Hiding text in speech signal using K-means, LSB techniques and chaotic maps

In this paper, a new technique that hides a secret text inside a speech signal without any apparent noise is presented. The technique for encoding the secret text is through first scrambling the text using Chaotic Map, then encoding the scraped text using the Zaslavsky map, and finally hiding the text by breaking the speech signal into blocks and using only half of each block with the LSB, K-means algorithms. The measures (SNR, PSNR, Correlation, SSIM, and MSE) are used on various speech files (“.WAV”), and various secret texts. We observed that the suggested technique offers high security (SNR, PSNR, Correlation, and SSIM) of an encrypted text with low error (MSE). This indicates that the noise level in the speech signal is very low and the speech purity is high, so the suggested method is effective for embedding encrypted text into speech files

Simple, Fast, and Accurate Cybercrime Detection on E-Government with Elastic Stack SIEM

Increased public activity in cyberspace (Internet) during the Covid-19 pandemic has also increased cybercrime cases with various attack targets, including E-Government services. Cybercrime is hidden and occurs unnoticed in E-Government, so handling it is challenging for all government agencies. The characteristics of E-Government are unique and different from other service systems in general, requiring extra anticipation for the prevention and handling of cybercrime attack threats. This research proposes log and event data analysis to detect cybercrime in e-Government using System Information and Event Management (SIEM). The main contribution of this research is a simple, fast, and accurate cybercrime detection process in the e-Government environment by increasing the level of log and event data analysis with the SIEM approach. SIEM technology based on machine learning and big data is implemented with Elastic Stack. The implemented technique can be used as a mitigation program against cybercrime threats that often attack and target e-Government. With simple, accurate, and fast cybercrime detection, it is expected to improve e-Government security and increase public confidence in public services organized by government agencies

Nonintrusive tracing in the Internet

Intruders that log in through a series of machines when conducting an attack are hard to trace because of the complex architecture of the Internet. The thumbprinting method provides an efficient way of tracing such intruders by determining whether two connections are part of the same connection chain. Because many connections are transient and therefore short in length, choosing the best time interval to thumbprint over can be an issue. In this paper, we provide a way to shorten the time interval used for thumbprinting. We then study some special properties of the thumbprinting function. We also study another mechanism for tracing intruders in the Internet based on a timestamping approach, which passively monitors flows between source and destination pairs. Given a potentially suspicious source, we identify its true destination. We compute the error probability of our algorithm and show that its value decreases exponentially as the observation time increases. Our simulation results show that our approach performs well

The Challenge of Adapting the Rule of Law to Technological Developments

The problem in the digital era is that technology is developing rapidly without being accompanied by sufficient legal rules.  Meanwhile, laws and regulations are always lagging and cannot achieve legal flexibility in society. One of the results of technological development is electronic sports matches. This research reviews the concept of cyber law and the development of information and technology, especially in dealing with electronic matches. This article aims to validate the legal concept of adjusting to the rules of law in the electronic field that applies in Indonesia. The research method is juridical normative with a legislative and conceptual approach starting from the origin of ideas and doctrines developed into a legal study.   First, is threat of e-sports offences. e-sports offences including sexual harassment, gender, and drugs can be addressed by the applicable regulations, namely the Electronic Information and Transaction Law. When there are developments in information and technology, these can be based on "unwritten" rules or laws that apply in society.  Secondly,  the gambling industry has the opportunity to influence the sustainability of e-sports competitions. An indication of corruption in e-sports competitions can be bribery, and this requires law enforcement with the Information and Electronic Transactions Law or also by using unwritten rules.</p

Cyber-offenders versus traditional offenders: An empirical comparison

Bernasco, W. [Promotor]Ruiter, S. [Promotor]Gelder, J.-.L. van [Copromotor

Malware detection issues, future trends and challenges: a survey

This paper focuses on the challenges and issues of detecting malware in to-day's world where cyberattacks continue to grow in number and complexity. The paper reviews current trends and technologies in malware detection and the limitations of existing detection methods such as signature-based detection and heuristic analysis. The emergence of new types of malware, such as file-less malware, is also discussed, along with the need for real-time detection and response. The research methodology used in this paper is presented, which includes a literature review of recent papers on the topic, keyword searches, and analysis and representation methods used in each study. In this paper, the authors aim to address the key issues and challenges in detecting malware today, the current trends and technologies in malware detection, and the limitations of existing methods. They also explore emerging threats and trends in malware attacks and highlight future directions for research and development in the field. To achieve this, the authors use a research methodology that involves a literature review of recent papers related to the topic. They focus on detecting and analyzing methods, as well as representation and extraction methods used in each study. Finally, they classify the literature re-view, and through reading and criticism, highlight future trends and problems in the field of malware detection

