 5 extraemos algunas conclusiones y resumimos los trabajos publicados (es decir, revistas científicas con alto factor de impacto y conferencias internacionales prestigiosas).Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: Arturo Ribagorda Garnacho.- Secretario: Jorge Blasco Alís.- Vocal: Jesús García López de Lacall

Improving Energy Efficiency and Security for Pervasive Computing Systems

Pervasive computing systems are comprised of various personal mobile devices connected by the wireless networks. Pervasive computing systems have gained soaring popularity because of the rapid proliferation of the personal mobile devices. The number of personal mobile devices increased steeply over years and will surpass world population by 2016.;However, the fast development of pervasive computing systems is facing two critical issues, energy efficiency and security assurance. Power consumption of personal mobile devices keeps increasing while the battery capacity has been hardly improved over years. at the same time, a lot of private information is stored on and transmitted from personal mobile devices, which are operating in very risky environment. as such, these devices became favorite targets of malicious attacks. Without proper solutions to address these two challenging problems, concerns will keep rising and slow down the advancement of pervasive computing systems.;We select smartphones as the representative devices in our energy study because they are popular in pervasive computing systems and their energy problem concerns users the most in comparison with other devices. We start with the analysis of the power usage pattern of internal system activities, and then identify energy bugs for improving energy efficiency. We also investigate into the external communication methods employed on smartphones, such as cellular networks and wireless LANs, to reduce energy overhead on transmissions.;As to security, we focus on implantable medical devices (IMDs) that are specialized for medical purposes. Malicious attacks on IMDs may lead to serious damages both in the cyber and physical worlds. Unlike smartphones, simply borrowing existing security solutions does not work on IMDs because of their limited resources and high requirement of accessibility. Thus, we introduce an external device to serve as the security proxy for IMDs and ensure that IMDs remain accessible to save patients\u27 lives in certain emergency situations when security credentials are not available