I2PA : An Efficient ABC for IoT

Internet of Things (IoT) is very attractive because of its promises. However, it brings many challenges, mainly issues about privacy preserving and lightweight cryptography. Many schemes have been designed so far but none of them simultaneously takes into account these aspects. In this paper, we propose an efficient ABC scheme for IoT devices. We use ECC without pairing, blind signing and zero knowledge proof. Our scheme supports block signing, selective disclosure and randomization. It provides data minimization and transactions' unlinkability. Our construction is efficient since smaller key size can be used and computing time can be reduced. As a result, it is a suitable solution for IoT devices characterized by three major constraints namely low energy power, small storage capacity and low computing power

Data-centric Misbehavior Detection in VANETs

Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is very important problem with wide range of implications including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. Because of this (\emph{rational behavior}), it is more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can independently decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alert with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. Instead of revoking all the secret credentials of misbehaving nodes, as done in most schemes, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes.Comment: 12 page

Vehicular Internet: Security & Privacy Challenges and Opportunities

The vehicular internet will drive the future of vehicular technology and intelligent transportation systems (ITS). Whether it is road safety, infotainment, or driver-less cars, the vehicular internet will lay the foundation for the future of road travel. Governments and companies are pursuing driver-less vehicles as they are considered to be more reliable than humans and, therefore, safer. The vehicles today are not just a means of transportation but are also equipped with a wide range of sensors that provide valuable data. If vehicles are enabled to share data that they collect with other vehicles or authorities for decision-making and safer driving, they thereby form a vehicular network. However, there is a lot at stake in vehicular networks if they are compromised. With the stakes so high, it is imperative that the vehicular networks are secured and made resilient to any attack or attempt that may have serious consequences. The vehicular internet can also be the target of a cyber attack, which can be devastating. In this paper, the opportunities that the vehicular internet offers are presented and then various security and privacy aspects are discussed and some solutions are presented

Securing the Internet of Things Communication Using Named Data Networking Approaches

The rapid advancement in sensors and their use in devices has led to the drastic increase of Internet-of-Things (IoT) device applications and usage. A fundamental requirement of an IoT-enabled ecosystem is the device’s ability to communicate with other devices, humans etc. IoT devices are usually highly resource constrained and come with varying capabilities and features. Hence, a host-based communication approach defined by the TCP/IP architecture relying on securing the communication channel between the hosts displays drawbacks especially when working in a highly chaotic environment (common with IoT applications). The discrepancies between requirements of the application and the network supporting the communication demands for a fundamental change in securing the communication in IoT applications. This research along with identifying the fundamental security problems in IoT device lifecycle in the context of secure communication also explores the use of a data-centric approach advocated by a modern architecture called Named Data Networking (NDN). The use of NDN modifies the basis of communication and security by defining data-centric security where the data chunks are secured directly and retrieved using specialized requests in a pull-based approach. This work also identifies the advantages of using semantically-rich names as the basis for IoT communication in the current client-driven environment and reinforces it with best-practices from the existing host-based approaches for such networks. We present in this thesis a number of solutions built to automate and securely onboard IoT devices; encryption, decryption and access control solutions based on semantically rich names and attribute-based schemes. We also provide the design details of solutions to sup- port trustworthy and conditionally private communication among highly resource constrained devices through specialized signing techniques and automated certificate generation and distribution with minimal use of the network resources. We also explore the design solutions for rapid trust establishment and vertically securing communication in applications including smart-grid operations and vehicular communication along with automated and lightweight certificate generation and management techniques. Through all these design details and exploration, we identify the applicability of the data-centric security techniques presented by NDN in securing IoT communication and address the shortcoming of the existing approaches in this area

Secure Authentication and Privacy-Preserving Techniques in Vehicular Ad-hoc NETworks (VANETs)

In the last decade, there has been growing interest in Vehicular Ad Hoc NETworks (VANETs). Today car manufacturers have already started to equip vehicles with sophisticated sensors that can provide many assistive features such as front collision avoidance, automatic lane tracking, partial autonomous driving, suggestive lane changing, and so on. Such technological advancements are enabling the adoption of VANETs not only to provide safer and more comfortable driving experience but also provide many other useful services to the driver as well as passengers of a vehicle. However, privacy, authentication and secure message dissemination are some of the main issues that need to be thoroughly addressed and solved for the widespread adoption/deployment of VANETs. Given the importance of these issues, researchers have spent a lot of effort in these areas over the last decade. We present an overview of the following issues that arise in VANETs: privacy, authentication, and secure message dissemination. Then we present a comprehensive review of various solutions proposed in the last 10 years which address these issues. Our survey sheds light on some open issues that need to be addressed in the future

Data Minimisation in Communication Protocols: A Formal Analysis Framework and Application to Identity Management

With the growing amount of personal information exchanged over the Internet, privacy is becoming more and more a concern for users. One of the key principles in protecting privacy is data minimisation. This principle requires that only the minimum amount of information necessary to accomplish a certain goal is collected and processed. "Privacy-enhancing" communication protocols have been proposed to guarantee data minimisation in a wide range of applications. However, currently there is no satisfactory way to assess and compare the privacy they offer in a precise way: existing analyses are either too informal and high-level, or specific for one particular system. In this work, we propose a general formal framework to analyse and compare communication protocols with respect to privacy by data minimisation. Privacy requirements are formalised independent of a particular protocol in terms of the knowledge of (coalitions of) actors in a three-layer model of personal information. These requirements are then verified automatically for particular protocols by computing this knowledge from a description of their communication. We validate our framework in an identity management (IdM) case study. As IdM systems are used more and more to satisfy the increasing need for reliable on-line identification and authentication, privacy is becoming an increasingly critical issue. We use our framework to analyse and compare four identity management systems. Finally, we discuss the completeness and (re)usability of the proposed framework

