Biblio

In this paper, we propose a new ordered statistics decoding (OSD) for linear block codes, which is referred to as local constraint-based OSD (LC-OSD). Distinguished from the conventional OSD, which chooses the most reliable basis (MRB) for re-encoding, the LC-OSD chooses an extended MRB on which local constraints are naturally imposed. A list of candidate codewords is then generated by performing a serial list Viterbi algorithm (SLVA) over the trellis specified with the local constraints. To terminate early the SLVA for complexity reduction, we present a simple criterion which monitors the ratio of the bound on the likelihood of the unexplored candidate codewords to the sum of the hard-decision vector’s likelihood and the up-to-date optimal candidate’s likelihood. Simulation results show that the LC-OSD can have a much less number of test patterns than that of the conventional OSD but cause negligible performance loss. Comparisons with other complexity-reduced OSDs are also conducted, showing the advantages of the LC-OSD in terms of complexity.

Vulnerability discovery is an important field of computer security research and development today. Because most of the current vulnerability discovery methods require large-scale manual auditing, and the code parsing process is cumbersome and time-consuming, the vulnerability discovery effect is reduced. Therefore, for the uncertainty of vulnerability discovery itself, it is the most basic tool design principle that auxiliary security analysts cannot completely replace them. The purpose of this paper is to study the source code vulnerability discovery method based on graph neural network. This paper analyzes the three processes of data preparation, source code vulnerability mining and security assurance of the source code vulnerability mining method, and also analyzes the suspiciousness and particularity of the experimental results. The empirical analysis results show that the types of traditional source code vulnerability mining methods become more concise and convenient after using graph neural network technology, and we conducted a survey and found that more than 82% of people felt that the design source code vulnerability mining method used When it comes to graph neural networks, it is found that the design efficiency has become higher.

Nowadays, improving the reliability and security of the transmitted data has gained more attention with the increase in emerging power-limited and lightweight communication devices. Also, the transmission needs to meet specific latency requirements. Combining data encryption and encoding in one physical layer block has been exploited to study the effect on security and latency over traditional sequential data transmission. Some of the current works target secure error-correcting codes that may be candidates for post-quantum computing. However, modifying the popularly used channel coding techniques to guarantee secrecy and maintain the same error performance and complexity at the decoder is challenging since the structure of the channel coding blocks is altered which results in less optimal decoding performance. Also, the redundancy nature of the error-correcting codes complicates the encryption method. In this paper, we briefly review the proposed security schemes on Turbo codes. Then, we propose a secure turbo code design and compare it with the relevant security schemes in the literature. We show that the proposed method is more secure without adding complexity.

We present a ternary source coding scheme in this paper, which is a special class of low density generator matrix (LDGM) codes. We prove that a ternary linear block LDGM code, whose generator matrix is randomly generated with each element independent and identically distributed, is universal for source coding in terms of the symbol-error rate (SER). To circumvent the high-complex maximum likelihood decoding, we introduce a special class of convolutional LDGM codes, called block Markov superposition transmission of repetition (BMST-R) codes, which are iteratively decodable by a sliding window algorithm. Then the presented BMST-R codes are applied to construct a tandem scheme for Gaussian source compression, where a dead-zone quantizer is introduced before the ternary source coding. The main advantages of this scheme are its universality and flexibility. The dead-zone quantizer can choose a proper quantization level according to the distortion requirement, while the LDGM codes can adapt the code rate to approach the entropy of the quantized sequence. Numerical results show that the proposed scheme performs well for ternary sources over a wide range of code rates and that the distortion introduced by quantization dominates provided that the code rate is slightly greater than the discrete entropy.

Fractional repetition (FR) codes are a special family of regenerating codes with the repair-by-transfer property. The constructions of FR codes are naturally related to combinatorial designs, graphs, and hypergraphs. Given the file size of an FR code, it is desirable to determine the minimum number of storage nodes needed. The problem is related to an extremal graph theory problem, which asks for the minimum number of vertices of an α-regular graph such that any subgraph with k vertices has at most δ edges. In this paper, we present a class of regular graphs for this problem to give the bounds for the minimum number of storage nodes for the FR codes.

