Browsing by Author "Paverd, Andrew"

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HardScope: Hardening Embedded Systems Against Data-Oriented Attacks
(2019-06-02) Nyman, Thomas; Dessouky, Ghada; Zeitouni, Shaza; Lehikoinen, Aaro; Paverd, Andrew; Asokan, N.; Sadeghi, Ahmad-Reza
A4 Artikkeli konferenssijulkaisussa
Memory-unsafe programming languages like C and C++ leave many (embedded) systems vulnerable to attacks like control-flow hijacking. However, defenses against control-flow attacks, such as (fine-grained) randomization or control-flow integrity are in-effective against data-oriented attacks and more expressive Data-oriented Programming (DOP) attacks that bypass state-of-the-art defenses. We propose run-time scope enforcement (RSE), a novel approach that efficiently mitigates all currently known DOP attacks by enforcing compile-time memory safety constraints like variable visibility rules at run-time. We present Hardscope, a proof-of-concept implementation of hardware-assisted RSE for RISC-V, and show it has a low performance overhead of 3.2% for embedded benchmarks.
Improving the Security and Efficiency of Blockchain-based Cryptocurrencies
(2017-08-28) Gopinath Nirmala, Rakesh
Perustieteiden korkeakoulu | Master's thesis
In recent years, the desire for financial privacy and anonymity spurred the growth of electronic cash and cryptocurrencies. The introduction of decentralized cryptocurrencies, such as Bitcoin, accelerated their adoption in society. Since digital information is easier to reproduce, digital currencies are vulnerable to be spent more than once – this is called a double-spending attack. In order to prevent double-spending, Bitcoin records transactions in a tamper-resilient shared ledger called the blockchain. However, the time required to generate new blocks in the blockchain causes a delay in the transaction confirmation. This delay, typically around one hour in Bitcoin, is impractical for real world trade and limits the wide-spread use of blockchain-based cryptocurrencies. In this thesis, we propose a solution to prevent double-spending attacks and thus enable fast transaction confirmations using the security guarantees of Trusted Execution Environments (TEEs). We achieve this by enforcing sign-once semantics that prevent the payer from reusing designated signing keys to sign more than one transaction. We also provide a way for the payee to verify whether a specific signing key is subject to sign-once semantics. The payee, however still receives the funds later, once the transaction is verified similarly to existing credit card payments. In this way, our solution reduces transaction confirmation times of blockchain-based cryptocurrencies and is also compatible with existing deployments since it does not require any modifications to the base protocol, peers, or miners. We designed and implemented a proof-of-concept of our solution using Intel SGX technology and integrated it with Copay, a popular Bitcoin wallet from BitPay. This thesis also presents the security evaluation of our system along with other possible extensions and enhancements.
Improving Web Security Using Trusted Hardware
(2017-08-28) Krawiecka, Klaudia
Perustieteiden korkeakoulu | Master's thesis
Web servers that utilize password-based authentication have become large centralized password repositories. Consequently, these servers have also become attractive targets for cyber criminals. When the adversary compromises a web server, he usually obtains access to a database file that contains stored passwords and salts. By using pre-computed hash tables (e.g. rainbow tables), the adversary can perform offline password guessing in a relatively short period of time. Thus, securing password databases on web servers is a significant open challenge. We introduce SafeKeeper, a system that is designed to address the challenge of protecting user passwords and other types of sensitive data on the web. This system consists of a hardware-backed password protection service, which applies a keyed one-way cryptographic function to the password. The secret key is protected by a Trusted Execution Environment. SafeKeeper also includes a browser extension that uses remote attestation allow users to verify if their credentials are protected by a web server. We have implemented a prototype of SafeKeeper using Intel Software Guard Extensions (SGX) and integrated it into the WordPress platform. We have also implemented a browser extension for Google Chrome. Our solution does not require utilizing additional servers and introduces less than 2% performance overhead. Our user study with 64 participants demonstrated that users using the SafeKeeper browser extension can correctly identify 87% of websites in the presence of active phishing.
