scholarly journals ZPiE: Zero-Knowledge Proofs in Embedded Systems

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2569
Author(s):  
Xavier Salleras ◽  
Vanesa Daza
Keyword(s):  
Embedded Systems ◽  
Identity Management ◽  
State Of The Art ◽  
Limited Resources ◽  
Proof Of Concept ◽  
Authentication Protocols ◽  
Cryptographic Primitives ◽  
Zero Knowledge ◽  
In The Wild ◽  
The Internet Of Things

Zero-Knowledge Proofs (ZKPs) are cryptographic primitives allowing a party to prove to another party that the former knows some information while keeping it secret. Such a premise can lead to the development of numerous privacy-preserving protocols in different scenarios, like proving knowledge of some credentials to a server without leaking the identity of the user. Even when the applications of ZKPs were endless, they were not exploited in the wild for a couple of decades due to the fact that computing and verifying proofs was too computationally expensive. However, the advent of efficient schemes (in particular, zk-SNARKs) made this primitive to break into the scene in fields like cryptocurrencies, smart-contracts, and more recently, self-sovereign scenarios: private-by-design identity management and authentication. Nevertheless, its adoption in environments like the Internet of Things (IoT) remains unexplored due to the computational limitations of embedded systems. In this paper, we introduce ZPiE, a C library intended to create ZKP applications to be executed in embedded systems. Its main feature is portability: it can be compiled, executed, and used out-of-the-box in a wide variety of devices. Moreover, our proof-of-concept has been proved to work smoothly in different devices with limited resources, which can execute state-of-the-art ZKP authentication protocols.

A Lightweight Architecture for Hardware-Based Security in the Emerging Era of Systems of Systems

2021 ◽  
Vol 17 (3) ◽  
pp. 1-25
Author(s):  
Nico Mexis ◽  
Nikolaos Athanasios Anagnostopoulos ◽  
Shuai Chen ◽  
Jan Bambach ◽  
Tolga Arul ◽  
...  
Keyword(s):  
State Of The Art ◽  
Low Cost ◽  
System Of Systems ◽  
Proof Of Concept ◽  
Systems Of Systems ◽  
Blockchain Technology ◽  
Security Challenges ◽  
Commercial Off The Shelf ◽  
New Generation ◽  
The Internet Of Things

In recent years, a new generation of the Internet of Things (IoT 2.0) is emerging, based on artificial intelligence, the blockchain technology, machine learning, and the constant consolidation of pre-existing systems and subsystems into larger systems. In this work, we construct and examine a proof-of-concept prototype of such a system of systems, which consists of heterogeneous commercial off-the-shelf components, and utilises diverse communication protocols. We recognise the inherent need for lightweight security in this context, and address it by employing a low-cost state-of-the-art security solution. Our solution is based on a novel hardware and software co-engineering paradigm, utilising well-known software-based cryptographic algorithms, in order to maximise the security potential of the hardware security primitive (a Physical Unclonable Function) that is used as a security anchor. The performance of the proposed security solution is evaluated, proving its suitability even for real-time applications. Additionally, the Dolev-Yao attacker model is considered in order to assess the resilience of our solution towards attacks against the confidentiality, integrity, and availability of the examined system of systems. In this way, it is confirmed that the proposed solution is able to address the emerging security challenges of the oncoming era of systems of systems.

CNN-based Rain Reduction in Street View Images

2020 ◽  
Vol 2020 (1) ◽  
pp. 78-81
Author(s):  
Simone Zini ◽  
Simone Bianco ◽  
Raimondo Schettini
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
State Of The Art ◽  
Weather Conditions ◽  
Specific Interest ◽  
Optical Character ◽  
Street View ◽  
In The Wild ◽  
Bad Weather ◽  
Detection And Recognition

Rain removal from pictures taken under bad weather conditions is a challenging task that aims to improve the overall quality and visibility of a scene. The enhanced images usually constitute the input for subsequent Computer Vision tasks such as detection and classification. In this paper, we present a Convolutional Neural Network, based on the Pix2Pix model, for rain streaks removal from images, with specific interest in evaluating the results of the processing operation with respect to the Optical Character Recognition (OCR) task. In particular, we present a way to generate a rainy version of the Street View Text Dataset (R-SVTD) for "text detection and recognition" evaluation in bad weather conditions. Experimental results on this dataset show that our model is able to outperform the state of the art in terms of two commonly used image quality metrics, and that it is capable to improve the performances of an OCR model to detect and recognise text in the wild.