With memory safety and security issues continuing to plague modern systems, security is rapidly becoming a first class priority in new architectures and competes directly with performance and power efficiency. The capability-based architecture model provides a promising solution to many memory vulnerabilities by replacing plain addresses with capabilities, i.e., addresses and related metadata. A key advantage of the capability model is compatibility with existing code bases. Capabilities can be implemented transparently to a programmer, i.e., without source code changes. Capabilities leverage semantics in source code to describe access permissions but require customized compilers to translate the semantics to their binary equivalent.In this work, we introduce a complete capabilityaware compiler toolchain for such secure architectures. We illustrate the compiler construction with a RISC-V capability-based architecture, called Zeno. As a securityfocused, large-scale, global shared memory architecture, Zeno implements a Namespace-based capability model for accesses. Namespace IDs (NSID) are encoded with an extended addressing model to associate them with access permission metadata elsewhere in the system. The NSID extended addressing model requires custom compiler support to fully leverage the protections offered by Namespaces. The Zeno compiler produces code transparently to the programmer that is aware of Namespaces and maintains their integrity. The Zeno assembler enables custom Zeno instructions which support secure memory operations. Our results show that our custom toolchain moderately increases the binary size compared to nonZeno compilation. We find the minimal overhead incurred by the additional NSID management instructions to be an acceptable trade-off for the memory safety and security offered by Zeno Namespaces.

Binary analysis is pervasively utilized to assess software security and test vulnerabilities without accessing source codes. The analysis validity is heavily influenced by the inferring ability of information related to the code compilation. Among the compilation information, compiler type and optimization level, as the key factors determining how binaries look like, are still difficult to be inferred efficiently with existing tools. In this paper, we conduct a thorough empirical study on the binary's appearance under various compilation settings and propose a lightweight binary analysis tool based on the simplest machine learning method, called DIComP to infer the compiler and optimization level via most relevant features according to the observation. Our comprehensive evaluations demonstrate that DIComP can fully recognize the compiler provenance, and it is effective in inferring the optimization levels with up to 90% accuracy. Also, it is efficient to infer thousands of binaries at a millisecond level with our lightweight machine learning model (1MB).

The authors' industry experiences suggest that compiler warnings, a lightweight version of program analysis, are valuable early bug detection tools. Significant costs are associated with patches and security bulletins for issues that could have been avoided if compiler warnings were addressed. Yet, the industry's attitude towards compiler warnings is mixed. Practices range from silencing all compiler warnings to having a zero-tolerance policy as to any warnings. Current published data indicates that addressing compiler warnings early is beneficial. However, support for this value theory stems from grey literature or is anecdotal. Additional focused research is needed to truly assess the cost-benefit of addressing warnings.

Cognitive Radio (CR) is an attractive solution in mobile communication for solving the spectrum scarcity problem. Moreover, security concerns are not yet fully satisfied. This article focuses on attacks such as the Primary user emulation attack (PUE) and the jammer attack. These attacks create anomalous spectrum access thereby disturbing the dynamic spectrum usage in the CR networks. A framework based on cross-layer has been designed effectively to determine these attacks in the CR networks. First, each secondary user will sense the spectrum in the physical layer and construct a feature space. Using the extracted features, the clusters are formed effectively for each user. In the network layer, multipath routing is employed to discover the routes for the secondary user. If the node in the path identifies any spectrum shortage, it will verify that location with the help of constructed cluster. If the node does not belong to any of the clusters, then it will be identified as the attacker node. Simulation results and security analysis are performed using the NS2 simulations, which show improvement in detection of the attacks, decrease in the detection delay, and less route dis-connectivity. The proposed cross-layer framework identifies the anomalous spectrum access attack effectively.

In this paper, physical-layer security (PLS) of an underlay cognitive radio network (CRN) operating over cascaded Rayleigh fading channels is examined. In this scenario, a secondary user (SU) transmitter communicates with a SU receiver through a cascaded Rayleigh fading channel while being exposed to eavesdroppers. By harvesting energy from the SU transmitter, a cooperating jammer attempts to ensure the privacy of the transmitted communications. That is, this harvested energy is utilized to generate and spread jamming signals to baffle the information interception at eavesdroppers. Additionally, two scenarios are examined depending on the manner in which eavesdroppers intercept messages; colluding and non-colluding eavesdroppers. These scenarios are compared to determine which poses the greatest risk to the network. Furthermore, the channel cascade effect on security is investigated. Distances between users and the density of non-colluding eavesdroppers are also investigated. Moreover, cooperative jamming-based energy harvesting effectiveness is demonstrated.