Towards a Framework for Preserving Privacy in VANET

Vehicular Ad-hoc Network (VANET) is envisioned as an integral part of the Intelligent Transportation Systems as it promises various services and benefits such as road safety, traffic efficiency, navigation and infotainment services. However, the security and privacy risks associated with the wireless communication are often overlooked. Messages exchanged in VANET wireless communication carry inferable Personally Identifiable Information(PII). This introduces several privacy threats that could limit the adoption of VANET. The quantification of these privacy threats is an active research area in VANET security and privacy domains. The Pseudonymisation technique is currently the most preferred solution for critical privacy threats in VANET to provide conditional anonymous authentication. In the existing literature, several Pseudonym Changing Schemes(PCS) have been proposed as effective de-identification approaches to prevent the inference of PII. However, for various reasons, none of the proposed schemes received public acceptance. Moreover, one of the open research challenges is to compare different PCSs under varying circumstances with a set of standardized experimenting parameters and consistent metrics. In this research, we propose a framework to assess the effectiveness of PCSs in VANET with a systematic approach. This comprehensive equitable framework consists of a variety of building blocks which are segmented into correlated sub-domains named Mobility Models, Adversary Models, and Privacy Metrics. Our research introduces a standard methodology to evaluate and compare VANET PCSs using a generic simulation setup to obtain optimal, realistic and most importantly, consistent results. This road map for the simulation setup aims to help the research \& development community to develop, assess and compare the PCS with standard set of parameters for proper analysis and reporting of new PCSs. The assessment of PCS should not only be equitable but also realistic and feasible. Therefore, the sub-domains of the framework need coherent as well as practically applicable characteristics. The Mobility Model is the layout of the traffic on the road which has varying features such as traffic density and traffic scenarios based on the geographical maps. A diverse range of Adversary Models is important for pragmatic evaluation of the PCSs which not only considers the presence of global passive adversary but also observes the effect of intelligent and strategic \u27local attacker\u27 placements. The biggest challenge in privacy measurement is the fact that it is a context-based evaluation. In the literature, the PCSs are evaluated using either user-oriented or adversary-oriented metrics. Under all circumstances, the PCSs should be assessed from both user and adversary perspectives. Using this framework, we determined that a local passive adversary can be strong based on the attacking capabilities. Therefore, we propose two intelligent adversary placements which help in privacy assessment with realistic adversary modelling. When the existing PCSs are assessed with our systematic approach, consistent models and metrics, we identified the privacy vulnerabilities and the limitations of existing PCSs. There was a need for comprehensive PCS which consider the context of the vehicles and the changing traffic patterns in the neighbourhood. Consequently, we developed a Context-Aware \& Traffic Based PCS that focuses on increasing the overall rate of confusion for the adversary and to reduce deterministic information regarding the pseudonym change. It is achieved by increasing the number of dynamic attributes in the proposed PCS for inference of the changing pattern of the pseudonyms. The PCS increases the anonymity of the vehicle by having the synchronized pseudonym changes. The details given under the sub-domains of the framework solidifies our findings to strengthen the privacy assessment of our proposed PCS

A trust-driven privacy architecture for vehicular ad-hoc networks

Vehicular Ad-Hoc NETworks (VANETs) are an emerging technology which aims to improve road safety by preventing and reducing traffic accidents. While VANETs offer a great variety of promising applications, such as, safety-related and infotainment applications, they remain a number of security and privacy related research challenges that must be addressed. A common approach to security issues widely adopted in VANETs is the use of Public Key Infrastructures (PKI) and digital certificates in order to enable authentication, authorization and confidentiality. These approaches usually rely on a large set of regional Certification Authorities (CAs). Despite the advantages of PKI-based approaches, there are two main problems that arise, i) the secure interoperability among the different and usually unknown- issuing CAs, and ii) the sole use of PKI in a VANET environment cannot prevent privacy related attacks, such as, linking a vehicle with an identifier, tracking vehicles ¿big brother scenario" and user profiling. Additionally, since vehicles in VANETs will be able to store great amounts of information including private information, unauthorized access to such information should be carefully considered. This thesis addresses authentication and interoperability issues in vehicular communications, considering an inter-regional scenario where mutual authentication between nodes is needed. To provide interoperability between vehicles and services among different domains, an Inter-domain Authentication System (AS) is proposed. The AS supplies vehicles with a trusted set of authentication credentials by implementing a near real-time certificate status service. The proposed AS also implements a mechanism to quantitatively evaluate the trust level of a CA, in order to decide on-the-y if an interoperability relationship can be created. This research work also contributes with a Privacy Enhancing Model (PEM) to deal with important privacy issues in VANETs. The PEM consists of two PKI-based privacy protocols: i) the Attribute-Based Privacy (ABP) protocol, and ii) the Anonymous Information Retrieval (AIR) protocol. The ABP introduces Attribute-Based Credentials (ABC) to provide conditional anonymity and minimal information disclosure, which overcome with the privacy issues related to linkability (linking a vehicle with an identifier) and vehicle tracking (big brother scenario). The AIR protocol addresses user profiling when querying Service Providers (SPs), by relying in a user collaboration privacy protocol based on query forgery and permutation; and assuming that neither participant nodes nor SPs could be completely trusted. Finally, the Trust Validation Model (TVM) is proposed. The TVM supports decision making by evaluating entities trust based on context information, in order to provide i) access control to driver and vehicle's private information, and ii) public information trust validation