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CSAFE’s Latest Resources

Change cannot happen without community. CSAFE is passionate about achieving its mission to apply a statistically sound and scientifically solid foundation to the interpretation of forensic evidence. To that end, we invite fellow scientists and researchers, along with those in the forensic and legal communities, to use and share these resources as we work together to elevate forensic science and technology.

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An algorithm for source identification of footwear impressions—its application on pristine shoeprints and crime-scene like shoeprints

Type: Research Area(s): ,

Published: 2023 | By: Hana Lee

This presentation is from the 107th International Association for Identification (IAI) Annual Educational Conference, National Harbor, Maryland, August 20-26, 2023. Posted with permission of CSAFE.

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Diagnostic Tools for Automatic Cartridge Case Comparisons

Type: Research Area(s): ,

Published: 2023 | By: Joseph Zemmels

The following was presented at the Association of Firearm and Tool Mark Examiners (AFTE) 2023, Austin, Texas, May 21-26, 2023. Copyright 2023, The Authors. Posted with permission of CSAFE.

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Algorithmic assessment of striation similarity between wire cuts

Type: Research Area(s):

Published: 2023 | By: Yuhang Lin

The following was presented at the Association of Firearm and Tool Mark Examiners (AFTE) 2023, Austin, Texas, May 21-26, 2023. Copyright 2023, The Authors. Posted with permission of CSAFE.

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An Anti-Fuzzing Approach for Android Apps

Type: , Research Area(s):

Published: 2023 | By: Chris Chao-Chun Cheng

One of significant mobile app forensic analysis problems is the app evidence extraction from the device. Given the fact that mobile apps could generate more than 19K files in a device [6], simply manually inspecting every file is time consuming…

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Forensic Analysis of Android Cryptocurrency Wallet Applications

Type: , Research Area(s):

Published: 2023 | By: Chen Shi

Crypto wallet apps that integrate with various block-chains allow the users to make digital currencies transaction with QR codes. According to reports from financesonline [3], there is over 68 million crypto wallet app users in 2021. As new crypto wallets…

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Variations and Extensions of Information Leakage Metrics with Applications to Privacy Problems with Imperfect Statistical Information

Type: , Research Area(s): ,

Published: 2023 | By: Shahnewaz Karim Sakib

The conventional information leakage metrics assume that an adversary has complete knowledge of the distribution of the mechanism used to disclose information correlated with the sensitive attributes of a system. The only uncertainty arises from the specific realizations that are…

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Camera Device Identification and the Effects of Underexposure

Type: , Research Area(s): ,

Published: 2023 | By: Seth Pierre

Technology today allows a photograph from a digital camera to be matched with the camera that took it. However, the matching software was created over 10 years ago using data that is not necessarily representative of today’s data. The objective…

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Shifting decision thresholds can undermine the probative value and legal utility of forensic pattern-matching evidence

Type: Research Area(s): ,

Published: 2023 | By: William Thompson

Forensic pattern analysis requires examiners to compare the patterns of items such as fingerprints or tool marks to assess whether they have a common source. This article uses signal detection theory to model examiners’ reported conclusions (e.g., identification, inconclusive, or…

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A statistical approach to aid examiners in the forensic analysis of handwriting

Type: Research Area(s): ,

Published: 2023 | By: Amy Crawford

We develop a statistical approach to model handwriting that accommodates all styles of writing (cursive, print, connected print). The goal is to compute a posterior probability of writership of a questioned document given a closed set of candidate writers. Such…

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Ensemble learning for score likelihood ratios under the common source problem

Type: Research Area(s):

Published: 2023 | By: Federico Veneri

Machine learning-based score likelihood ratios (SLRs) have emerged as alternatives to traditional likelihood ratios and Bayes factors to quantify the value of evidence when contrasting two opposing propositions. When developing a conventional statistical model is infeasible, machine learning can be…

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