Information leakage detection in distributed systems using software agents

Lee, Yung-Chuan; Bishop, Stephen; Okhravi, Hamed; Rahimi, Shahram

doi:10.1109/ia.2009.4927510

Cited by 4 publications

(1 citation statement)

References 20 publications

(18 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Records [12]. Given the present strict regulatory and legal compliance requirement on intellectual and personal data protection, organisations, including Universities, have invested a great deal of time and resources in safeguarding their information from potential unauthorised access and disclosure [13]. Many researchers have developed various counter measures to fight against data leakage issues, which are collectively known as Data Leakage Prevention (DLP) solutions.…”

Section: Literature Reviewmentioning

confidence: 99%

A Review on Distribution Model for Mobile Agent-Based Information Leakage Prevention

Kayode¹,

Dayo²,

Uthman³

2021

View full text Add to dashboard Cite

With the continuous use of cloud and distributed computing, the threats associated with data and information technology (IT) in such an environment have also increased. Thus, data security and data leakage prevention have become important in a distributed environment. In this aspect, mobile agent-based systems are one of the latest mechanisms to identify and prevent the intrusion and leakage of the data across the network. Thus, to tackle one or more of the several challenges on Mobile Agent-Based Information Leakage Prevention, this paper aim at providing a comprehensive, detailed, and systematic study of the Distribution Model for Mobile Agent-Based Information Leakage Prevention. This paper involves the review of papers selected from the journals which are published in 2009 and 2019. The critical review is presented for the distributed mobile agent-based intrusion detection systems in terms of their design analysis, techniques, and shortcomings. Initially, eighty-five papers were identified, but a paper selection process reduced the number of papers to thirteen important reviews.

show abstract

Section: Literature Reviewmentioning

confidence: 99%