Multilayer framework for botnet detection using machine learning algorithms
A botnet is a malware program that a hacker remotely controls called a botmaster. Botnet
can perform massive cyber-attacks such as DDOS, SPAM, click-fraud, information, and …
can perform massive cyber-attacks such as DDOS, SPAM, click-fraud, information, and …
Protecting iots from mirai botnet attacks using blockchains
Z Ahmed, SM Danish, HK Qureshi… - 2019 IEEE 24th …, 2019 - ieeexplore.ieee.org
The exponential growth of Internet of Things (IoT) devices with limited computing resources
and poor security configurations make them vulnerable to different cyber-attacks. Mirai …
and poor security configurations make them vulnerable to different cyber-attacks. Mirai …
[HTML][HTML] IoTSecSim: A framework for modelling and simulation of security in Internet of things
The proliferation of the Internet of Things (IoT) devices has provided attackers with
tremendous opportunities to launch various cyber-attacks. It has been challenging to …
tremendous opportunities to launch various cyber-attacks. It has been challenging to …
Optimizing symbolic execution for malware behavior classification
Increasingly software correctness, reliability, and security is being analyzed using tools that
combine various formal and heuristic approaches. Often such analysis becomes expensive …
combine various formal and heuristic approaches. Often such analysis becomes expensive …
Malware analysis with symbolic execution and graph kernel
CH Bertrand Van Ouytsel, A Legay - Nordic Conference on Secure IT …, 2022 - Springer
Malware analysis techniques are divided into static and dynamic analysis. Both techniques
can be bypassed by circumvention techniques such as obfuscation. In a series of works, the …
can be bypassed by circumvention techniques such as obfuscation. In a series of works, the …
Analysis of attacker behavior in compromised hosts during command and control
F Sadique, S Sengupta - ICC 2021-IEEE International …, 2021 - ieeexplore.ieee.org
Traditional reactive approach of blacklisting botnets fails to adapt to the rapidly evolving
landscape of cyberattacks. An automated and proactive approach to detect and block botnet …
landscape of cyberattacks. An automated and proactive approach to detect and block botnet …
PORTFILER: port-level network profiling for self-propagating malware detection
Recent self-propagating malware (SPM) campaigns compromised hundred of thousands of
victim machines on the Internet. It is challenging to detect these attacks in their early stages …
victim machines on the Internet. It is challenging to detect these attacks in their early stages …
Resilient Machine Learning Methods for Cyber-Attack Detection
T Ongun - 2023 - search.proquest.com
The cyber threat landscape has evolved tremendously in recent years, with new threat
variants emerging daily, and large-scale coordinated campaigns becoming more prevalent …
variants emerging daily, and large-scale coordinated campaigns becoming more prevalent …
Ddos attack simulation and machine learning-based detection approach in internet of things experimental environment
H Chen, C Meng, J Chen - … of Information Security and Privacy (IJISP), 2021 - igi-global.com
Aiming at the problem of DDoS attack detection in internet of things (IoT) environment,
statistical and machine-learning algorithms are proposed to model and analyze the network …
statistical and machine-learning algorithms are proposed to model and analyze the network …
On Exploiting Symbolic Execution to Improve the Analysis of RAT Samples with angr
This article presents new contributions for Remote Access Trojan (RAT) analysis using
symbolic execution techniques. The first part of the article identifies the challenges in the …
symbolic execution techniques. The first part of the article identifies the challenges in the …