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Register a new userVeSPA: Vehicular Security and Privacy-preserving Architecture
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Mohammad Khodaei
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Standardization and harmonization efforts have reached a consensus towards using a special-purpose Vehicular Public-Key Infrastructure (VPKI) in upcoming Vehicular Communication (VC) systems. However, there are still several technical challenges with no conclusive answers; one such an important yet open challenge is the acquisition of short-term credentials, pseudonym: how should each vehicle interact with the VPKI, e.g., how frequently and for how long? Should each vehicle itself determine the pseudonym lifetime? Answering these questions is far from trivial. Each choice can affect both the user privacy and the system performance and possibly, as a result, its security. In this paper, we make a novel systematic effort to address this multifaceted question. We craft three generally applicable policies and experimentally evaluate the VPKI system performance, leveraging two large-scale mobility datasets. We consider the most promising, in terms of efficiency, pseudonym acquisition policies; we find that within this class of policies, the most promising policy in terms of privacy protection can be supported with moderate overhead. Moreover, in all cases, this work is the first to provide tangible evidence that the state-of-the-art VPKI can serve sizable areas or domain with modest computing resources.
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WhatsApp messenger is arguably the most popular mobile app available on all smart-phones. Over one billion people worldwide for free messaging, calling, and media sharing use it. In April 2016, WhatsApp switched to a default end-to-end encrypted service. This means that all messages (SMS), phone calls, videos, audios, and any other form of information exchanged cannot be read by any unauthorized entity since WhatsApp. In this paper we analyze the WhatsApp messaging platform and critique its security architecture along with a focus on its privacy preservation mechanisms. We report that the Signal Protocol, which forms the basis of WhatsApp end-to-end encryption, does offer protection against forward secrecy, and MITM to a large extent. Finally, we argue that simply encrypting the end-to-end channel cannot preserve privacy. The metadata can reveal just enough information to show connections between people, their patterns, and personal information. This paper elaborates on the security architecture of WhatsApp and performs an analysis on the various protocols used. This enlightens us on the status quo of the app security and what further measures can be used to fill existing gaps without compromising the usability. We start by describing the following (i) important concepts that need to be understood to properly understand security, (ii) the security architecture, (iii) security evaluation, (iv) followed by a summary of our work. Some of the important concepts that we cover in this paper before evaluating the architecture are - end-to-end encryption (E2EE), signal protocol, and curve25519. The description of the security architecture covers key management, end-to-end encryption in WhatsApp, Authentication Mechanism, Message Exchange, and finally the security evaluation. We then cover importance of metadata and role it plays in conserving privacy with respect to whatsapp.
Recently Homomorphic Encryption (HE) is used to implement Privacy-Preserving Neural Networks (PPNNs) that perform inferences directly on encrypted data without decryption. Prior PPNNs adopt mobile network architectures such as SqueezeNet for smaller computing overhead, but we find naively using mobile network architectures for a PPNN does not necessarily achieve shorter inference latency. Despite having less parameters, a mobile network architecture typically introduces more layers and increases the HE multiplicative depth of a PPNN, thereby prolonging its inference latency. In this paper, we propose a textbf{HE}-friendly privacy-preserving textbf{M}obile neural ntextbf{ET}work architecture, textbf{HEMET}. Experimental results show that, compared to state-of-the-art (SOTA) PPNNs, HEMET reduces the inference latency by $59.3%sim 61.2%$, and improves the inference accuracy by $0.4 % sim 0.5%$.
Significant developments have taken place over the past few years in the area of vehicular communication (VC) systems. Now, it is well understood in the community that security and protection of private user information are a prerequisite for the deployment of the technology. This is so, precisely because the benefits of VC systems, with the mission to enhance transportation safety and efficiency, are at stake. Without the integration of strong and practical security and privacy enhancing mechanisms, VC systems could be disrupted or disabled, even by relatively unsophisticated attackers. We address this problem within the SeVeCom project, having developed a security architecture that provides a comprehensive and practical solution. We present our results in a set of two papers in this issue. In this first one, we analyze threats and types of adversaries, we identify security and privacy requirements, and we present a spectrum of mechanisms to secure VC systems. We provide a solution that can be quickly adopted and deployed. In the second paper, we present our progress towards the implementation of our architecture and results on the performance of the secure VC system, along with a discussion of upcoming research challenges and our related current results.
Resource Public Key Infrastructure (RPKI) is vital to the security of inter-domain routing. However, RPKI enables Regional Internet Registries (RIRs) to unilaterally takedown IP prefixes - indeed, such attacks have been launched by nation-state adversaries. The threat of IP prefix takedowns is one of the factors hindering RPKI adoption. In this work, we propose the first distributed RPKI system, based on threshold signatures, that requires the coordination of a number of RIRs to make changes to RPKI objects; hence, preventing unilateral prefix takedown. We perform extensive evaluations using our implementation demonstrating the practicality of our solution. Furthermore, we show that our system is scalable and remains efficient even when RPKI is widely deployed.
Healthcare blockchains provide an innovative way to store healthcare information, execute healthcare transactions, and build trust for healthcare data sharing and data integration in a decentralized open healthcare network environment. Although the healthcare blockchain technology has attracted broad interests and attention in industry, government and academia, the security and privacy concerns remain the focus of debate when deploying blockchains for information sharing in the healthcare sector from business operation to research collaboration. This paper focuses on the security and privacy requirements for medical data sharing using blockchain, and provides a comprehensive analysis of the security and privacy risks and requirements, accompanied by technical solution techniques and strategies. First, we discuss the security and privacy requirements and attributes required for electronic medical data sharing by deploying the healthcare blockchain. Second, we categorize existing efforts into three reference blockchain usage scenarios for electronic medical data sharing, and discuss the technologies for implementing these security and privacy properties in the three categories of usage scenarios for healthcare blockchain, such as anonymous signatures, attribute-based encryption, zero-knowledge proofs, verification techniques for smart contract security. Finally, we discuss other potential blockchain application scenarios in healthcare sector. We conjecture that this survey will help healthcare professionals, decision makers, and healthcare service developers to gain technical and intuitive insights into the security and privacy of healthcare blockchains in terms of concepts, risks, requirements, development and deployment technologies and systems.
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