Results 71 to 80 of about 1,097,826 (233)
Detection of randomized bot command and control traffic on an end-point host
Bots are malicious software entities that unobtrusively infect machines and silently engage in activities ranging from data stealing to cyber warfare. Most recent bot detection methods rely on regularity of bot command and control (C&C) traffic for bot ...
B. Soniya, M. Wilscy
doaj +1 more source
Network Connectivity Graph for Malicious Traffic Dissection [PDF]
Malware is a major threat to security and privacy of network users. A huge variety of malware typically spreads over the Internet, evolving every day, and challenging the research community and security practitioners to improve the effectiveness of countermeasures.
BOCCHI, ENRICO +7 more
openaire +2 more sources
Multiterminal High‐Voltage Direct Current Projects: A Comprehensive Assessment and Future Prospects
ABSTRACT Multiterminal high‐voltage direct current (MT‐HVDC) systems are an important part of modern power systems, addressing the need for bulk power delivery and efficient renewable energy integration. This paper provides a comprehensive overview of recent advances in MT‐HVDC technology, including launched projects and ongoing initiatives.
Mohammad Hossein Mousavi +3 more
wiley +1 more source
Guest Editorial: Unfolding the potential of 5G technologies for future wireless networks
Abstract With the rapid advancements in mobile Internet and smartphones, data traffic in current mobile communication systems is growing exponentially. At the same time, demands for lower latency, increased robustness, and higher energy efficiency are becoming more stringent.
Gwanggil Jeon +3 more
wiley +1 more source
Network security relies on effective and accurate malicious traffic detection, which is increasingly important for edge devices. As computing resources are distributed across many devices, detecting malicious traffic at the edge becomes crucial ...
Fuhao Li, Ifiok Udoidiok, Jielun Zhang
doaj +1 more source
An LSTM-Based Deep Learning Approach for Classifying Malicious Traffic at the Packet Level
Recently, deep learning has been successfully applied to network security assessments and intrusion detection systems (IDSs) with various breakthroughs such as using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) to classify ...
Ren-Hung Hwang +3 more
doaj +1 more source
IoT malicious traffic identification using wrapper-based feature selection mechanisms
© 2020 Elsevier Ltd Machine Learning (ML) plays very significant role in the Internet of Things (IoT) cybersecurity for malicious and intrusion traffic identification. In other words, ML algorithms are widely applied for IoT traffic identification in IoT
M. Shafiq +4 more
semanticscholar +1 more source
ABSTRACT This article examines how the Swedish child welfare services (CWSs) are described in Arabic‐speaking social media, with a focus on the ‘LVU campaign.’ The material consists of Facebook and YouTube posts and comments about the Swedish CWSs' actions in child mistreatment cases involving migrant families.
Dana Sofi, Jonas Stier, Emmie Wahlström
wiley +1 more source
Analysis of Encrypted Malicious Traffic
In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation and communication. Due to the volume of legitimate encrypted data, encrypted malicious traffic resembles benign traffic.
openaire +2 more sources
ABSTRACT For decades, children have been taught about ‘stranger danger’. Fear of the stranger has been associated with overly cautious parenting strategies, and the curtailing of freedoms as children transition to adolescents. This article aims to examine the extent to which parents consider this issue of stranger danger in their decisions to grant ...
Craig Collie
wiley +1 more source

