Forensics as a Service: Three-Tier Architecture for Cloud Based Forensic Analysis

Nanda, Saurav; Hansen, Raymond A.

doi:10.1109/ispdc.2016.31

Cited by 17 publications

(8 citation statements)

References 7 publications

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“…"X as a Service" is mainly used to describe the service of cloud computing. Recently, many studies [15][16][17][18] have proposed a digital forensic readiness model based on cloud computing service [19]. In the future, the computer system of financial company is also expected to be transferred to the cloud computing environment.…”

Section: Internal Network Hackingmentioning

confidence: 99%

K-FFRaaS: A Generic Model for Financial Forensic Readiness as a Service in Korea

Lee

Kim

2021

IEEE Access

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While Korean financial companies are currently providing electronic financial services by establishing the high-level information technology and security system in accordance with the Electronic Financial Supervision Regulations (EFSR), they are rarely equipped with digital forensic readiness (DFR) to maximize the capability to collect critical digital evidence (DE). So, there is a limit to identifying the root cause of financial incidents and securing admissible DE. In this paper, there, the authors present Financial Forensic Readiness as a Service in Korea (K-FFRaaS), as DFR of financial companies to secure the admissible DE. Based on ISO/IEC 27043:2015 international standard, K-FFRaaS consists of 3 processes groups, namely: Planning processes group, Implementation processes group, and Assessment processes group. Planning processes group is the processes group to prepare the organization to be forensically ready before potential incidents happen. Implementation processes group is the stage to carry out the processes defined in the planning group. Assessment processes group consists of activities that evaluate whether the result of the implementation process group is consistent with the objective of K-FFRaaS. The contribution of this research is to present that the financial company can adopt the systematic management procedure for mitigating the causes of incidents, store admissible DE, and present scientific evidence to a court of law through K-FFRaaS.

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Section: Internal Network Hackingmentioning

confidence: 99%

K-FFRaaS: A Generic Model for Financial Forensic Readiness as a Service in Korea

Lee

Kim

2021

IEEE Access

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“…Literature [11] aimed at the increasing number of data and equipment to be analyzed in electronic forensics cases, taking time parameters as data correlation factors, and proposed an automatic clustering algorithm based on self-organizing maps, which reduced the influences of noise data on forensics algorithms. (3) Electronic forensics in the context of cloud computing and big data is the current research focus and research hotspot in the field of electronic forensics [14][15][16][17][18]. Literature [14] proposed a three-layer forensic model adapted to the cloud computing architecture based on the cloud computing architecture.…”

Section: Related Workmentioning

confidence: 99%

Research on Data Analysis and Electronic Forensics Algorithm of Telecom Fraud Activity

Zhang

2021

Lecture Notes in Electrical Engineering

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This paper aims to provide effective and complete electronic evidence of telecom fraud activity for public safety agency. We proposed telecom fraud activity computer forensics platform architecture based on the characteristics of telecom operator data. The telephone fraud and SMS fraud were taken as the research object. The electronic evidence table of telecom fraud activities was generated. An electronic evidence analysis algorithm for telecom fraud activities was proposed. Dataset was analyzed from two aspects of user characteristics and fraud types. From the analysis results, it is known that there are more types of telecom fraud that require further analysis and research, in addition to telephone fraud and SMS fraud.

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“…The collected data and the result of the diagnosis algorithm are packed together in JavaScript Object Notation (JSON) format and sent to the central repository. Note that in the current implementation we do not store long‐term data, but the system can be easily extended to also store such kind of data (eg, for forensic reasons) in different levels as in the study of Nanda and Hansen …”

Section: Architecturementioning

confidence: 99%

“…Note that in the current implementation we do not store long-term data, but the system can be easily extended to also store such kind of data (eg, for forensic reasons) in different levels as in the study of Nanda and Hansen. 19 Phase 2 starts as soon as the page is completely fetched, rather than running together with the browsing. This architectural choice is taken as ingesting additional traffic on the network (eg, performing a Traceroute) may interfere with passive measurements phase.…”

Section: Phase 4: Uploadmentioning

confidence: 99%

Network level perspective in web sessions troubleshooting

Milanesio

Callegari

Michiardi

2019

Int J Communication

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Summary In the last years, the quantity of data and the number of applications carried over web traffic have been continuously increasing and nowadays web browsing accounts for most of the Internet traffic. In such a scenario, a poor browsing experience can result very annoying to the end user, and the effective identification of the root cause of such bad performance is of primary interest to both the users and the network operators. In this paper, we present a unified framework, based on a novel lightweight open‐source publicly available probe and on an original statistical diagnosis algorithm, to correctly and effectively point out the segment of a web connection (eg, local client, backbone network, and DNS server) responsible for a poor web browsing experience. The extensive experimental evaluation carried out in the paper demonstrates the effectiveness of the proposed approach to diagnose poor quality of experience at a large scale.

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Forensics as a Service: Three-Tier Architecture for Cloud Based Forensic Analysis

Cited by 17 publications

References 7 publications

K-FFRaaS: A Generic Model for Financial Forensic Readiness as a Service in Korea

K-FFRaaS: A Generic Model for Financial Forensic Readiness as a Service in Korea

Research on Data Analysis and Electronic Forensics Algorithm of Telecom Fraud Activity

Network level perspective in web sessions troubleshooting

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