Network intrusion detection systems need to be updated due to the rise in cyber threats. In order to improve detection accuracy, this research presents a strong strategy that makes use of a stacked ensemble method, wh...Network intrusion detection systems need to be updated due to the rise in cyber threats. In order to improve detection accuracy, this research presents a strong strategy that makes use of a stacked ensemble method, which combines the advantages of several machine learning models. The ensemble is made up of various base models, such as Decision Trees, K-Nearest Neighbors (KNN), Multi-Layer Perceptrons (MLP), and Naive Bayes, each of which offers a distinct perspective on the properties of the data. The research adheres to a methodical workflow that begins with thorough data preprocessing to guarantee the accuracy and applicability of the data. In order to extract useful attributes from network traffic data—which are essential for efficient model training—feature engineering is used. The ensemble approach combines these models by training a Logistic Regression model meta-learner on base model predictions. In addition to increasing prediction accuracy, this tiered approach helps get around the drawbacks that come with using individual models. High accuracy, precision, and recall are shown in the model’s evaluation of a network intrusion dataset, indicating the model’s efficacy in identifying malicious activity. Cross-validation is used to make sure the models are reliable and well-generalized to new, untested data. In addition to advancing cybersecurity, the research establishes a foundation for the implementation of flexible and scalable intrusion detection systems. This hybrid, stacked ensemble model has a lot of potential for improving cyberattack prevention, lowering the likelihood of cyberattacks, and offering a scalable solution that can be adjusted to meet new threats and technological advancements.展开更多
Cryptography as a service is becoming extremely popular. It eases the way companies deal with securing their information without having to worry about their customer’s information being accessed by someone who should...Cryptography as a service is becoming extremely popular. It eases the way companies deal with securing their information without having to worry about their customer’s information being accessed by someone who should not have access to it. In this overview, we will be taking a closer look at Cryptography as a Service. The ground we will be examining is the effectiveness of it for mobile/wireless and desktop computing. Since we will be looking at something that operates as a service, we will need to first cover the application program interface (API) basics [1] or standard software as a service (SaaS) [2]. Next, what exactly cryptography as a service means for each of the aforementioned platforms. Lastly, other possible solutions and how they compare to CaaS. For the purpose of this review, we will be looking at CaaS in a cloud environment since typical SaaS is used that way. Subsequently most cloud environments utilize a UNIX based operating system or similar solution, which will be the target environment for the purpose of this paper. Popular algorithms that are used in CaaS will be the final part that will be examined on the grounds of how they perform, level of security offered, and usability in CaaS. Upon reading this paper the reader will have a better understanding of how exactly CaaS operates and what it has to offer for mobile, desktop, and wireless users in the present and future.展开更多
The advent of technology brought forth a myriad of developments that have streamlined the manner through which people operate. With the growing need to be at the forefront of communication and information, people have...The advent of technology brought forth a myriad of developments that have streamlined the manner through which people operate. With the growing need to be at the forefront of communication and information, people have resorted to the use of mobile phones with a great percentile preferring android oriented systems. Similarly, the systems are susceptible to the various threats posed by technology with due summations showing that security flaws and unauthorized access to sensitive data pose a huge threat to the overarching efficacy of the android systems. The research presented lays a primal focus on how users can improve intrinsic android features through the use of Google services, rooting, custom kernels and ROM techniques. The research also focused on how Android security features can be improved when using or installing applications. Results indicate that the rooting process is the most conclusive and safest scheme. Summations drawn are indicative of the fact that system security is a moot research topic that requires further research into how it can be improved.展开更多
文摘Network intrusion detection systems need to be updated due to the rise in cyber threats. In order to improve detection accuracy, this research presents a strong strategy that makes use of a stacked ensemble method, which combines the advantages of several machine learning models. The ensemble is made up of various base models, such as Decision Trees, K-Nearest Neighbors (KNN), Multi-Layer Perceptrons (MLP), and Naive Bayes, each of which offers a distinct perspective on the properties of the data. The research adheres to a methodical workflow that begins with thorough data preprocessing to guarantee the accuracy and applicability of the data. In order to extract useful attributes from network traffic data—which are essential for efficient model training—feature engineering is used. The ensemble approach combines these models by training a Logistic Regression model meta-learner on base model predictions. In addition to increasing prediction accuracy, this tiered approach helps get around the drawbacks that come with using individual models. High accuracy, precision, and recall are shown in the model’s evaluation of a network intrusion dataset, indicating the model’s efficacy in identifying malicious activity. Cross-validation is used to make sure the models are reliable and well-generalized to new, untested data. In addition to advancing cybersecurity, the research establishes a foundation for the implementation of flexible and scalable intrusion detection systems. This hybrid, stacked ensemble model has a lot of potential for improving cyberattack prevention, lowering the likelihood of cyberattacks, and offering a scalable solution that can be adjusted to meet new threats and technological advancements.
文摘Cryptography as a service is becoming extremely popular. It eases the way companies deal with securing their information without having to worry about their customer’s information being accessed by someone who should not have access to it. In this overview, we will be taking a closer look at Cryptography as a Service. The ground we will be examining is the effectiveness of it for mobile/wireless and desktop computing. Since we will be looking at something that operates as a service, we will need to first cover the application program interface (API) basics [1] or standard software as a service (SaaS) [2]. Next, what exactly cryptography as a service means for each of the aforementioned platforms. Lastly, other possible solutions and how they compare to CaaS. For the purpose of this review, we will be looking at CaaS in a cloud environment since typical SaaS is used that way. Subsequently most cloud environments utilize a UNIX based operating system or similar solution, which will be the target environment for the purpose of this paper. Popular algorithms that are used in CaaS will be the final part that will be examined on the grounds of how they perform, level of security offered, and usability in CaaS. Upon reading this paper the reader will have a better understanding of how exactly CaaS operates and what it has to offer for mobile, desktop, and wireless users in the present and future.
文摘The advent of technology brought forth a myriad of developments that have streamlined the manner through which people operate. With the growing need to be at the forefront of communication and information, people have resorted to the use of mobile phones with a great percentile preferring android oriented systems. Similarly, the systems are susceptible to the various threats posed by technology with due summations showing that security flaws and unauthorized access to sensitive data pose a huge threat to the overarching efficacy of the android systems. The research presented lays a primal focus on how users can improve intrinsic android features through the use of Google services, rooting, custom kernels and ROM techniques. The research also focused on how Android security features can be improved when using or installing applications. Results indicate that the rooting process is the most conclusive and safest scheme. Summations drawn are indicative of the fact that system security is a moot research topic that requires further research into how it can be improved.