Cognitive Radio Network makes intelligent use of the spectrum resources. However, spectrum sensing is vulnerable to numerous harmful assaults. To lower the network's performance, hackers attempt to alter the sensed result. In the fusion centre, blockchain technology is used to make broad judgments on spectrum sensing in order to detect and thwart hostile activities. The sensed local results are hashed using the SHA 3 technique. This improves spectrum sensing precision and effectively thwarts harmful attacks. In comparison to other established techniques like equal gain combining, the simulation results demonstrate higher detection probability and sensing precision. Thus, employing Blockchain technology, cognitive radio network security can be significantly enhanced.

The strategy of permanently allocating a frequency band in a wireless communication network to one application has led to exceptionally low utilization of the vacant spectrum. By utilizing the unused licensed spectrum along with the unlicensed spectrum, Cognitive Radio Sensor Network (CRSNs) ensures the efficiency of spectrum management. To utilize the spectrum dynamically it is important to safeguard the spectrum sensing. Cooperative Spectrum Sensing (CSS) is recommended for this task. CSS aims to provide reliable spectrum sensing. However, there are various vulnerabilities experienced in CSS which can influence the performance of the network. In this work, the focus is on the Byzantine attack in CSS and current security solutions available to avoid the Byzantines in CRSN.

Browsers are one of the most widely used types of software around the world. This prevalence makes browsers a prime target for cyberattacks. To mitigate these threats, users can practice safe browsing habits and take advantage of the security features available to browsers. These protections, however, could be severely crippled if the browser itself were malicious. Presented in this paper is the concept of the evil-twin browser (ETB), a clone of a legitimate browser that looks and behaves identically to the original browser, but discreetly performs other tasks that harm a user's security. To better understand the concept of the evil-twin browser, a prototype ETB named ChroNe was developed. The creation and installation process of ChroN e is discussed in this paper. This paper also explores the motivation behind creating such a browser, examines existing relevant work, inspects the open-source codebase Chromium that assisted in ChroNe's development, and discusses relevant topics like ways to deliver an ETB, the capabilities of an ETB, and possible ways to defend against ETBs.

Aiming at the current troubles encountered by enterprise employees in their daily work when operating business systems due to web compatibility issues, a dual-core secure browser is designed and developed in the paper based on summarizing the current development status of multi-core browsers, key difficulties and challenges in the field. Based on the Chromium open-source project, the design of a dual-core browser auto-adaptation method is carried out. Firstly, dual-core encapsulation technology is implemented, followed by a study of the core auto-adaptation algorithm, and then a core cookie sharing function is developed based on Hook technology. In addition, the security of the browser is reinforced by designing a cookie manager, adding behavior monitoring functions, and unified platform control to enhance confidentiality and security, providing a safe and secure interface for employees' work and ubiquitous IoT access. While taking security into account, the browser realizes the need for a single browser compatible with all business system web pages of the enterprise, enhancing the operating experience of the client. Finally, the possible future research directions in this field are summarized and prospected.

IoT has been an efficient technology for interconnecting different physical objects with the internet. Several cyber-attacks have resulted in compromise in security. Blockchain distributed ledger provide immutability that can answer IoT security concerns. The paper aims at highlighting the challenges & problems currently associated with IoT implementation in real world and how these problems can be minimized by implementing Blockchain based solutions and smart contracts. Blockchain helps in creation of new highly robust IoT known as Blockchain of Things(BCoT). We will also examine presently employed projects working with integrating Blockchain & IoT together for creating desired solutions. We will also try to understand challenges & roadblocks preventing the further implementation of both technologies merger.

