67 research outputs found
Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment
With the evolution of computer systems, the amount of sensitive data to be
stored as well as the number of threats on these data grow up, making the data
confidentiality increasingly important to computer users. Currently, with
devices always connected to the Internet, the use of cloud data storage
services has become practical and common, allowing quick access to such data
wherever the user is. Such practicality brings with it a concern, precisely the
confidentiality of the data which is delivered to third parties for storage. In
the home environment, disk encryption tools have gained special attention from
users, being used on personal computers and also having native options in some
smartphone operating systems. The present work uses the data sealing, feature
provided by the Intel Software Guard Extensions (Intel SGX) technology, for
file encryption. A virtual file system is created in which applications can
store their data, keeping the security guarantees provided by the Intel SGX
technology, before send the data to a storage provider. This way, even if the
storage provider is compromised, the data are safe. To validate the proposal,
the Cryptomator software, which is a free client-side encryption tool for cloud
files, was integrated with an Intel SGX application (enclave) for data sealing.
The results demonstrate that the solution is feasible, in terms of performance
and security, and can be expanded and refined for practical use and integration
with cloud synchronization services
Techniques and methods for obtaining access to data protected by linux-based encryption â A reference guide for practitioners
This research presents an overview of the typical disc and folder-level encryption that a digital forensic investigator may encounter when investigating a Linux operating system. Based on prior first-hand experience and significant follow-up testing and research, this work examines the operation of such encryption from the user's perspective, discusses how the encryption operates âunder the hoodâ; and explores methods and techniques that can be used to access and retrieve data from such encrypted devices, both during at-scene/live forensic investigation and also post-scene. Worked examples are presented, to aid the reader's understanding. This research also presents considerations, approaches and steps that can be used by an investigator, in order to maximise the potential for data acquisition, and most crucially discusses lessons learnt to facilitate getting the best evidence in such cases. A breakdown of the binary structure of the key files associated with fscrypt is also presented, for reference. Current limitations and gaps in knowledge are also discussed
BootBandit: A macOS bootloader attack
Historically, the boot phase on personal computers left systems in a relatively vulnerable state. Because traditional antivirus software runs within the operating system, the boot environment is difficult to protect from malware. Examples of attacks against bootloaders include soâcalled âevil maidâ attacks, in which an intruder physically obtains a boot disk to install malicious software for obtaining the password used to encrypt a disk. The password then must be stored and retrieved again through physical access. In this paper, we discuss an attack that borrows concepts from the evil maid. We assume exploitation can be used to infect a bootloader on a system running macOS remotely to install code to steal the user\u27s password. We explore the ability to create a communication channel between the bootloader and the operating system to remotely steal the password for a disk protected by FileVault 2. On a macOS system, this attack has additional implications due to âpassword forwardingâ technology, in which a user\u27s account password also serves as the FileVault password, enabling an additional attack surface through privilege escalation
faulTPM: Exposing AMD fTPMs' Deepest Secrets
Trusted Platform Modules constitute an integral building block of modern
security features. Moreover, as Windows 11 made a TPM 2.0 mandatory, they are
subject to an ever-increasing academic challenge. While discrete TPMs - as
found in higher-end systems - have been susceptible to attacks on their exposed
communication interface, more common firmware TPMs (fTPMs) are immune to this
attack vector as they do not communicate with the CPU via an exposed bus. In
this paper, we analyze a new class of attacks against fTPMs: Attacking their
Trusted Execution Environment can lead to a full TPM state compromise. We
experimentally verify this attack by compromising the AMD Secure Processor,
which constitutes the TEE for AMD's fTPMs. In contrast to previous dTPM
sniffing attacks, this vulnerability exposes the complete internal TPM state of
the fTPM. It allows us to extract any cryptographic material stored or sealed
by the fTPM regardless of authentication mechanisms such as Platform
Configuration Register validation or passphrases with anti-hammering
protection. First, we demonstrate the impact of our findings by - to the best
of our knowledge - enabling the first attack against Full Disk Encryption
solutions backed by an fTPM. Furthermore, we lay out how any application
relying solely on the security properties of the TPM - like Bitlocker's TPM-
only protector - can be defeated by an attacker with 2-3 hours of physical
access to the target device. Lastly, we analyze the impact of our attack on FDE
solutions protected by a TPM and PIN strategy. While a naive implementation
also leaves the disk completely unprotected, we find that BitLocker's FDE
implementation withholds some protection depending on the complexity of the
used PIN. Our results show that when an fTPM's internal state is compromised, a
TPM and PIN strategy for FDE is less secure than TPM-less protection with a
reasonable passphrase.Comment: *Both authors contributed equally. We publish all code necessary to
mount the attack under https://github.com/PSPReverse/ftpm_attack. The
repository further includes several intermediate results, e.g., flash memory
dumps, to retrace the attack process without possessing the target boards and
required hardware tool
The Trusted Server: A secure computational environment for privacy compliant evaluations on plain personal data