Java APIs for Trusted Execution Environments
(2016-07-29) Yang, Rui
Perustieteiden korkeakoulu | Master's thesis
Based on GlobalPlatform (GP) Trusted Execution Environment (TEE) specifications, Open-TEE paved the way for ordinary developers to create and deploy Trusted Applications in a GP-compliant TEE. However, when developing an Android Client Application which intends to use the functionality of the GP-Compliant TEE, there still lacks an easy way of using the C binding GP TEE Client API. In this thesis, the problem is addressed in more details and the proposed solution by designing and prototyping a Java API is discussed.
Privacy Preserving Deep Neural Network Prediction using Trusted Hardware
(2018-11-07) Reuter, Max
Perustieteiden korkeakoulu | Master's thesis
In recent years machine learning has gained a lot of attention not only in the scientific community but also in user-facing applications. Today, many applications utilise machine learning to take advantage of its capabilities. With such applications, users actively or passively input data that is used by state-of-the-art algorithms to generate accurate predictions. Due to the extensive work necessary to fine-tune these algorithms for a specific task, they are predominantly executed in the cloud where they can be protected from competitors or malicious users. As a result, users' privacy might be at risk as their data is sent to and processed by remote cloud services. Depending on the application, users might expose highly sensitive data, meaning a malicious provider could harvest extensive amounts of personal data from its users. In order to protect user privacy without compromising the confidentiality guarantees of traditional solutions, we propose using trusted hardware for privacy preserving deep neural network predictions. Our solution consists of a hardware-backed prediction service and a client device that connects to said service. All machine learning computations executed by the prediction service that depend on input data are protected by a trusted hardware component, called a Trusted Execution Environment. This can be verified by users via remote attestation to ensure their data remains protected. In addition, we have built a proof-of-concept implementation of our solution using Intel Software Guard Extensions (SGX). Compared to existing solutions relying on homomorphic encryption, our proof-of-concept implementation vastly increases the set of supported machine learning algorithms. Moreover, our implementation is tightly integrated into the existing pipeline of machine learning tools by supporting the Open Neural Network Exchange (ONNX) Format. Furthermore, we focus on minimising our Trusted Computing Base (TCB), thus our proof-of-concept implementation only consists of 4,500 lines of code. Additionally, we achieve a 7x increase in throughput whilst decreasing the latency 40x compared to prior work. In our tests, SGX reduced throughput by 11% and increased latency by 21% compared to our baseline implementation without SGX.
Protecting Password Databases Using Trusted Hardware
(2016-12) Krawiecka, Klaudia; Paverd, Andrew; Asokan, N.
A4 Artikkeli konferenssijulkaisussa
SafeKeeper: Protecting Web Passwords using Trusted Execution Environments
(2018-04-23) Krawiecka, Klaudia; Kurnikov, Arseny; Paverd, Andrew; Mannan, Mohmmad; Asokan, N.
A4 Artikkeli konferenssijulkaisussa
Passwords are by far the most widely-used mechanism for authenticating users on the web, out-performing all competing solutions in terms of deployability (e.g. cost and compatibility). However, two critical security concerns are phishing and theft of password databases. These are exacerbated by users» tendency to reuse passwords across different services. Current solutions typically address only one of the two concerns, and do not protect passwords against rogue servers. Furthermore, they do not provide any verifiable evidence of their (server-side) adoption to users, and they face deployability challenges in terms of ease-of-use for end users, and/or costs for service providers. We present SafeKeeper, a novel and comprehensive solution to ensure secrecy of passwords in web authentication systems. Unlike previous approaches, SafeKeeper protects users» passwords against very strong adversaries, including external phishers as well as corrupted (rogue) servers. It is relatively inexpensive to deploy as it (i) uses widely available hardware-based trusted execution environments like Intel SGX, (ii) requires only minimal changes for integration into popular web platforms like WordPress, and (iii) imposes negligible performance overhead. We discuss several challenges in designing and implementing such a system, and how we overcome them. Via an 86-participant user study, systematic analysis and experiments, we show the usability, security and deployability of SafeKeeper, which is available as open-source.
