Detecting and preventing cyber insider threats: A survey

L Liu, O De Vel, QL Han, J Zhang… - … Surveys & Tutorials, 2018‏ - ieeexplore.ieee.org
Information communications technology systems are facing an increasing number of cyber
security threats, the majority of which are originated by insiders. As insiders reside behind …

[HTML][HTML] Intrusion detection system in cloud environment: Literature survey & future research directions

S Lata, D Singh - International Journal of Information Management Data …, 2022‏ - Elsevier
The cloud provides infrastructure, applications, and storage services to users that need to be
protected by some policies or procedures. Hence, security in the cloud is to protect user data …

Deep learning approach for intelligent intrusion detection system

R Vinayakumar, M Alazab, KP Soman… - IEEE …, 2019‏ - ieeexplore.ieee.org
Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …

In-vehicle network intrusion detection using deep convolutional neural network

HM Song, J Woo, HK Kim - Vehicular Communications, 2020‏ - Elsevier
The implementation of electronics in modern vehicles has resulted in an increase in attacks
targeting in-vehicle networks; thus, attack detection models have caught the attention of the …

[ספר][B] Data mining: the textbook

CC Aggarwal - 2015‏ - Springer
This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Cryptolock (and drop it): stop** 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 …

Mamadroid: Detecting android malware by building markov chains of behavioral models (extended version)

L Onwuzurike, E Mariconti, P Andriotis… - ACM Transactions on …, 2019‏ - dl.acm.org
As Android has become increasingly popular, so has malware targeting it, thus motivating
the research community to propose different detection techniques. However, the constant …

Nodoze: Combatting threat alert fatigue with automated provenance triage

WU Hassan, S Guo, D Li, Z Chen, K Jee, Z Li… - network and distributed …, 2019‏ - par.nsf.gov
Large enterprises are increasingly relying on threat detection softwares (eg, Intrusion
Detection Systems) to allow them to spot suspicious activities. These softwares generate …

[ספר][B] An introduction to outlier analysis

CC Aggarwal, CC Aggarwal - 2017‏ - Springer
Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …

Mamadroid: Detecting android malware by building markov chains of behavioral models

E Mariconti, L Onwuzurike, P Andriotis… - arxiv preprint arxiv …, 2016‏ - arxiv.org
The rise in popularity of the Android platform has resulted in an explosion of malware threats
targeting it. As both Android malware and the operating system itself constantly evolve, it is …