Privacy-preserving biometric-based remote user authentication with leakage resilience

National Research Foundation (NRF) Singapor

Distributed IoT Attestation via Blockchain (Extended Version)

The growing number and nature of Internet of Things (IoT) devices makes these resource-constrained appliances particularly vulnerable and increasingly impactful in their exploitation. Current estimates for the number of connected things commonly reach the tens of billions. The low-cost and limited computational strength of these devices can preclude security features. Additionally, economic forces and a lack of industry expertise in security often contribute to a rush to market with minimal consideration for security implications. It is essential that users of these emerging technologies, from consumers to IT professionals, be able to establish and retain trust in the multitude of diverse and pervasive compute devices that are ever more responsible for our critical infrastructure and personal information. Remote attestation is a well-known technique for building such trust between devices. In standard implementations, a potentially untrustworthy prover attests, using public key infrastructure, to a verifier about its configuration or properties of its current state. Attestation is often performed on an ad hoc basis with little concern for historicity. However, controls and sensors manufactured for the Industrial IoT (IIoT) may be expected to operate for decades. Even in the consumer market, so-called smart things can be expected to outlive their manufacturers. This longevity combined with limited software or firmware patching creates an ideal environment for long-lived zero-day vulnerabilities. Knowing both if a device is vulnerable and if so when it became vulnerable is a management nightmare as IoT deployments scale. For network connected machines, with access to sensitive information and real-world physical controls, maintaining some sense of a device\u27s lifecycle would be insightful. In this paper, we propose a novel attestation architecture, DAN: a distributed attestation network, utilizing blockchain to store and share device information. We present the design of this new attestation architecture, and describe a virtualized simulation, as well as a prototype system chosen to emulate an IoT deployment with a network of Raspberry Pi, Infineon TPMs, and a Hyperledger Fabric blockchain. We discuss the implications and potential challenges of such a network for various applications such as identity management, intrusion detection, forensic audits, and regulatory certification

Security and Privacy in RFID Applications

Concerns about privacy and security may limit the deployment of RFID technology and its benefits, therefore it is important they are identified and adequately addressed. System developers and other market actors are aware of the threats and are developing a number of counter measures. RFID systems can never be absolutely secure but effort needs to be made to ensure a proper balance between the risks and the costs of counter measures. The approach taken to privacy and security should depend on the application area and the context of a specific application. In this chapter, we selected and discussed four application areas, but there are many others where privacy and security issues are relevant.JRC.J.4-Information Societ

Enriching Vulnerability Reports Through Automated and Augmented Description Summarization

Security incidents and data breaches are increasing rapidly, and only a fraction of them is being reported. Public vulnerability databases, e.g., national vulnerability database (NVD) and common vulnerability and exposure (CVE), have been leading the effort in documenting vulnerabilities and sharing them to aid defenses. Both are known for many issues, including brief vulnerability descriptions. Those descriptions play an important role in communicating the vulnerability information to security analysts in order to develop the appropriate countermeasure. Many resources provide additional information about vulnerabilities, however, they are not utilized to boost public repositories. In this paper, we devise a pipeline to augment vulnerability description through third party reference (hyperlink) scrapping. To normalize the description, we build a natural language summarization pipeline utilizing a pretrained language model that is fine-tuned using labeled instances and evaluate its performance against both human evaluation (golden standard) and computational metrics, showing initial promising results in terms of summary fluency, completeness, correctness, and understanding.Comment: 13 pages; to appear in WISA 202

A distributed mix-context-based method for location privacy in road networks

Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a vehicle using sensitive information transmitted in beacons such as vehicle identity and location. By matching the vehicle identity used in beacon messages at various locations, an adversary learns the location history of a vehicle. This compromises the privacy of the vehicle driver. In existing research work, pseudonyms are used in place of the actual vehicle identity in the beacons. Pseudonyms should be changed regularly to safeguard the location privacy of vehicles. However, applying simple change in pseudonyms does not always provide location privacy. Existing schemes based on mix zones operate efficiently in higher traffic environments but fail to provide privacy in lower vehicle traffic densities. In this paper, we take the problem of location privacy in diverse vehicle traffic densities. We propose a new Crowd-based Mix Context (CMC) privacy scheme that provides location privacy as well as identity protection in various vehicle traffic densities. The pseudonym changing process utilizes context information of road such as speed, direction and the number of neighbors in transmission range for the anonymisation of vehicles, adaptively updating pseudonyms based on the number of a vehicle neighbors in the vicinity. We conduct formal modeling and specification of the proposed scheme using High-Level Petri Nets (HPLN). Simulation results validate the effectiveness of CMC in terms of location anonymisation, the probability of vehicle traceability, computation time (cost) and effect on vehicular applications