CP-ABE (Ciphertext-policy attribute based encryption) is considered as a secure access control for data sharing. However, the SK(secret key) in most CP-ABE scheme is generated by Centralized authority(CA). It could lead to the high cost of building trust and single point of failure. Because of the characters of blockchain, some schemes based on blockchain have been proposed to prevent the disclosure and protect privacy of users' attribute. Thus, a new CP-ABE identity-attribute management(IAM) data sharing scheme is proposed based on blockchain, i.e. IAM-BDSS, to guarantee privacy through the hidden policy and attribute. Meanwhile, we define a transaction structure to ensure the auditability of parameter transmission on blockchain system. The experimental results and security analysis show that our IAM-BDSS is effective and feasible.

Blockchain is a relatively new technology, a distributed database used for sharing between nodes of computer networks. A blockchain stores all information in automated digital format as a database. Blockchain innovation ensures the accuracy and security of the data record and generates trust without the need for a trusted third party. The objectives of this paper are to determine the security risk of the blockchain systems, analyze the vulnerabilities exploited on the blockchain, and identify recent security challenges that the blockchain faces. This review paper presents some of the previous studies of the security threats that blockchain faces and reviews the security enhancement solutions for blockchain vulnerabilities. There are some studies on blockchain security issues, but there is no systematic examination of the problem, despite the blockchain system’s security threats. An observational research methodology was used in this research. Through this methodology, many research related to blockchain threats and vulnerabilities obtained. The outcomes of this research are to Identify the most important security threats faced by the blockchain and consideration of security recently vulnerabilities. Processes and methods for dealing with security concerns are examined. Intelligent corporate security academic challenges and limitations are covered throughout this review. The goal of this review is to serve as a platform as well as a reference point for future work on blockchain-based security.

Blockchain smart contracts are prevalent nowadays as numerous applications are developed based on this feature. Though smart contracts are important and widely used, they contain certain vulnerabilities. This paper discusses various security issues that arise in smart contract applications. They are categorized in the smart contract platform, the applications that integrate with the Blockchain, and the vulnerabilities in smart contract code. A detailed study of smart contract-specific vulnerabilities and the defense against those vulnerabilities are presented in this article. Because of certain limitations of platforms or programming language used to write smart contract, there are possibilities of attacks on smart contracts. Hence different security measures or precautions to be taken while writing the smart contract code is discussed in this article. This will prevent the potential attacks happening on Blockchain distributed applications.

The exponential rise of online services has heightened awareness of safeguarding the various applications that cooperate with and provide Internet users. Users must present their credentials, such as user name and secret code, to the servers to be authorized. This sensitive data should be secured from being exploited due to numerous security breaches, resulting in criminal activity. It is vital to secure systems against numerous risks. This article offers a novel approach to protecting against brute force attacks. A solution is presented where the user obtains the keypad on each occurrence. Following the establishment of the keypad, the webserver produces an encrypted password for the user's Computer/device authentication. The encrypted password will be used for authentication; users must type the amended one-time password (OTP) every time they access the website. This research protects passwords using reformation-based encryption and decryption and optimal honey encryption (OH-E) and decryption.

The development of IoT has penetrated various sectors. The development of IoT devices continues to increase and is predicted to reach 75 billion by 2025. However, the development of IoT devices is not followed by security developments. Therefore, IoT devices can become gateways for cyber attacks, including brute force and sniffing attacks. Authentication mechanisms can be used to ward off attacks. However, the implementation of authentication mechanisms on IoT devices is challenging. IoT devices are dominated by constraint devices that have limited computing. Thus, conventional authentication mechanisms are not suitable for use. Two-factor authentication using RFID and fingerprint can be a solution in providing an authentication mechanism. Previous studies have proposed a two-factor authentication mechanism using RFID and fingerprint. However, previous research did not pay attention to message exchange security issues and did not provide mutual authentication. This research proposes a secure mutual authentication protocol using two-factor RFID and fingerprint using MQTT protocol. Two processes support the authentication process: the registration process and authentication. The proposed protocol is tested based on biometric security by measuring the false acceptance rate (FAR) and false rejection rate (FRR) on the fingerprint, measuring brute force attacks, and measuring sniffing attacks. The test results obtained the most optimal FAR and FRR at the 80% threshold. Then the equal error rate (ERR) on FAR and FRR is around 59.5%. Then, testing brute force and sniffing attacks found that the proposed protocol is resistant to both attacks.

