IWNetFAF: An Integrated Wireless Network Forensic Analysis Framework

2016 ◽  
Author(s):  
Nadia Benchikha ◽  
Mohamed Krim ◽  
Khaled Zeraoulia ◽  
Chafika Benzaid
Keyword(s):  
Wireless Network ◽  
Forensic Analysis ◽  
Analysis Framework ◽  
Network Forensic

Forensic Analysis of Artifacts of Giant Instant Messaging “WhatsApp” in Android Smartphone

2018 ◽  
Vol 5 (2) ◽  
pp. 73-83
Author(s):  
Hussein Abed Ghannam
Keyword(s):  
Instant Messaging ◽  
Smart Phone ◽  
Forensic Analysis ◽  
Digital Evidence ◽  
Terror Attack ◽  
Left Behind ◽  
Digital Crime ◽  
Internal Storage ◽  
Network Forensic ◽  
Electronic Crime

WhatsApp is a giant mobile instant message IM application with over 1billion users. The huge usage of IM like WhatsApp through giant smart phone “Android” makes the digital forensic researchers to study deeply. The artefacts left behind in the smartphone play very important role in any electronic crime, or any terror attack. “WhatsApp” as a biggest IM in the globe is considered to be very important resource for information gathering about any digital crime. Recently, end-to-end encryption and many other important features were added and no device forensic analysis or network forensic analysis studies have been performed to the time of writing this paper. This paper explains how can we able to extract the Crypt Key of “WhatsApp” to decrypt the databases and extract precious artefacts resides in the android system without rooting the device. Artefacts that extracted from the last version of WhatsApp have been analysed and correlate to give new valuable evidentiary traces that help in investigating. Many hardware and software tools for mobile and forensics are used to collect as much digital evidence as possible from persistent storage on android device. Some of these tools are commercial like UFED Cellebrite and Andriller, and other are open source tools such as autopsy, adb, WhatCrypt. All of these tools that forensically sound accompanied this research to discover a lot of artefacts resides in android internal storage in WhatsApp application.

scholarly journals Intrusion Detection System in Network Forensic Analysis and Investigation

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Forensic Analysis ◽  
Signature Database ◽  
The Law ◽  
Secure Network ◽  
Network Forensic ◽  
Network Administrators

Intrusion Detection System is built to protect the network from threats of hackers, crackers and security experts from the possibility of action that does not comply with the law. Problems arise when new attacks emerge in a relatively fast so that a network administrator must create their signature and stay updated with new types of attacks that appear. IDS would oversee the packets in the network and benchmark against only those packages with a signature database that is owned by IDS systems or attributes of the attempted attacks ever known. By using IDS, network security will be more secure. Network administrators will be easier to know if network conditions change.

A transductive scheme based inference techniques for network forensic analysis

2015 ◽  
Vol 12 (2) ◽  
pp. 167-176 ◽  
Author(s):  
Zhihong Tian ◽  
Wei Jiang ◽  
Yang Li
Keyword(s):  
Forensic Analysis ◽  
Inference Techniques ◽  
Network Forensic

scholarly journals Machine Learning Based Automotive Forensic Analysis for Mobile Applications Using Data Mining

2015 ◽  
Vol 16 (2) ◽  
pp. 350
Author(s):  
MD. Hussain Khan ◽  
G. Pradeepini
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Mobile Apps ◽  
Forensic Analysis ◽  
Evaluation Framework ◽  
Security Evaluation ◽  
Analysis Framework ◽  
Security Issues ◽  
The People ◽  
Using Data

<p>Phone is a device which provides communication between the people through voice, text, video etc. Now a day’s people may leave without food but not without using phones. No of operating systems are working with various versions and various security issues are working. Security is very important task in Mobiles and mobile apps. To improve the security status of mobiles, existing methodology is using cloud computing and data mining. Out traditional method is named as MobSafe to identify the mobile apps antagonism or graciousness. In the proposed system, we adopt Android Security Evaluation Framework (ASEF) and Static Android Analysis Framework (SAAF).In this paper, our proposed system works on machine learning to conduct automotive forensic analysis of mobile apps based on the generated multifaceted data in this stage.</p>

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