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Have you ever experienced the frustration of trying to hit a bullseye on a moving target? In the medical device industry, cybersecurity is one of the fastest-moving targets. Medical device [...]

The last decade witnessed significant research of user behavior and social networks within online hacker forums and illicit markets. Researchers have used the quantifiable nature of forum posting behaviors to assess network ties between actors and identify key participants based on their connections. These studies are based on the publicly identifiable associations between actors in public posts. Participants within forums can also connect with users through private messaging systems linking users directly through a sort of e-mail-based exchange. Few have considered how the public and private message networks of actors differ and what can be gleaned from their analysis. This study employed a quantitative analysis of a highly popular web forum used by hackers involved in both legal and criminal hacks. First, the networks were built of the relationships between 1,313 users across 12,531 threads and 19,862 public posts, and between those users’ 1,738 private messages. Then the centrality on hidden networks was estimated from the centrality on the visible networks. The implications of this study for policy and our understanding of online network structures are discussed. [ABSTRACT FROM AUTHOR]

Given the sensitive nature of cybersecurity in authoritarian regimes, the existence of semi-autonomous patriotic hackers raises questions about their function because no security-adjacent actor can survive without at least tacit regime approval. Reflecting the attention that the phenomenon has received from scholars of defence and cybersecurity, the hackers' presence has to date been viewed as a pragmatic strategy that either compensates for autocrats' own lack of technological capacity, or that deflects blowback from high-stakes cyber operations. But less is known about how the hackers' presence relates to authoritarian stabilization and survival agendas. This prompts this article to ask: How does the devolution of cybersecurity functions to patriotic hackers influence regime stabilization and survival agendas? Observing patriotic hacking in Syria through work on authoritarian devolution, space and cybersecurity, the article argues that while there is much precedent for authoritarian power devolution, digital devolution has novel mechanisms and effects. This is because the internet enables regimes to consciously and instrumentally manipulate the process, thereby creating a sense of constantly shifting space between themselves and the hackers that facilitates new opportunities for authoritarian stabilization and survival. [ABSTRACT FROM AUTHOR]

The purpose of this study is to find the most effective and cost-efficient ways to improve the security and stability of electronic election and vote counting systems, as well as to identify the main targets of intruders and vulnerabilities of the system to prevent possible attacks. This paper describes the main types and of hacker attacks and their mechanism, assesses the consequences of damage to the structures of electronic elections in the United States, France, Germany, Northern Macedonia, and Indonesia. The vulnerabilities of electronic election systems were investigated and the technology for their detection during development and testing was provided. Recommendations were given on the implementation of preventive work to reduce the risks of hacker attacks. The study explained the motives of the crimes committed in the cyberspace of electronic election systems. [ABSTRACT FROM AUTHOR]

The widespread use of cloud computing has brought cloud security to the forefront. The cloud provider and the firm assume varying degrees of joint responsibility for cloud security with cloud service models including IaaS, PaaS, and SaaS, to defend the strategic hacker. This paper builds a game-theoretical model to study cloud security management, in which we find that ignoring the strategic hacker leads to the dislocation security investment decisions (overinvestment or underinvestment) for the provider and the firm in bilateral refund contracts (BRCs). The strategic hacker's attack effort is inverse U-shaped with cloud service models, leading to a free-riding problem between the provider and the firm. Furthermore, from the perspective of social welfare maximization, both the provider and the firm would underinvest or overinvest in cloud security. To solve the problem, we propose two new contract mechanisms: one is an internal effort-based contract, in which the provider oversees the firm internally and the compensation rate depends on the firm's effort once the breach occurs. The other is an external effort-based contract, in which the monitoring agency supervises the efforts of the provider and the firm. We compare the two new contracts with BRCs and obtain the optimal choice for principals. [ABSTRACT FROM AUTHOR]

In the era of the Internet, widely used web applications have become the target of hacker attacks because they contain a large amount of personal information. Among these vulnerabilities, stealing private data through cross-site scripting (XSS) attacks is one of the most commonly used attacks by hackers. Currently, deep learning-based XSS attack detection methods have good application prospects; however, they suffer from problems such as being prone to overfitting, a high false alarm rate, and low accuracy. To address these issues, we propose a multi-stage feature extraction and fusion model for XSS detection based on Random Forest feature enhancement. The model utilizes Random Forests to capture the intrinsic structure and patterns of the data by extracting leaf node indices as features, which are subsequently merged with the original data features to form a feature set with richer information content. Further feature extraction is conducted through three parallel channels. Channel I utilizes parallel one-dimensional convolutional layers (1D convolutional layers) with different convolutional kernel sizes to extract local features at different scales and perform multi-scale feature fusion; Channel II employs maximum one-dimensional pooling layers (max 1D pooling layers) of various sizes to extract key features from the data; and Channel III extracts global information bi-directionally using a Bi-Directional Long-Short Term Memory Network (Bi-LSTM) and incorporates a multi-head attention mechanism to enhance global features. Finally, effective classification and prediction of XSS are performed by fusing the features of the three channels. To test the effectiveness of the model, we conduct experiments on six datasets. We achieve an accuracy of 100% on the UNSW-NB15 dataset and 99.99% on the CICIDS2017 dataset, which is higher than that of the existing models. [ABSTRACT FROM AUTHOR]

