Current Issue : January-March Volume : 2023 Issue Number : 1 Articles : 5 Articles
Satellite communications have historically played a vital role in a variety of industries, including maritime communications. The marine communication environment is exceedingly complicated, and extracting the characteristics of communication equipment signals is difficult. This research proposes a method for extracting satellite signal fingerprint characteristics based on the maritime complex communication environment. To create the signal fingerprint feature vector, the marginal spectral entropy is determined using the HHT (Hilbert-Huang transform) time-frequency analysis approach. Furthermore, by merging the Mahalanobis distance approach with the EEMD (ensemble empirical mode decomposition) algorithm, this study enhances it. The improved EEMD algorithm decomposes the original signal using EEMD, calculates the Mahalanobis distance between each IMF (intrinsic mode function) component and the raw data, optimizes the adaptive threshold using MPA (marine predators algorithm), and then analyzes the IMF components and redundant IMF components. It was decided to eliminate superfluous IMF components. Finally, this article mimics the Iridium satellite signal. The results of the experiments suggest that using this strategy minimizes the computational cost of the next step in fingerprint feature extraction while ensuring the accuracy of signal fingerprint feature recognition....
With the occurrence of cyber security incidents, the value of threat intelligence is coming to the fore. Timely extracting Indicator of Compromise (IOC) from cyber threat intelligence can quickly respond to threats. However, the sparse text in public threat intelligence scatters useful information, which makes it challenging to assess unstructured threat intelligence. In this paper, we proposed Cyber Threat Intelligence Automated Assessment Model (TIAM), a method to automatically assess highly sparse threat intelligence from multiple dimensions. TIAM implemented automatic classification of threat intelligence based on feature extraction, defined assessment criteria to quantify the value of threat intelligence, and combined ATT&CK to identify attack techniques related to IOC. Finally, we associated the identified IOCs, ATT&CK techniques, and intelligence quantification results. The experimental results shown that TIAM could better assess threat intelligence and help security managers to obtain valuable cyber threat intelligence....
In recent years, the Internet of Things has become urgent in our lives, as it is used in many areas to facilitate business and daily life. But unfortunately, there are concerns due to security and safety issues. Therefore, many researchers have turned their attention to identifying the best solutions for increasing security and raising privacy one of which is the usage of Blockchain in the Internet of Things. This paper presents the benefits of applying Blockchain technology to the Internet of Things, the challenges faced and the most up-to-date components that satisfy the Component-Based Development (CBD) principles to enhance security and privacy....
In the current society of rapid expansion of information, big data have achieved vigorous development in all walks of life, considerably promoting data transmission and information sharing. Meanwhile, individuals are becoming increasingly reliant on big data and the Internet, but at the same time, the threat of information security posed by big data is becoming increasingly visible. As a result, how to protect the information security of big data has piqued the interest of both government and businesses. The essence of information security management is risk management, which is closely related to each other. Therefore, this study focuses on the following two aspects of research work. On the one hand, most existing risk management models merely describe risk management in the abstract from a macro-level, and they lack research on risk assessment, making them ineffective. This research builds a novel information security risk management model on the basis of existing risk management models based on the concept of multidimensional risk management. To achieve multidimensional dynamic management of big data risks and to keep them within an acceptable range as much as possible, the model is divided into five levels and two dimensions. On the other hand, this research also optimizes and improves the fuzzy mathematical analysis method and proposes a fuzzy comprehensive assessment method as the core algorithm for the risk assessment layer in the model. As a post-event risk assessment method, the advantage of this method is that it can comprehensively consider factors affecting risk and can quantify some assessment factors in the real network to achieve an effective combination of qualitative and quantitative, thereby providing a basis for decision-making in risk analysis and risk control. Finally, the effectiveness of the risk model in the real application is verified by example analysis, and it is intended that the study work would provide assistance and assurance for big data information security management....
This rapidly changing digital world is always sensitive to improving security and resilience to protect the inhabitants of this ecosystem in terms of data, processes, repositories, communication, and functions. The transformation of this digital ecosystem is heavily dependent on cloud computing, as it is becoming the global platform for individuals, corporates, and even governments. Therefore, the concerns related to security are now linked closely with cloud computing. In this paper, a multi-cloud security framework takes a view on the development of security mechanisms to provide a diversion to the attacker. The purpose is to gain more time to analyze the attack and mitigate the intrusion without compromises. This mechanism is designed using the honeypot technology that has been around for some time but has not been used in cloud computing and other technologies. The proposed framework provides modules related to managing the multi-cloud platform, the intrusion detection and prevention system, and honeypots. The results show significant improvement in the accuracy of detecting attacks. These results are generated in a twophase scenario, and the first phase has been analyzed without the engagement of the honeypot module presented in the framework. The second phase has been executed with same parameters and conditions by engaging the honeypot module. It includes a comparison taxonomy of both results and an in-depth study of existing honeypots, as well as critical design elements for current honeypot research and outstanding concerns for future honeypots in IoT, multi-cloud contexts....
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