نشریه منادی امنیت فضای تولید و تبادل اطلاعات (افتا)
سال دوازدهم شماره 2 (پیاپی 24، پاییز و زمستان 1402)

In the Internet of Things (IoT) environment, security and privacy are paramount concerns for critical applications. The LoRa protocol efficiently enables long-range communication for resource-constrained end devices in LoRaWAN networks. To foster technology adoption and user trust, safeguarding the data collected by end devices is essential. Authentication and key agreement protocols play a pivotal role in achieving this goal. Here, we introduce a novel scheme for authentication and key exchange in LoRaWAN, enabling mutual authentication among participants. This scheme empowers users/end devices and network servers to establish secure end-to-end session keys without unconditional trust. We assess the scheme's security informally and provide formal verification using AVISPA tools and the BAN logic. Furthermore, we compare it to existing authentication schemes, demonstrating its efficiency in terms of computational and communication overhead.

Financial transactions in Bitcoin are stored in a distributed database called the block chain. All transactions are publicly available for all network nodes with the aim of transparency and the possibility of verifying the correctness. But this blockchain transparency feature, exploited by transaction analysis techniques, can lead to the violation of users’ privacy and the disclosure of their identities. Researchers have proposed various techniques such as transaction mixing or fair exchange with the aim of improving privacy in Bitcoin transactions. In this paper, we present a new mixing scheme that overcomes some of the weaknesses of previous schemes. Obviously, in the proposed scheme, users can mix different amounts of Bitcoin in each round of the protocol implementation, which leads to achieving the result in a shorter time and at a lower cost. Also, this scheme is more resistant to denial of service attacks by malicious users.

Cyber security education in Iran is not aligned with global standards and approaches, and three factors, the educational sector, training applicants and stakeholders, and companies do not have proper knowledge of the required specializations and work roles. Different specializations in cyber security work fields in Iran do not match the international standard puzzles and this has created security holes in the country's cyber ecosystem. People working in cyberspace need a combination of domain-specific knowledge, skills, abilities, and other expertise to be as reliable and resilient as the technologies they work with.At the international level, several frameworks have been designed and implemented for the training and employment of cybersecurity professionals. The most important of which are the US National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework, the European Cybersecurity Skills Framework (ECSF), and the Australian Signals Directorate (ASD) Cyber Skills Framework. In this paper, each of these frameworks is briefly introduced and their key features, including purpose, structure, and components, are reviewed and analyzed. In addition, their effectiveness in handling global organizations' challenges in creating and developing cybersecurity expert human resources is evaluated and analyzed critically. This review highlights the strengths and weaknesses of each framework, shows the propinquity of one of the frameworks to Iran's educational and labor markets, and provides recommendations for designing a national framework for training and employing cybersecurity professionals, which can be a great lesson for the country to ensure that the necessary measures are taken as soon as possible by those in charge.

In the world of digital communication, authentication is an important concern and the need for a safe and secure system increases the necessity of designing authentication systems. To perform authentication, biometric-based approaches are of great interest due to the property of being alive and resistant to forgery. In this study, an authentication system based on heart signal is designed. Due to the process of receiving heart signals, their data usually has a lot of noise. In order to prepare the data, in the proposed system, the heart signals are first cleaned and then transferred to the frequency domain for feature extraction. Also, they are converted into an image by applying the Wigner-Ville distribution, so that each image contains the signal information of each person’s heart and is unique. In the proposed authentication system, these images are used for training and evaluation in a deep convolutional neural network. The output of this system provides the possibility of people’s identification. The data of this study are taken from the NSRDB and MITDB databases, and significant results have been obtained compared to previous studies.

Steganalysis is the art of detecting the existence of hidden data. Recent research has revealed that convolutional neural networks (CNNs) can detect data through automatic feature extraction. Several studies investigated the performance of existing models using a limited number of spatial steganography methods. This study aims to propose a CNN and comprehensively investigate its efficiency in detecting different spatial methods. The proposed model comprises three modules: preprocessing, convolutional (five blocks), and classifier (three fully connected layers). The test results for the least-significant-bit (LSB) and pixel-value differencing (PVD) based methods indicate that the proposed method can detect data of even concise length with high accuracy and a low error. The proposed method also detects complexity-based LSB-M (CBL) as an adaptive approach. Lower embedding rates make this success even more impressive. Manual feature extraction has much lower success rates due to low variations of statistical features at low embedding rates than the proposed model.

The Internet of Drones (IoD) refers to the use of unmanned aerial vehicles (UAVs) connected to the Internet. This concept is a specific application of IoT. The IoD may offer opportunities, but it also poses security vulnerabilities. It is necessary to use authentication and key agreement protocols in drone communications to prevent these vulnerabilities. In 2020, Alladi et al presented an authentication and key agreement protocol based on physical unclonable functions called SecAutUAV. They analyzed the security of their scheme through both formal and informal methods. In this paper, we demonstrate the vulnerability of the SecAuthUAV protocol to a key recovery attack. An adversary can obtain a session key between a drone and a ground station by intercepting and analyzing the session data. In addition, we present a secret value recovery attack with complexity , which is lower than the complexity of brute force attacks. An adversary could spoof and track the drone by using these values. In order to improve the security and efficiency of SecAuthUAV, we present a new version and compare it to the original. We utilize both the informal method and formal-based ProVerif to analyze the.security of the latest protocol. To compare the efficiency of the new protocol and SecAuthUAV, we counted their number of operators and functions. The new protocol is more secure and efficient than SecAutUAV.

In a verifiable database scheme (VDB), a client with limited storage resources securely outsources its very large and dynamic database to an untrusted server such that any attempt to tamper with the data, or even any unintentional changes to the data, can be detected by the client with high probability. The latest work in this area has tried to add the secure search feature of single keyword and multiple keywords. In this paper, we intend to add a range query to the features of this database. The scheme presented in this article provides the requirements of a secure search, namely the completeness of the search result, the proof of the empty search result, the lack of additional information leakage and the freshness of the search results, as well as the database with public verifiability. In the proposed scheme, the computational complexity of the client is not changed significantly compared with the previous scheme, but the computational and storage complexity of the server has increased which is justifiable by its rich resources.

The adoption of post-quantum encryption algorithms to replace older asymmetric algorithms is of paramount importance. Diverse categories of post-quantum encryption, including lattice-based and code-based cryptography, are currently in the final stages of NIST's standardization competition, with the aim of providing security against quantum computers. Among the lattice-based key encapsulation mechanisms (KEM) garnering attention in this competition, the NTRU Prime algorithm stands out. The primary challenge in implementing such algorithms revolves around executing resource-intensive polynomial multiplications within a ring structure. Leveraging the Number Theoretic Transform (NTT) allows us to achieve polynomial multiplication with near-linear efficiency (O (n log n)). To enhance hardware efficiency, butterfly structures are frequently employed in NTT multipliers. Our research centers on comparing our approach with the best multiplication implementations utilized in NTRU Prime on FPGA up to the present version. This involves the redesign and modification of data preprocessing methods and storage structures, resulting in an increase in frequency and a reduction in the utilization of LUT resources.