Do you want to publish a course? Click here

Intrinsically Reliable and Lightweight Physical Obfuscated Keys

149   0   0.0 ( 0 )
 Added by Chenglu Jin
 Publication date 2017
and research's language is English




Ask ChatGPT about the research

Physical Obfuscated Keys (POKs) allow tamper-resistant storage of random keys based on physical disorder. The output bits of current POK designs need to be first corrected due to measurement noise and next de-correlated since the original output bits may not be i.i.d. (independent and identically distributed) and also public helper information for error correction necessarily correlates the corrected output bits.For this reason, current designs include an interface for error correction and/or output reinforcement, and privacy amplification for compressing the corrected output to a uniform random bit string. We propose two intrinsically reliable POK designs with only XOR circuitry for privacy amplification (without need for reliability enhancement) by exploiting variability of lithographic process and variability of granularity in phase change memory (PCM) materials. The two designs are demonstrated through experiments and simulations.



rate research

Read More

In this paper, we investigate physical-layer security (PLS) methods for proximity-based group-key establishment and proof of location. Fields of application include secure car-to-car communication, privacy-preserving and secure distance evidence for healthcare or location-based feature activation. Existing technologies do not solve the problem satisfactorily, due to communication restrictions, e.g., ultra-wide band (UWB) based time of flight measurements, or trusted hardware, e.g., using global navigation satellite system (GNSS) positioning data. We introduce PLS as a solution candidate. It is information theoretically secure, which also means post-quantum resistant, and has the potential to run on resource constrained devices with low latency. Furthermore, we use wireless channel properties of satellite-to-Earth links, demonstrate the first feasibility study using off-the-shelf hardware testbeds and present first evaluation results and future directions for research.
175 - Aldar C-F. Chan 2008
Any secured system can be modeled as a capability-based access control system in which each user is given a set of secret keys of the resources he is granted access to. In some large systems with resource-constrained devices, such as sensor networks and RFID systems, the design is sensitive to memory or key storage cost. With a goal to minimize the maximum users key storage, key compression based on key linking, that is, deriving one key from another without compromising security, is studied. A lower bound on key storage needed for a general access structure with key derivation is derived. This bound demonstrates the theoretic limit of any systems which do not trade off security and can be treated as a negative result to provide ground for designs with security tradeoff. A concrete, provably secure key linking scheme based on pseudorandom functions is given. Using the key linking framework, a number of key pre-distribution schemes in the literature are analyzed.
At Crypto07, Goyal introduced the concept of Accountable Authority Identity-Based Encryption as a convenient tool to reduce the amount of trust in authorities in Identity-Based Encryption. In this model, if the Private Key Generator (PKG) maliciously re-distributes users decryption keys, it runs the risk of being caught and prosecuted. Goyal proposed two constructions: the first one is efficient but can only trace well-formed decryption keys to their source; the second one allows tracing obfuscated decryption boxes in a model (called weak black-box model) where cheating authorities have no decryption oracle. The latter scheme is unfortunately far less efficient in terms of decryption cost and ciphertext size. In this work, we propose a new construction that combines the efficiency of Goyals first proposal with a very simple weak black-box tracing mechanism. Our scheme is described in the selective-ID model but readily extends to meet all security properties in the adaptive-ID sense, which is not known to be true for prior black-box schemes.
Several cybersecurity domains, such as ransomware detection, forensics and data analysis, require methods to reliably identify encrypted data fragments. Typically, current approaches employ statistics derived from byte-level distribution, such as entropy estimation, to identify encrypted fragments. However, modern content types use compression techniques which alter data distribution pushing it closer to the uniform distribution. The result is that current approaches exhibit unreliable encryption detection performance when compressed data appears in the dataset. Furthermore, proposed approaches are typically evaluated over few data types and fragment sizes, making it hard to assess their practical applicability. This paper compares existing statistical tests on a large, standardized dataset and shows that current approaches consistently fail to distinguish encrypted and compressed data on both small and large fragment sizes. We address these shortcomings and design EnCoD, a learning-based classifier which can reliably distinguish compressed and encrypted data. We evaluate EnCoD on a dataset of 16 different file types and fragment sizes ranging from 512B to 8KB. Our results highlight that EnCoD outperforms current approaches by a wide margin, with accuracy ranging from ~82 for 512B fragments up to ~92 for 8KB data fragments. Moreover, EnCoD can pinpoint the exact format of a given data fragment, rather than performing only binary classification like previous approaches.
New cryptographic techniques such as homomorphic encryption (HE) allow computations to be outsourced to and evaluated blindfolded in a resourceful cloud. These computations often require private data owned by multiple participants, engaging in joint evaluation of some functions. For example, Genome-Wide Association Study (GWAS) is becoming feasible because of recent proliferation of genome sequencing technology. Due to the sensitivity of genomic data, these data should be encrypted using different keys. However, supporting computation on ciphertexts encrypted under multiple keys is a non-trivial task. In this paper, we present a comprehensive survey on different state-of-the-art cryptographic techniques and schemes that are commonly used. We review techniques and schemes including Attribute-Based Encryption (ABE), Proxy Re-Encryption (PRE), Threshold Homomorphic Encryption (ThHE), and Multi-Key Homomorphic Encryption (MKHE). We analyze them based on different system and security models, and examine their complexities. We share lessons learned and draw observations for designing better schemes with reduced overheads.
comments
Fetching comments Fetching comments
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا