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Topic Review
DriveSpace
DriveSpace (initially known as DoubleSpace) is a disk compression utility supplied with MS-DOS starting from version 6.0 in 1993 and ending in 2000 with the release of Windows Me. The purpose of DriveSpace is to increase the amount of data the user could store on disks by transparently compressing and decompressing data on-the-fly. It is primarily intended for use with hard drives, but use for floppy disks is also supported. This feature was removed in Windows XP and later.
  • 410
  • 16 Nov 2022
Topic Review
Strengthening Privacy Security in Biomedical Microelectromechanical Systems
Biomedical Microelectromechanical Systems (BioMEMS) serve as a crucial catalyst in enhancing internet of things (IoT) communication security and safeguarding smart healthcare systems. Situated at the nexus of advanced technology and healthcare, BioMEMS are instrumental in pioneering personalized diagnostics, monitoring, and therapeutic applications. Nonetheless, this integration brings forth a complex array of security and privacy challenges intrinsic to IoT communications within smart healthcare ecosystems, demanding comprehensive scrutiny. 
  • 410
  • 13 Nov 2023
Topic Review
A Proactive Protection by Computational Intelligence Methods
A combination of computational intelligence methods: identifying anomalies in network traffic by evaluating its self-similarity, detecting and classifying cyberattacks in anomalies, and taking effective protection measures using Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) cells.
  • 409
  • 25 Oct 2022
Topic Review
Octopussy
Octopussy, also known as 8Pussy, is a free and open-source computer-software which monitors systems, by constantly analyzing the syslog data they generate and transmit to such a central Octopussy server (thus often called a SIEM solution). Therefore, software like Octopussy plays an important role in maintaining an information security management system within ISO/IEC 27001-compliant environments. Octopussy has the ability to monitor any device that supports the syslog protocol, such as servers, routers, switches, firewalls, load balancers, and its important applications and services. The main purpose of the software is to alert its administrators and users to different kinds of events, like system outages, attacks on systems or errors in applications. However, unlike Nagios or Icinga, Octopussy is not a state-checker and therefore problems cannot be resolved within the application. The software also makes no prescription whatsoever on which messages must be/must not be analyzed. As such, Octopussy can be seen as less powerful than other popular commercial software in the same category (event monitoring and log analysis). Octopussy is compatible with many Linux system distributions like Debian, Ubuntu, OpenSUSE, CentOS, RHEL and even meta-distributions as Gentoo or Arch Linux. Although Octopussy was originally designed to run on Linux, it could be ported to other Unix variants like FreeBSD with minimal effort. Octopussy has extensive report generating features and also various interfaces to other software, like e.g. NSCA (Nagios), Jabber/XMPP and Zabbix. With the help of software like Snare even Windows EventLogs can be processed. Octopussy is licensed under the terms of the GNU General Public License.
  • 409
  • 11 Nov 2022
Topic Review
Secure Access Service Edge
Secure Access Service Edge (SASE) is a term coined by analyst firm Gartner, SASE simplifies wide-area networking (WAN) and security by delivering both as a cloud service directly to the source of connection (user, device, branch office, IoT device, edge computing location) rather than the enterprise data center. Security is based on identity, real-time context and enterprise security and compliance policies. An identity may be attached to anything from a person/user to a device, branch office, cloud service, application, IoT system, or an edge computing location. SASE is meant to be a simplified WAN and security solution for a mobile, global workplace that relies on cloud applications and data. The common solution of backhauling all WAN traffic over long distances to one or a few corporate data centers for security functions adds network latency when users and their cloud applications are globally dispersed, rather than on-premises. By targeting services to the edge at the connection source, SASE eliminates the latency caused by backhauling.
  • 409
  • 23 Nov 2022
Topic Review
Remote Sensing Object Detection
Remote sensing image object detection holds signifificant research value in resources and the environment. Nevertheless, complex background information and considerable size differences between objects in remote sensing images make it challenging.
  • 409
  • 04 Sep 2023
Topic Review
Intrusion Detection System in IoT Wi-Fi Networks
The Internet of Things (IoT) is a network of billions of interconnected devices embedded with sensors, software, and communication technologies. Wi-Fi is one of the main wireless communication technologies essential for establishing connections and facilitating communication in IoT environments. However, IoT networks are facing major security challenges due to various vulnerabilities, including de-authentication and disassociation DoS attacks that exploit IoT Wi-Fi network vulnerabilities. Traditional intrusion detection systems (IDSs) improved their cyberattack detection capabilities by adapting machine learning approaches, especially deep learning (DL). However, DL-based IDSs still need improvements in their accuracy, efficiency, and scalability to properly address the security challenges including de-authentication and disassociation DoS attacks tailored to suit IoT environments. The main purpose of this research was to overcome these limitations by designing a transfer learning (TL) and convolutional neural network (CNN)-based IDS for deauthentication and disassociation DoS attack detection with better overall accuracy compared to various current solutions. 
  • 409
  • 15 Oct 2023
Topic Review
Decision Support Systems in Forestry and Tree-Planting Practices
Using deep neural networks (DNNs), a decision support system (DSS) can be trained to learn from a large dataset of tree data, including information about tree species, climate, soil conditions, and other factors that influence tree growth and survival. This is because the use of neural networks was proposed three decades ago to solve forest management problems by integrating forest knowledge with artificial intelligence (AI). AI greatly benefits sustainability and the preservation of ecosystem values, as increasing disruptions in a changing world can only be managed beyond human intelligence. Furthermore, despite the various DSSs and AI systems used, the appointment of appropriate project managers is crucial to the execution and subsequent success of a project.
  • 409
  • 04 Mar 2024
Topic Review
AI-Based Prediction of Dementia
Dementia, the most severe expression of cognitive impairment, is among the main causes of disability in older adults and currently effects over 55 million individuals. Dementia prevention is a global public health priority, and recent ones have shown that dementia risk can be reduced through non-pharmacological interventions targeting different lifestyle areas. The FINnish GERiatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) has shown a positive effect on cognition in older adults at risk of dementia, through a 2-year multidomain intervention targeting lifestyle and vascular risk factors. The LETHE project builds on these findings and will provide a digital-enabled FINGER intervention model for delaying or preventing the onset of cognitive decline. An individualised ICT-based multidomain, preventive lifestyle intervention program will be implemented utilising behaviour and intervention data through passive and active data collection. Artificial intelligence and machine learning methods will be used for data-driven risk factor prediction models. An initial model based large multinational datasets will be validated and integrated in a 18-month trial integrating digital biomarkers, to further improve the model. Furthermore, the LETHE project will investigate the concept of federated learning to, on the one hand, protect the privacy of the health and behaviour data, and, on the other hand, to provide the opportunity to enhance the data model easily by integrating additional clinical centres.
  • 408
  • 10 Jun 2022
Topic Review
Attack Graph Based on Vulnerability Correlation
As network technology has advanced, and as larger and larger quantities of data are being collected, networks are becoming increasingly complex. Various vulnerabilities are being identified in such networks, and related attacks are continuously occurring. To solve these problems and improve the overall quality of network security, a network risk scoring technique using attack graphs and vulnerability information must be used. This technology calculates the degree of risk by collecting information and related vulnerabilities in the nodes and the edges existing in the network-based attack graph, and then determining the degree of risk in a specific network location or the degree of risk occurring when a specific route is passed within the network.
  • 408
  • 25 Jul 2022
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