Agora: A Privacy-Aware Data Marketplace

We propose Agora, the first blockchain-based data marketplace that enables multiple privacy-concerned parties to get compensated for contributing and exchanging data, without relying on a trusted third party during the exchange. Agora achieves data privacy, output verifiability, and atomicity of payments by leveraging cryptographic techniques, and is designed as a decentralized application via smart contracts. Particularly, data generators provide encrypted data to data brokers who use a functional secret key to learn nothing but the output of a specific, agreed upon, function over the raw data. Data consumers can purchase decrypted outputs from the brokers, accompanied by corresponding proofs of correctness. We implement a working prototype of Agora on Ethereum and experimentally evaluate its performance and deployment costs. As a core building block of Agora, we propose a new functional encryption scheme with additional public parameters that operate as a trust anchor for verifying decrypted results

Computational Resource Abuse in Web Applications

Internet browsers include Application Programming Interfaces (APIs) to support Web applications that require complex functionality, e.g., to let end users watch videos, make phone calls, and play video games. Meanwhile, many Web applications employ the browser APIs to rely on the user's hardware to execute intensive computation, access the Graphics Processing Unit (GPU), use persistent storage, and establish network connections. However, providing access to the system's computational resources, i.e., processing, storage, and networking, through the browser creates an opportunity for attackers to abuse resources. Principally, the problem occurs when an attacker compromises a Web site and includes malicious code to abuse its visitor's computational resources. For example, an attacker can abuse the user's system networking capabilities to perform a Denial of Service (DoS) attack against third parties. What is more, computational resource abuse has not received widespread attention from the Web security community because most of the current specifications are focused on content and session properties such as isolation, confidentiality, and integrity. Our primary goal is to study computational resource abuse and to advance the state of the art by providing a general attacker model, multiple case studies, a thorough analysis of available security mechanisms, and a new detection mechanism. To this end, we implemented and evaluated three scenarios where attackers use multiple browser APIs to abuse networking, local storage, and computation. Further, depending on the scenario, an attacker can use browsers to perform Denial of Service against third-party Web sites, create a network of browsers to store and distribute arbitrary data, or use browsers to establish anonymous connections similarly to The Onion Router (Tor). Our analysis also includes a real-life resource abuse case found in the wild, i.e., CryptoJacking, where thousands of Web sites forced their visitors to perform crypto-currency mining without their consent. In the general case, attacks presented in this thesis share the attacker model and two key characteristics: 1) the browser's end user remains oblivious to the attack, and 2) an attacker has to invest little resources in comparison to the resources he obtains. In addition to the attack's analysis, we present how existing, and upcoming, security enforcement mechanisms from Web security can hinder an attacker and their drawbacks. Moreover, we propose a novel detection approach based on browser API usage patterns. Finally, we evaluate the accuracy of our detection model, after training it with the real-life crypto-mining scenario, through a large scale analysis of the most popular Web sites

Privacy in trajectory micro-data publishing : a survey

We survey the literature on the privacy of trajectory micro-data, i.e., spatiotemporal information about the mobility of individuals, whose collection is becoming increasingly simple and frequent thanks to emerging information and communication technologies. The focus of our review is on privacy-preserving data publishing (PPDP), i.e., the publication of databases of trajectory micro-data that preserve the privacy of the monitored individuals. We classify and present the literature of attacks against trajectory micro-data, as well as solutions proposed to date for protecting databases from such attacks. This paper serves as an introductory reading on a critical subject in an era of growing awareness about privacy risks connected to digital services, and provides insights into open problems and future directions for research.Comment: Accepted for publication at Transactions for Data Privac