Organizational practices as antecedents of the information security management performance

ABSTRACT: Purpose The purpose of this paper is to expand current knowledge about the security organizational practices and analyze its effects on the information security management performance. Design/methodology/approach Based on the literature review, the authors propose a research model together with hypotheses. The survey questionnaires were developed to collect data, which then validated the measurement model. The authors collected 111 responses from CEOs at manufacturing small- and medium-sized enterprises (SMEs) that had already implemented security policies. The hypothesized relationships were tested using the structural equation model approach with EQS 6.1 software. Findings Results validate that information security knowledge sharing, information security education and information security visibility, as well as security organizational practices, have a positive effect on the information security management performance. Research limitations/implications The consideration of organizational aspects of information security should be taken into account by academics, practitioners and policymakers in SMEs. Besides, the work helps validate novel constructs used in recent research (information security knowledge sharing and information security visibility). Practical implications The authors extend previous works by analyzing how security organizational practices affect the performance of information security. The results suggest that an improved performance of information security in the industrial SMEs requires innovative practices to foster knowledge sharing among employees. Originality/value The literature recognizes the need to develop empirical research on information security focused on SMEs. Besides the need to identify organizational practices that improve information security, this paper empirically investigates SMEs' organizational practices in the security of information and analyzes its effects on the performance of information security

Deteção de ataques de negação de serviços distribuídos na origem

From year to year new records of the amount of traffic in an attack are established, which demonstrate not only the constant presence of distributed denialof-service attacks, but also its evolution, demarcating itself from the other network threats. The increasing importance of resource availability alongside the security debate on network devices and infrastructures is continuous, given the preponderant role in both the home and corporate domains. In the face of the constant threat, the latest network security systems have been applying pattern recognition techniques to infer, detect, and react more quickly and assertively. This dissertation proposes methodologies to infer network activities patterns, based on their traffic: follows a behavior previously defined as normal, or if there are deviations that raise suspicions about the normality of the action in the network. It seems that the future of network defense systems continues in this direction, not only by increasing amount of traffic, but also by the diversity of actions, services and entities that reflect different patterns, thus contributing to the detection of anomalous activities on the network. The methodologies propose the collection of metadata, up to the transport layer of the osi model, which will then be processed by the machien learning algorithms in order to classify the underlying action. Intending to contribute beyond denial-of-service attacks and the network domain, the methodologies were described in a generic way, in order to be applied in other scenarios of greater or less complexity. The third chapter presents a proof of concept with attack vectors that marked the history and a few evaluation metrics that allows to compare the different classifiers as to their success rate, given the various activities in the network and inherent dynamics. The various tests show flexibility, speed and accuracy of the various classification algorithms, setting the bar between 90 and 99 percent.De ano para ano são estabelecidos novos recordes de quantidade de tráfego num ataque, que demonstram não só a presença constante de ataques de negação de serviço distribuídos, como também a sua evolução, demarcando-se das outras ameaças de rede. A crescente importância da disponibilidade de recursos a par do debate sobre a segurança nos dispositivos e infraestruturas de rede é contínuo, dado o papel preponderante tanto no dominio doméstico como no corporativo. Face à constante ameaça, os sistemas de segurança de rede mais recentes têm vindo a aplicar técnicas de reconhecimento de padrões para inferir, detetar e reagir de forma mais rápida e assertiva. Esta dissertação propõe metodologias para inferir padrões de atividades na rede, tendo por base o seu tráfego: se segue um comportamento previamente definido como normal, ou se existem desvios que levantam suspeitas sobre normalidade da ação na rede. Tudo indica que o futuro dos sistemas de defesa de rede continuará neste sentido, servindo-se não só do crescente aumento da quantidade de tráfego, como também da diversidade de ações, serviços e entidades que refletem padrões distintos contribuindo assim para a deteção de atividades anómalas na rede. As metodologias propõem a recolha de metadados, até á camada de transporte, que seguidamente serão processados pelos algoritmos de aprendizagem automática com o objectivo de classificar a ação subjacente. Pretendendo que o contributo fosse além dos ataques de negação de serviço e do dominio de rede, as metodologias foram descritas de forma tendencialmente genérica, de forma a serem aplicadas noutros cenários de maior ou menos complexidade. No quarto capítulo é apresentada uma prova de conceito com vetores de ataques que marcaram a história e, algumas métricas de avaliação que permitem comparar os diferentes classificadores quanto à sua taxa de sucesso, face às várias atividades na rede e inerentes dinâmicas. Os vários testes mostram flexibilidade, rapidez e precisão dos vários algoritmos de classificação, estabelecendo a fasquia entre os 90 e os 99 por cento.Mestrado em Engenharia de Computadores e Telemátic