Intrusion tolerance model against higher institution database
Article Sidebar
Main Article Content
Abstract
Privacy and security are the two major concerns of keeping and accessing data on the internet. The rate of intruding organisation’s database by unauthorised users is on the increase. Thus, the affected organisation’s data confidentiality is lost; it can be viewed, modified, deleted and/or make it inaccessible to authorised users. Intrusion detection and tolerance techniques help in recognising malicious attacks as well as supports the websites to survive the attack. A quantitative approach was used in this study even though numerous attempts of quantitative evaluation of the survivability of intrusion tolerant systems, especially in database field have been made. Study on survivability of intrusion tolerant systems has being done, taking behaviour of attack, prediction of scale, speed of database damage propagation and its degree of spreading as facilitators. This paper provides the intrusion tolerant database system as a series of state transition model (Zumkas Model) based on the hidden Markov model.
Keywords: Intrusion, survivability, model, patterns
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).