Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media
, 2017 Social media is often viewed as a sensor into various societal events such as disease outbreaks, protests, and elections. We describe the use of social media as a crowdsourced sensor to gain insight into ongoing cyber-attacks.
Becker Hila +14 more
core +1 more source
DoS and DDoS Attack Detection in IoT Infrastructure using Xception Model with Explainability
Proceedings of the International Florida Artificial Intelligence Research Society ConferenceThe denial of service (DoS) and distributed denial of service (DDoS) attacks are considered the most frequent attacks targeting the Internet of Things (IoT) network infrastructure globally.
Nelly Elsayed +2 more
doaj +1 more source
HF-Blocker: Detection of Distributed Denial of Service Attacks Based On Botnets [PDF]
Journal of Advances in Computer Engineering and Technology, 2015 —Today, botnets have become a serious threat to enterprise networks. By creation of network of bots, they launch several attacks, distributed denial of service attacks (DDoS) on networks is a sample of such attacks.
Bita Amirshahi, Ali Ahangari
doaj
An improved agent-based adaptive protection model for distributed denial of service flooding attack and flash crowd flooding traffic [PDF]
, 2019 Recently, a serious disturbance for network security could be a Distributed Denial of Service (DDoS) attack. The advent of technological era has also brought along the threat of DDoS attacks for a variety of services and applications that use the ...
Ahmed Khalaf, Bashar
core +1 more source
An Unsupervised Generative Adversarial Network System to Detect DDoS Attacks in SDN
IEEE AccessNetwork management is a crucial task to maintain modern systems and applications running. Some applications have become vital for society and are expected to have zero downtime.
Daniel M. Brandao Lent +5 more
doaj +1 more source
DDoS Attacks with Randomized Traffic Innovation: Botnet Identification Challenges and Strategies
, 2016 Distributed Denial-of-Service (DDoS) attacks are usually launched through the $botnet$, an "army" of compromised nodes hidden in the network. Inferential tools for DDoS mitigation should accordingly enable an early and reliable discrimination of the ...
Di Mauro, Mario +2 more
core +1 more source
Machine Learning DDoS Detection for Consumer Internet of Things Devices
, 2018 An increasing number of Internet of Things (IoT) devices are connecting to the Internet, yet many of these devices are fundamentally insecure, exposing the Internet to a variety of attacks. Botnets such as Mirai have used insecure consumer IoT devices to
Apthorpe, Noah +2 more
core +1 more source
A Feature Analysis Based Identifying Scheme Using GBDT for DDoS with Multiple Attack Vectors
Applied Sciences, 2019 In recent years, distributed denial of service (DDoS) attacks have increasingly shown the trend of multiattack vector composites, which has significantly improved the concealment and success rate of DDoS attacks.
Jian Zhang, Qidi Liang, Rui Jiang, Xi Li
doaj +1 more source
BARTD: Bio-inspired anomaly based real time detection of under rated App-DDoS attack on web
Journal of King Saud University: Computer and Information Sciences, 2020 The internet network is mostly victimized to the Distributed Denial of Service (DDOS) Attack, which is one that intentionally occupies the computing resources and bandwidth in order to deny that services to potential users.
K. Munivara Prasad +2 more
doaj +1 more source
Babylonian Journal of NetworkingDistributed denial-of-service assaults, often known as DDoS attacks, pose a significant danger to the stability and security of the internet, particularly in light of the increasing number of devices that are linked to the internet. Intelligent detection
Sara salman Qasim, Sarah Mohammed Nsaif
semanticscholar +1 more source