A survey of intrusion detection techniques

@article{Chandran2018ASO,
  title={A survey of intrusion detection techniques},
  author={Sharanya Chandran and K. Senthil Kumar},
  journal={International journal of engineering and technology},
  year={2018},
  volume={7},
  pages={187}
}
  • S. Chandran, K. S. Kumar
  • Published 10 March 2018
  • Computer Science
  • International journal of engineering and technology
In today’s world, the number of companies is increasing day by day that help end users to express opinion i.e. social media management, to watch news, payment applications, retail, ecommerce etc. There are large amount of forms, which take personal information’s like username, password, social security number, credit card, debit card and account information. Thus the applications are vulnerable to security issues like phishing attacks, denial of service attacks, cross-site scripting attack and… 
Q-Learning for Securing Cyber-Physical Systems : A survey
  • Montdher Alabadi, Zafer Albayrak
  • Computer Science
    2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)
  • 2020
TLDR
This paper provides a survey of the recent works that utilized the Q-Learning algorithm in terms of security enabling and privacy-preserving and classified and analyzed the state-of-the-art of Q-learning and CPS systems.

References

SHOWING 1-10 OF 27 REFERENCES
Detecting Web Attacks Using Multi-stage Log Analysis
TLDR
The proposed multi-stage log analysis architecture uses logs generated by the application during attacks to effectively detect attacks and to help preventing future attacks, and would be highly applicable to many intrusion detection applications.
XSS vulnerability assessment and prevention in web application
TLDR
In this paper, the focus is on injection, detection, and prevention of stored based XSS reflected XSS and DOM basedXSS, which are the most dangerous attacks against cross-site scripting.
An Attack Pattern Framework for Monitoring Enterprise Information Systems
TLDR
An attack pattern framework for EIS is proposed that enables an appIDS, such as SAP Enterprise Threat Detection (ETD) [1], to perform log analysis simultaneously from multiple sources and provides an attack pattern specification language and associated methodology for managing attack pattern lifecycle and appropriate alert mitigation response.
Introspective Intrusion Detection
TLDR
Introspective Intrusion Detection (IID) combines the advantages of traditional intrusion detection and CFI by distinguishing anomalies in execution without making absolute judgments about malicious intent.
BogusBiter: A transparent protection against phishing attacks
TLDR
BogusBiter is a unique client-side anti-phishing tool, which transparently feeds a relatively large number of bogus credentials into a suspected phishing site, and enables a legitimate Web site to identify stolen credentials in a timely manner.
New malware detection framework based on N-grams and Support Vector Domain Description
TLDR
A new framework to detect new malicious programs, based on N-grams and an improved version of Support Vector Domain Description is presented, which is generally regarded as ineffective against attacks like code polymorphism and metamorphism used by malware writers to obfuscate their code.
Semantic Interpretation of Structured Log Files
TLDR
A framework for analyzing logs and automatically generating a semantic description of their schema and content in RDF is described, which reveals their meaning and supports search, integration and reasoning over the data.
Detecting and mitigating denial of service attacks against the data plane in software defined networks
TLDR
This work discusses Denial of Service attacks against the data plane and their impact, and proposes a tailored statistical detection approach as well as a lightweight countermeasure to mitigate attacks in a lightweight and dependable way.
Research on the Performance of Mining Packets of Educational Network for Malware Detection between PM and VM
TLDR
This paper does a series of experiments to test performance of data mining algorithm based on Hadoop in physical machines and virtual machines and finds that the performance ofdata mining algorithm depends on disk I/O performance ofHadoop.
SECO: SDN sEcure COntroller algorithm for detecting and defending denial of service attacks
TLDR
SDN sEcure COntroller (SECO) a novel and simple detect and defense algorithm, running in the controller, for improving SDN security features under Denial of Service (DoS) attacks is introduced.
...
1
2
3
...