Abstract: The use of information is increasing everyday with the advent of more applications of social media platform that utilizes millions of data per second globally. These data include sensitive information such as trade secret, privacy and security issues. Most importantly, some organizations, both private and public use this medium to disseminate messages among colleagues especially in Africa. Also, the emergence of smart-phone has accelerated more problems with having little knowledge on security matters. Furthermore, cybercrimes use this opportunity to launch more cyber-attacks by invading people's privacy and steal sensitive information such as credit card details, online shopping information of customers, online ticket booking. Government official's details have being hacked or eavesdropped over the years when using their smart-phones for communications. Emails of prominent people have also being hacked or disrupted, causing huge financial lose. These attacks are on the increase and therefore, countermeasures are vital to combat cybercrimes and cyber warfare in this hostile cyberspace. The research study the sociological and technological issues that impact cybercrime and cyber-security within the boundary of Sierra Leone, as a national security threats. The study provides answers to the issues highlighted in the research. An extensive survey was conducted, which highlighted the need for a robust and proactive approach to mitigate the frequency on which cybercrime is carried out in the country and its neighbors. Data amassed were subjected to relevant questionnaires issued and collected from the respondents in the state security apparatus, based on the conventional approaches or methods of investing crime in Sierra Leone. The research shows that the state has weak laws regarding cybercrime and cyber security, and most people working in these departments or agencies have little knowledge in cyber security and cybercrime. In fact, most are on political appointment rather than on merit-base that supposed to be the right procedure that will accelerate and achieve the goals of these institutions.Abstract: The use of information is increasing everyday with the advent of more applications of social media platform that utilizes millions of data per second globally. These data include sensitive information such as trade secret, privacy and security issues. Most importantly, some organizations, both private and public use this medium to disseminate messa...Show More
Abstract: Many available signals in the real world are usually weak with impulse noises and/or outliers, and we also need to have higher estimation precision in applications. Our focus of attention is pretty much on integrating robustness and accuracy under lower signal to noise ratio (SNR) with impulse noises. Although traditional fractional adaptive time delay estimation (TDE) methods have higher precision, the results of estimation are unreasonable when the signals contain some impulse noises. While, most proposed robust algorithms later can work well mainly with high SNR. In this paper, considering the practical problem in equipment fault acoustic localization based on TDE methods, an improved robust fractional adaptive time delay estimation method is addressed facing lower SNR conditions. First, the impulse noises are modeled as Alpha stable distribution, and the integer part of TDE is getting by using covariate correlation approach. Then, the integer estimation value is used as initial parameter value of time delay. Covariant sequence is the input of time delay estimator. Next, fractional TDE value is adaptive obtained by iteration under minimum average p norm criterion. Covariant sequence weakens irrelevant noises, meanwhile preserves time delay information between original sequences. Computer simulations and comparative experiments show that improved method has better estimation results. This method is robust and higher precision, and especially under impulse environment and low SNR conditions.Abstract: Many available signals in the real world are usually weak with impulse noises and/or outliers, and we also need to have higher estimation precision in applications. Our focus of attention is pretty much on integrating robustness and accuracy under lower signal to noise ratio (SNR) with impulse noises. Although traditional fractional adaptive time d...Show More