A growing framework of legal and ethical requirements limit scientific and commercial evaluation of personal data. Typically, pseudonymization, encryption, or methods of distributed computing try to protect individual privacy. However, computational infrastructures still depend on human system administrators. This introduces severe security risks and has strong impact on privacy: system administrators have unlimited access to the computers that they manage including encryption keys and pseudonymization-tables. Distributed computing and data obfuscation technologies reduce but do not eliminate the risk of privacy leakage by administrators. They produce higher implementation effort and possible data quality degradation. This paper proposes the Trusted Server as an alternative approach that provides a sealed and inaccessible computational environment in a cryptographically strict sense. During operation or by direct physical access to storage media, data stored and processed inside the Trusted Server can by no means be read, manipulated or leaked, other than by brute-force. Thus, secure and privacy-compliant data processing or evaluation of plain person-related data becomes possible even from multiple sources, which want their data kept mutually secret
Exploiting an HMAC-SHA-1 optimization to speed up PBKDF2
PBKDF2 is a well-known password-based key derivation function. In order to slow attackers down, PBKDF2 introduces CPU-intensive operations based on an iterated pseudorandom function (in our case HMAC-SHA-1). If we are able to speed up a SHA-1 or an HMAC implementation, we are able to speed up PBKDF2-HMAC-SHA-1. This means that a performance improvement might be exploited by regular users and attackers. Interestingly, FIPS 198-1 suggests that it is possible to precompute first message block of a keyed hash function only once, store such a value and use it each time is needed. Therefore the computation of first message block does not contribute to slowing attackers down, thus making the computation of second message block crucial. In this paper we focus on the latter, investigating the possibility to avoid part of the HMAC-SHA-1 operations. We show that some CPU-intensive operations may be replaced with a set of equivalent, but less onerous, instructions. We identify useless XOR operations exploiting and extending Intel optimizations, and applying the Boyar-Peralta heuristic. In addition, we provide an alternative method to compute the SHA-1 message scheduling function and explain why attackers might exploit these findings to speed up a brute force attack against PBKDF2
Leveraging OpenStack and Ceph for a Controlled-Access Data Cloud
While traditional HPC has and continues to satisfy most workflows, a new
generation of researchers has emerged looking for sophisticated, scalable,
on-demand, and self-service control of compute infrastructure in a cloud-like
environment. Many also seek safe harbors to operate on or store sensitive
and/or controlled-access data in a high capacity environment.
To cater to these modern users, the Minnesota Supercomputing Institute
designed and deployed Stratus, a locally-hosted cloud environment powered by
the OpenStack platform, and backed by Ceph storage. The subscription-based
service complements existing HPC systems by satisfying the following unmet
needs of our users: a) on-demand availability of compute resources, b)
long-running jobs (i.e., days), c) container-based computing with
Docker, and d) adequate security controls to comply with controlled-access data
requirements.
This document provides an in-depth look at the design of Stratus with respect
to security and compliance with the NIH's controlled-access data policy.
Emphasis is placed on lessons learned while integrating OpenStack and Ceph
features into a so-called "walled garden", and how those technologies
influenced the security design. Many features of Stratus, including tiered
secure storage with the introduction of a controlled-access data "cache",
fault-tolerant live-migrations, and fully integrated two-factor authentication,
depend on recent OpenStack and Ceph features.Comment: 7 pages, 5 figures, PEARC '18: Practice and Experience in Advanced
Research Computing, July 22--26, 2018, Pittsburgh, PA, US
Taxonomy for Anti-Forensics Techniques & Countermeasures
Computer Forensic Tools are used by forensics investigators to analyze evidence from the seized devices collected at a crime scene or from a person, in such ways that the results or findings can be used in a court of law. These computer forensic tools are very important and useful as they help the law enforcement personnel to solve crimes. Computer criminals are now aware of the forensics tools used; therefore, they use countermeasure techniques to efficiently obstruct the investigation processes. By doing so, they make it difficult or almost impossible for investigators to uncover the evidence. These techniques, used against the computer forensics processes, are called Anti-forensics. This paper describes some of the many anti-forensicsâ method, techniques and tools using a taxonomy. The taxonomy classified anti-forensics into different levels and different categories: WHERE, WHICH, WHAT, and HOW. The WHERE level indicates where anti-forensics can occur during an investigation. The WHICH level indicates which anti-forensics techniques exist. The WHAT level defines the exact method used for each technique. Finally, the HOW level indicates the tools used. Additionally, some countermeasures were proposed
Storing IOT Data Securely in a Private Ethereum Blockchain
Internet of Things (IoT) is a set of technologies that enable network-connected devices to perform an action or share data among several connected devices or to a shared database. The actions can be anything from switching on an Air Conditioning device remotely to turning on the ignition of a car through a command issued from a remote location or asking Alexa or Google Assistant to search for weather conditions in an area. IoT has proved to be game-changing for many industries such as Supply Chain, Shipping and Transportation providing updates on the status of shipments in real time. This has resulted in a huge amount of data created by a lot of these devices all of which need to be processed in real time.
In this thesis, we propose a method to collect sensor data from IoT devices and use blockchain to store and retrieve the collected data in a secure and decentralized fashion within a closed system, suitable for a single enterprise or a group of companies in industries like shipping where sharing data with each other is required. Much like blockchain, we envision a future where IoT devices can connect and disconnect to distributed systems without causing downtime for the data collection or storage or relying on a cloud-based storage system for synchronizing data between devices. We also look at how the performance of some of these distributed systems like Inter Planetary File System (IPFS) and Ethereum Swarm compare on low-powered devices like the raspberry pi
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