Results 11 to 20 of about 76,542 (243)
Rusty clusters?: dusting an IPv6 research foundation [PDF]
ACM/SIGCOMM Internet Measurement Conference, 2022 The long-running IPv6 Hitlist service is an important foundation for IPv6 measurement studies. It helps to overcome infeasible, complete address space scans by collecting valuable, unbiased IPv6 address candidates and regularly testing their ...
Johannes Zirngibl +4 more
semanticscholar +1 more source
One bad apple can spoil your IPv6 privacy [PDF]
Computer communication review, 2022 IPv6 is being more and more adopted, in part to facilitate the millions of smart devices that have already been installed at home. Unfortunately, we find that the privacy of a substantial fraction of end-users is still at risk, despite the efforts by ...
Said Jawad Saidi +2 more
semanticscholar +1 more source
Applied Sciences, 2022 The increasing incidence of distributed denial-of-service (DDoS) attacks has made software-defined networking (SDN) more vulnerable to the depletion of controller resources.
Mohammad Adnan Aladaileh +5 more
doaj +1 more source
IPvSeeYou: Exploiting Leaked Identifiers in IPv6 for Street-Level Geolocation [PDF]
IEEE Symposium on Security and Privacy, 2022 We present IPvSeeYou, a privacy attack that permits a remote and unprivileged adversary to physically geolocate many residential IPv6 hosts and networks with street-level precision. The crux of our method involves: 1) remotely discovering wide area (WAN)
Erik C. Rye, Robert Beverly
semanticscholar +1 more source
SiamHAN: IPv6 Address Correlation Attacks on TLS Encrypted Traffic via Siamese Heterogeneous Graph Attention Network [PDF]
USENIX Security Symposium, 2022 Unlike IPv4 addresses, which are typically masked by a NAT, IPv6 addresses could easily be correlated with user activity, endangering their privacy. Mitigations to address this privacy concern have been deployed, making existing approaches for address-to-
Tianyu Cui +5 more
semanticscholar +1 more source
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
Applied Sciences, 2023 Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for ...
Tariq Emad Ali +2 more
doaj +1 more source
Illuminating large-scale IPv6 scanning in the internet [PDF]
ACM/SIGCOMM Internet Measurement Conference, 2022 While scans of the IPv4 space are ubiquitous, today little is known about scanning activity in the IPv6 Internet. In this work, we present a longitudinal and detailed empirical study on large-scale IPv6 scanning behavior in the Internet, based on ...
P. Richter, Oliver Gasser, A. Berger
semanticscholar +1 more source
Eth-PSD: A Machine Learning-Based Phishing Scam Detection Approach in Ethereum
IEEE Access, 2022 Recently, the rapid flourish of blockchain technology in the financial field has attracted many cybercriminals’ attention to launching blockchain-based attacks such as ponzi schemes, scam wallets, and phishing scams.
Arkan Hammoodi Hasan Kabla +3 more
doaj +1 more source
Trigonometric words ranking model for spam message classification
IET Networks, EarlyView., 2022 Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi +7 more
wiley +1 more source
Uncovering the Cloak: A Systematic Review of Techniques Used to Conceal Phishing Websites
IEEE Access, 2023 Phishing represents a cybersecurity attack strategy commonly employed by cybercriminals to unlawfully acquire sensitive user information, including passwords, account details, credit card data, and other personally identifiable information.
Wenhao Li +3 more
doaj +1 more source