Centralized storage and identity identification methods pose many risks, including hacker attacks, data misuse, and single points of failure. Additionally, existing centralized identity management methods face interoperability issues and rely on a single identity provider, leaving users without control over their identities. Therefore, this paper proposes a mechanism for identity identification and data sharing based on decentralized identifiers. The scheme utilizes blockchain technology to store the identifiers and data hashed on the chain to ensure permanent identity recognition and data integrity. Data is stored on InterPlanetary File System (IPFS) to avoid the risk of single points of failure and to enhance data persistence and availability. At the same time, compliance with World Wide Web Consortium (W3C) standards for decentralized identifiers and verifiable credentials increases the mechanism's scalability and interoperability. [ABSTRACT FROM AUTHOR]

CISOs in Southeast Asia should be on alert after the discovery that a suspected Chinese-based cyber espionage campaign that started last year is expanding its scope. The warning today comes [...]

Many enterprises rely on the YubiKey as a major part of their identity authentication strategy. It is one of the most popular and https://www.csoonline.com/article/571433/8-top-multifactor-authentication-products-and-how-to-choose-an-mfa-solution.html FIDO (fast identity online) hardware tokens [...]

Warnings went out this week to infosec leaders about two groups of Iranian threat actors attacking American and other organizations. The US Cybersecurity and Infrastructure Security Agency (CISA), the FBI [...]

State-sponsored Chinese hackers exploited a zero-day vulnerability in Versa Director, a software platform for managing SD-WAN infrastructure used by internet service providers (ISPs) and managed service providers (MSPs). The group, [...]

Bug bounty programs remain a crucial component of cybersecurity strategies in 2024, offering organisations the ability to draw in help from a diverse pool of cybersecurity professionals and researchers. The [...]

The February 2024 ransomware attack on Change Healthcare put the state of healthcare cybersecurity in the headlines and in front of the US Congress, with aftershocks from the seismic event [...]

A recent discovery has revealed a serious flaw in Microsoft’s Windows Update. Instead of protecting computers, it can be tricked into installing older, vulnerable operating system versions. This allows hackers [...]

We argue that the question, "Should psychology follow the methods and principles of the natural sciences?" is not one that should be answered by theoretical psychologists or metascientists; rather, we implore psychological researchers themselves to heed Wittgenstein's observation that a preoccupation with method and principles risks overlooking important conceptual issues, the clarification of which are necessarily antecedent to consideration of empirical activities. We examine potential conceptual problems that arise when psychological researchers attempt to follow natural science methods and principles without first considering the concepts that are relevant to their scientific pursuits. Drawing primarily from the works of Hacker, Lamiell, and Maraun, we argue against the dogmatic following of any methods or sets of principles. Instead, we posit that natural science methods and principles should be considered on a case-by-case basis after relevant psychological concepts have been carefully considered and empirical investigation has been deemed an appropriate path forward. [ABSTRACT FROM AUTHOR]

The object of this study is the process of detecting threats and vulnerabilities in hacker forums, which are a well-known source of potential dangers for Internet users. However, the problem of analyzing and classifying data from these forums is its complexity due to such features of the participants' language as specific slang, jargon, etc., which requires the use of modern tools of their processing. This paper explores the application of machine learning to devise an effective method for analyzing sentiment and trends in hacker forums to identify potential threats and vulnerabilities in cyberspace. All necessary stages of the process of detecting threats and vulnerabilities have been developed, ranging from data collection and preprocessing to the training of a model that is capable of processing “raw” unstructured data from hacker forums. The implementation of six popular machine learning algorithms, namely k Nearest Neighbors (kNN), Random Forest, Naive Bayes, Logistic Regression, Support Vector Machines (SVM), and Decision Tree algorithms have been studied with a view to determining their efficiency of threat and vulnerability detection and classification. The experiments have been conducted on real data (150,000 messengers). It has been determined that the Random Forest algorithm coped with the task the best (accuracy=0.89, recall=0.84, precision=0.91, F1-score=0.87 and ROC-AUC=0.89). The proposed tool based on machine learning not only collects data that poses a potential threat but also processes and classifies it according to the specified keywords. This allows detecting threats and vulnerabilities at a high speed. The results of the study make it possible to identify potential trends in threats and vulnerabilities. This will contribute to the improvement of cybersecurity systems and ensure more reliable protection of information resources. [ABSTRACT FROM AUTHOR]

The author investigates a range of international hacking groups collectively known as advanced persistent threats (APTs), which have conducted a concentrated number of cyber operations from four authoritarian states – China, Iran, Russia, and North Korea. The author collected data on 112 APTs that operated in 2003-2021 across the globe and analyzed their behavior and state affiliations to conclude that APTs' ties to the "big four" can be explained by the strategic goals of authoritarian states to supplement their military and economic power. The ties have also much to do with states possessing sufficient political capital at home to challenge existing norms of cyberspace behavior. Moreover, the big four boast a high degree of digital expertise and heavy investment into the superiority of cyber offense over defense. The author provides empirical support for the findings in a comparative case study of Chinese and Iranian cyber forces. [ABSTRACT FROM AUTHOR]