Data-driven cybersecurity incident prediction: A survey

N Sun, J Zhang, P Rimba, S Gao… - … surveys & tutorials, 2018 - ieeexplore.ieee.org
Driven by the increasing scale and high profile cybersecurity incidents related public data,
recent years we have witnessed a paradigm shift in understanding and defending against …

Shallow and deep networks intrusion detection system: A taxonomy and survey

E Hodo, X Bellekens, A Hamilton, C Tachtatzis… - ar** ransomware attacks on user data
N Scaife, H Carter, P Traynor… - 2016 IEEE 36th …, 2016 - ieeexplore.ieee.org
Ransomware is a growing threat that encrypts auser's files and holds the decryption key until
a ransom ispaid by the victim. This type of malware is responsible fortens of millions of …

Evolving deep learning architectures for network intrusion detection using a double PSO metaheuristic

W Elmasry, A Akbulut, AH Zaim - Computer Networks, 2020 - Elsevier
The prevention of intrusion is deemed to be a cornerstone of network security. Although
excessive work has been introduced on network intrusion detection in the last decade …

How the Great Firewall of China detects and blocks fully encrypted traffic

M Wu, J Sippe, D Sivakumar, J Burg… - 32nd USENIX Security …, 2023 - usenix.org
One of the cornerstones in censorship circumvention is fully encrypted protocols, which
encrypt every byte of the payload in an attempt to “look like nothing”. In early November …

A survey on systems security metrics

M Pendleton, R Garcia-Lebron, JH Cho… - ACM Computing Surveys …, 2016 - dl.acm.org
Security metrics have received significant attention. However, they have not been
systematically explored based on the understanding of attack-defense interactions, which …

Outside the closed world: On using machine learning for network intrusion detection

R Sommer, V Paxson - 2010 IEEE symposium on security and …, 2010 - ieeexplore.ieee.org
In network intrusion detection research, one popular strategy for finding attacks is monitoring
a network's activity for anomalies: deviations from profiles of normality previously learned …

Intrusion detection using naive Bayes classifier with feature reduction

S Mukherjee, N Sharma - Procedia Technology, 2012 - Elsevier
Intrusion detection is the process of monitoring and analyzing the events occurring in a
computer system in order to detect signs of security problems. Today most of the intrusion …

Empirical evaluation and new design for fighting evolving twitter spammers

C Yang, R Harkreader, G Gu - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
To date, as one of the most popular online social networks (OSNs), Twitter is paying its dues
as more and more spammers set their sights on this microblogging site. Twitter spammers …

Testing intrusion detection systems: a critique of the 1998 and 1999 darpa intrusion detection system evaluations as performed by lincoln laboratory

J McHugh - ACM Transactions on Information and System Security …, 2000 - dl.acm.org
In 1998 and again in 1999, the Lincoln Laboratory of MIT conducted a comparative
evaluation of intrusion detection systems (IDSs) developed under DARPA funding. While …