First Ever Advanced Cross Case Analytics (ACCE) released with Secure View 4

First Ever Advanced Cross Case Analytics (ACCE) for mobile forensics will debut with Secure View 4!

Irvine, Ca. 4/27/2015

With the launch of Secure View 4 this Thursday, April 30th, 2015 new and current users will have access to the first ever ACCE analytics for mobile forensics called SV Detect. This breakthrough will allow users to increase conviction rates and build new evidence against past crimes. SV Detect will allow Secure View users to run newly acquired data against their old reports. This fantastic feature allows a user to run newly acquired contacts and text messages through old cases to match up data. This tool is a feature that can be turned on or off at your discretion. SV Detect is just one of the new features to be launched with Secure View 4.“A major benefit of Secure View is that it has always been software based. We did not require departments to purchase individual machines that could not be easily connected or updated” said Jeremy Kirby, Director of Sales for Susteen, Inc. “With the SV Detect module, detectives will now be able to truly use this to their advantage.” “They can run data off of newly acquired phones through their past reports and acquisitions. This might allow them to reopen old cases based on newly acquired data. It is just another tool that our military and law enforcement agencies can use to help keep us safer.”
Secure View 4 launches on April 30th, 2015. Secure View was the first mobile forensic tool on the market and continues to break new ground with all new analytics and the recent launch of their SV Strike pincode/passcode breaking software for both Androids and iPhones. Secure View 4 will be localized for North American, European, South American and Asian markets.

Request your free trial or sign up for a webinartoday! [email protected]
[image]

Leave a Comment

Latest Videos

Quantifying Data Volatility for IoT Forensics With Examples From Contiki OS

Forensic Focus 22nd June 2022 5:00 am

File timestamps are used by forensics practitioners as a fundamental artifact. For example, the creation of user files can show traces of user activity, while system files, like configuration and log files, typically reveal when a program was run. 

Despite timestamps being ubiquitous, the understanding of their exact meaning is mostly overlooked in favor of fully-automated, correlation-based approaches. Existing work for practitioners aims at understanding Windows and is not directly applicable to Unix-like systems. 

In this paper, we review how each layer of the software stack (kernel, file system, libraries, application) influences MACB timestamps on Unix systems such as Linux, OpenBSD, FreeBSD and macOS.

We examine how POSIX specifies the timestamp behavior and propose a framework for automatically profiling OS kernels, user mode libraries and applications, including compliance checks against POSIX.

Our implementation covers four different operating systems, the GIO and Qt library, as well as several user mode applications and is released as open-source.

Based on 187 compliance tests and automated profiling covering common file operations, we found multiple unexpected and non-compliant behaviors, both on common operations and in edge cases.

Furthermore, we provide tables summarizing timestamp behavior aimed to be used by practitioners as a quick-reference.

Learn more: https://dfrws.org/presentation/a-systematic-approach-to-understanding-macb-timestamps-on-unixlike-systems/

File timestamps are used by forensics practitioners as a fundamental artifact. For example, the creation of user files can show traces of user activity, while system files, like configuration and log files, typically reveal when a program was run.

Despite timestamps being ubiquitous, the understanding of their exact meaning is mostly overlooked in favor of fully-automated, correlation-based approaches. Existing work for practitioners aims at understanding Windows and is not directly applicable to Unix-like systems.

In this paper, we review how each layer of the software stack (kernel, file system, libraries, application) influences MACB timestamps on Unix systems such as Linux, OpenBSD, FreeBSD and macOS.

We examine how POSIX specifies the timestamp behavior and propose a framework for automatically profiling OS kernels, user mode libraries and applications, including compliance checks against POSIX.

Our implementation covers four different operating systems, the GIO and Qt library, as well as several user mode applications and is released as open-source.

Based on 187 compliance tests and automated profiling covering common file operations, we found multiple unexpected and non-compliant behaviors, both on common operations and in edge cases.

Furthermore, we provide tables summarizing timestamp behavior aimed to be used by practitioners as a quick-reference.

Learn more: https://dfrws.org/presentation/a-systematic-approach-to-understanding-macb-timestamps-on-unixlike-systems/

YouTube Video UCQajlJPesqmyWJDN52AZI4Q_i0zd7HtluzY

A Systematic Approach to Understanding MACB Timestamps on Unixlike Systems

Forensic Focus 21st June 2022 5:00 am

This error message is only visible to WordPress admins

Important: No API Key Entered.

Many features are not available without adding an API Key. Please go to the YouTube Feed settings page to add an API key after following these instructions.

Latest Articles

Share to...