Algorithm for optimal allocation of limited resources based on the game iteration method

2019 ◽  
pp. 89-99
Author(s):  
V. Ya. Vilisov
Keyword(s):  
Optimal Control ◽  
Linear Programming ◽  
Embedded Systems ◽  
Iterative Method ◽  
High Speed ◽  
Optimal Allocation ◽  
Software Implementation ◽  
Limited Resources ◽  
Matrix Game ◽  
Acceptable Accuracy

The article proposes an algorithm for solving a linear programming problem (LPP) based on the use of its representation in the form of an antagonistic matrix game and the subsequent solution of the game by an iterative method. The algorithm is implemented as a computer program. The rate of convergence of the estimates of the solution to the actual value with the required accuracy has been studied. The software implementation shows a high speed of obtaining the LPP solution with acceptable accuracy in fractions or units of seconds. This allows the use algorithm in embedded systems for optimal control.

Publicly auditable conditional blind signatures

2021 ◽  
Vol 29 (2) ◽  
pp. 229-271
Author(s):  
Panagiotis Grontas ◽  
Aris Pagourtzis ◽  
Alexandros Zacharakis ◽  
Bingsheng Zhang
Keyword(s):  
Proof Of Concept ◽  
Equivalence Test ◽  
Zero Knowledge ◽  
Private Key ◽  
Blind Signatures ◽  
Cryptographic Primitive ◽  
Security Properties ◽  
Designated Verifier

This work formalizes Publicly Auditable Conditional Blind Signatures (PACBS), a new cryptographic primitive that allows the verifiable issuance of blind signatures, the validity of which is contingent upon a predicate and decided by a designated verifier. In particular, when a user requests the signing of a message, blinded to protect her privacy, the signer embeds data in the signature that makes it valid if and only if a condition holds. A verifier, identified by a private key, can check the signature and learn the value of the predicate. Auditability mechanisms in the form of non-interactive zero-knowledge proofs are provided, so that a cheating signer cannot issue arbitrary signatures and a cheating verifier cannot ignore the embedded condition. The security properties of this new primitive are defined using cryptographic games. A proof-of-concept construction, based on the Okamoto–Schnorr blind signatures infused with a plaintext equivalence test is presented and its security is analyzed.

Automatic Vulnerability Detection in Embedded Devices and Firmware

2021 ◽  
Vol 54 (2) ◽  
pp. 1-42
Author(s):  
Abdullah Qasem ◽  
Paria Shirani ◽  
Mourad Debbabi ◽  
Lingyu Wang ◽  
Bernard Lebel ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Symbolic Execution ◽  
Vital Role ◽  
Security And Privacy ◽  
Embedded Devices ◽  
Security Vulnerabilities ◽  
Future Directions ◽  
Hybrid Approaches ◽  
Wide Range ◽  
The Internet Of Things

In the era of the internet of things (IoT), software-enabled inter-connected devices are of paramount importance. The embedded systems are very frequently used in both security and privacy-sensitive applications. However, the underlying software (a.k.a. firmware) very often suffers from a wide range of security vulnerabilities, mainly due to their outdated systems or reusing existing vulnerable libraries; which is evident by the surprising rise in the number of attacks against embedded systems. Therefore, to protect those embedded systems, detecting the presence of vulnerabilities in the large pool of embedded devices and their firmware plays a vital role. To this end, there exist several approaches to identify and trigger potential vulnerabilities within deployed embedded systems firmware. In this survey, we provide a comprehensive review of the state-of-the-art proposals, which detect vulnerabilities in embedded systems and firmware images by employing various analysis techniques, including static analysis, dynamic analysis, symbolic execution, and hybrid approaches. Furthermore, we perform both quantitative and qualitative comparisons among the surveyed approaches. Moreover, we devise taxonomies based on the applications of those approaches, the features used in the literature, and the type of the analysis. Finally, we identify the unresolved challenges and discuss possible future directions in this field of research.

scholarly journals A State-of-the-Art Analysis of Obstacle Avoidance Methods from the Perspective of an Agricultural Sprayer UAV’s Operation Scenario