In recent decennium, hardware security has gained a lot of attention due to different types of attacks being launched, such as IP theft, reverse engineering, counterfeiting, etc. The critical testing infrastructure incorporated into ICs is very popular among attackers to mount side-channel attacks. The IEEE standard 1687 (IJTAG) is one such testing infrastructure that is the focus of attackers these days. To secure access to the IJTAG network, various techniques based on Locking SIB (LSIB) have been proposed. One such very effective technique makes use of Security Linear Feedback Shift Register (SLFSR) along with LSIB. The SLFSR obfuscates the scan chain information from the attacker and hence makes the brute-force attack against LSIB ineffective.In this work, it is shown that the SLFSR based Locking SIB is vulnerable to side-channel attacks. A power analysis attack along with known-plaintext attack is used to determine the IJTAG network structure. First, the known-plaintext attack is used to retrieve the SLFSR design information. This information is further used along with power analysis attack to determine the exact length of the scan chain which in turn breaks the whole security scheme. Further, a countermeasure is proposed to prevent the aforementioned hybrid attack.

Recently, a mechanism that randomly shuffles the data sent and allows securing the communication without the need to encrypt all the information has been proposed. This proposal is ideal for IoT systems with low computational capacity. In this work, we analyze the strength of this proposal from a brute-force attack approach to obtain the original message without knowledge of the applied disordering. It is demonstrated that for a set of 10x10 16-bit data, the processing time and the required memory are unfeasible with current technology. Therefore, it is safe.

Since the provision of digital services in our days (e.g. container management, transport of COVID vaccinations or LNG) in most economic sectors (e.g. maritime, health, energy) involve national, EU and non-EU stakeholders compose complex Supply Chain Services (SCS). The security of the SCS is most important and it emphasized in the NIS 2 directive [3] and it is a shared responsibility of all stakeholders involved that will need to be compliant with a scheme. In this paper we present an overview of the proposed Cybersecurity Certification Scheme for Supply Chain Services (EUSCS) as proposed by the European Commission (EC) project CYRENE [1]. The EUSCS scheme covers all the three assurance levels defined in the Cybersecurity Act (CSA) [2] taking into consideration the criticality of SCS according to the NIS 2 directive [3], the ENISA Threat Landscape for Supply Chain Attacks [4] and the CYRENE extended online Information Security Management System (ISMS) that allows all SCS stakeholders to provide and access all information needed for certification purposes making the transition from current national schemes in the EU easier.

With the rapid development of information technology, hacker invasion, Internet fraud and privacy disclosure and other events frequently occur, therefore information security issues become the focus of attention. Protecting the secure transmission of information has become a hot topic in today's research. As the carrier of information, image has the characteristics of vivid image and large amount of information. It has become an indispensable part of people's communication. In this paper, we proposed the key simulation analysis research based on M-J set. The research uses a complex iterative mapping to construct M set. On the basis of the constructed M set, the constructed Julia set is used to form the encryption key. The experimental results show that the generalized M-set has the characteristics of chaotic characteristic and initial value sensitivity, and the complex mapping greatly exaggerates the key space. The research on the key space based on the generalized M-J set is helpful to improve the effect of image encryption.

E-health, smart health and telemedicine are examples of sophisticated healthcare systems. For end-to-end communication, these systems rely on digital medical information. Although this digitizing saves much time, it is open source. As a result, hackers could potentially manipulate the digital medical image as it is being transmitted. It is harder to diagnose an actual disease from a modified digital medical image in medical diagnostics. As a result, ensuring the security and confidentiality of clinical images, as well as reducing the computing time of encryption algorithms, appear to be critical problems for research groups. Conventional approaches are insufficient to ensure high-level medical image security. So this review paper focuses on depicting advanced methods like DNA cryptography and Chaotic Map as advanced techniques that could potentially help in encrypting the digital image at an effective level. This review acknowledges the key accomplishments expressed in the encrypting measures and their success indicators of qualitative and quantitative measurement. This research study also explores the key findings and reasons for finding the lessons learned as a roadmap for impending findings.