Scalable Honeypot Monitoring and Analytics
(2018-08-20) Kovtun, Mariia
Perustieteiden korkeakoulu | Master's thesis
Honeypot systems with a large number of instances pose new challenges in terms of monitoring and analytics. They produce a significant amount of data and require the analyst to monitor every new honeypot instance in the system. Specifically, current approaches require each honeypot instance to be monitored and analysed individually. Therefore, these cannot scale to support scenarios in which a large number of honeypots are used. Furthermore, amalgamating data from a large number of honeypots presents new opportunities to analyse trends. This thesis proposes a scalable monitoring and analytics system that is designed to address this challenge. It consists of three components: monitoring, analysis and visualisation. The system automatically monitors each new honeypot, reduces the amount of collected data and stores it centrally. All gathered data is analysed in order to identify patterns of attacker behaviour. Visualisation conveniently displays the analysed data to an analyst. A user study was performed to evaluate the system. It shows that the solution has met the requirements posed to a scalable monitoring and analytics system. In particular, the monitoring and analytics can be implemented using only open-source software and does not noticeably impact the performance of individual honeypots or the scalability of the overall honeypot system. The thesis also discusses several variations and extensions, including detection of new patterns, and the possibility of providing feedback when used in an educational setting, monitoring attacks by information-security students.
Sustainable security & safety: Challenges and opportunities
(2019-07-01) Paverd, Andrew; Völp, Marcus; Brasser, Ferdinand; Schunter, Matthias; Asokan, N.; Sadeghi, Ahmad Reza; Esteves-Veríssimo, Paulo; Steininger, Andreas; Holz, Thorsten
A4 Artikkeli konferenssijulkaisussa
A significant proportion of today’s information and communication technology (ICT) systems are entrusted with high value assets, and our modern society has become increasingly dependent on these systems operating safely and securely over their anticipated lifetimes. However, we observe a mismatch between the lifetimes expected from ICT-supported systems (such as autonomous cars) and the duration for which these systems are able to remain safe and secure, given the spectrum of threats they face. Whereas most systems today are constructed within the constraints of foreseeable technology advancements, we argue that long term, i.e., sustainable security & safety, requires anticipating the unforeseeable and preparing systems for threats not known today. In this paper, we set out our vision for sustainable security & safety. We summarize the main challenges in realizing this desideratum in real-world systems, and we identify several design principles that could address these challenges and serve as building blocks for achieving this vision.
Using SafeKeeper to Protect Web Passwords
(2018-04-23) Kurnikov, Arseny; Krawiecka, Klaudia; Paverd, Andrew; Mannan, Mohmmad; Asokan, N.
A4 Artikkeli konferenssijulkaisussa
Although passwords are by far the most widely-used user authentication mechanism on the web, their security is threatened by password phishing and password database breaches. SafeKeeper is a system for protecting web passwords against very strong adversaries, including sophisticated phishers and compromised servers. Compared to other approaches, one of the key differentiating aspects of SafeKeeper is that it provides web users with verifiable assurance that their passwords are being protected. In this paper, we demonstrate precisely how SafeKeeper can be used to protect web passwords in real-world systems. We first explain two important deployability aspects: i) how SafeKeeper can be integrated into the popular WordPress platform, and ii) how ordinary web users can use Intel SGX remote attestation to verify that SafeKeeper is running on a particular server. We then describe three demonstrations to illustrate the use of SafeKeeper: i) showing the user experience when visiting a legitimate website; ii) showing the encryption of the password in transit via live packet-capture; and iii) showing how SafeKeeper performs in the presence of phishing.