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1069
Author(s):  
Shibbir Ahmed ◽  
Baijing Qiu ◽  
Fiaz Ahmad ◽  
Chun-Wei Kong ◽  
Huang Xin
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
State Of The Art ◽  
Obstacle Detection ◽  
Crop Monitoring ◽  
Data Intensive ◽  
Structural Details ◽  
Dynamic Operating ◽  
New Generation ◽  
The Internet Of Things

Over the last decade, Unmanned Aerial Vehicles (UAVs), also known as drones, have been broadly utilized in various agricultural fields, such as crop management, crop monitoring, seed sowing, and pesticide spraying. Nonetheless, autonomy is still a crucial limitation faced by the Internet of Things (IoT) UAV systems, especially when used as sprayer UAVs, where data needs to be captured and preprocessed for robust real-time obstacle detection and collision avoidance. Moreover, because of the objective and operational difference between general UAVs and sprayer UAVs, not every obstacle detection and collision avoidance method will be sufficient for sprayer UAVs. In this regard, this article seeks to review the most relevant developments on all correlated branches of the obstacle avoidance scenarios for agricultural sprayer UAVs, including a UAV sprayer’s structural details. Furthermore, the most relevant open challenges for current UAV sprayer solutions are enumerated, thus paving the way for future researchers to define a roadmap for devising new-generation, affordable autonomous sprayer UAV solutions. Agricultural UAV sprayers require data-intensive algorithms for the processing of the images acquired, and expertise in the field of autonomous flight is usually needed. The present study concludes that UAV sprayers are still facing obstacle detection challenges due to their dynamic operating and loading conditions.

scholarly journals A Lightweight Blockchain-Based IoT Identity Management Approach

2021 ◽  
Vol 13 (2) ◽  
pp. 24
Author(s):  
Mohammed Amine Bouras ◽  
Qinghua Lu ◽  
Sahraoui Dhelim ◽  
Huansheng Ning
Keyword(s):  
Identity Management ◽  
Single Point ◽  
Data Access ◽  
Emerging Technology ◽  
Management Approach ◽  
Proof Of Concept ◽  
Data Access Control ◽  
And Storage ◽  
Privacy Issues ◽  
Centralized System

Identity management is a fundamental feature of Internet of Things (IoT) ecosystem, particularly for IoT data access control. However, most of the actual works adopt centralized approaches, which could lead to a single point of failure and privacy issues that are tied to the use of a trusted third parties. A consortium blockchain is an emerging technology that provides a neutral and trustable computation and storage platform that is suitable for building identity management solutions for IoT. This paper proposes a lightweight architecture and the associated protocols for consortium blockchain-based identity management to address privacy, security, and scalability issues in a centralized system for IoT. Besides, we implement a proof-of-concept prototype and evaluate our approach. We evaluate our work by measuring the latency and throughput of the transactions while using different query actions and payload sizes, and we compared it to other similar works. The results show that the approach is suitable for business adoption.

scholarly journals A Guideline on Pseudorandom Number Generation (PRNG) in the IoT

2021 ◽  
Vol 54 (6) ◽  
pp. 1-38
Author(s):  
Peter Kietzmann ◽  
Thomas C. Schmidt ◽  
Matthias Wählisch
Keyword(s):  
General Purpose ◽  
Packet Transmission ◽  
Limited Resources ◽  
Systematic Evaluation ◽  
The Internet ◽  
Random Numbers ◽  
Essential Input ◽  
Attack Surface ◽  
Pseudorandom Number Generation ◽  
The Internet Of Things

Random numbers are an essential input to many functions on the Internet of Things (IoT). Common use cases of randomness range from low-level packet transmission to advanced algorithms of artificial intelligence as well as security and trust, which heavily rely on unpredictable random sources. In the constrained IoT, though, unpredictable random sources are a challenging desire due to limited resources, deterministic real-time operations, and frequent lack of a user interface. In this article, we revisit the generation of randomness from the perspective of an IoT operating system (OS) that needs to support general purpose or crypto-secure random numbers. We analyze the potential attack surface, derive common requirements, and discuss the potentials and shortcomings of current IoT OSs. A systematic evaluation of current IoT hardware components and popular software generators based on well-established test suits and on experiments for measuring performance give rise to a set of clear recommendations on how to build such a random subsystem and which generators to use.

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