scholarly journals A Forensic Approach on Data Retrieval from IC/eMMC of Damaged Windows Mobile Phone using Easy JTagPlus Box tool and Magnet Forensic Axiom

2021 ◽  
pp. 499-508
Author(s):  
Bhushan Ghode ◽  
Akhlesh Kumar ◽  
Khevna Maniar ◽  
Dr. S. K. Jain
Keyword(s):  
Operating Systems ◽  
Data Extraction ◽  
Data Retrieval ◽  
Private Life ◽  
Digital Evidence ◽  
Portable Devices ◽  
Skill Sets ◽  
Digital World ◽  
Windows Mobile ◽  
Specialized Hardware

The digital world is dominated and ruled by the IOS and Android operating systems on mobile as well as tablet platforms. Together they share a whopping 99% (till 2021) of the share market. The Windows Phones (WP) are occupants of that less than 1% platform that they share with other subsidiary operating systems. Due to the lack of commercial popularity and production of such Windows devices, the process of data extraction and analysis of such devices is unique and challenging for forensic experts. The standard forensic data retrieving software and hardware do not support advanced requisition techniques except the direct extraction. Thus, in cases with locked WP devices, the software/ hardware is unable to support the device’s physical extraction or lock bypass facility. As observed in several digital cases, these portable devices contain details of an individual’s most private life including communications, contacts, browsing history, and location specifics at any given time. Although the operating systems of Microsoft and Windows mobile devices are similar in certain ways, specialized skill sets and tools are required while dealing with location, examination, and interpretation of the digital evidence on these systems. In this research paper, the authors are discussing the reliability and success of data extraction of a Windows mobile device from IC/eMMC using specialized hardware/software with the Windows device.

scholarly journals Improved Design Considerations of 8T SRAM Cell to Avoid Data Extraction

2020 ◽  
Vol 10 (1) ◽  
pp. 29-34
Keyword(s):  
Leakage Current ◽  
Data Extraction ◽  
Memory Cell ◽  
Memory Storage ◽  
Portable Devices ◽  
Simulation Tool ◽  
Digital World ◽  
Sram Cell ◽  
Static Power ◽  
Improved Design

In this digital world, everything is inculcated within technology which increases the importance of memory storage. All the data processed in today’s electronics requires a storage space. The data stored in this memory are extracted & misused which is a serious issue in day today world. This provenly shows that there is a need for enhancement in data security. There are different types of memory storage. Among them portable devices, routers, workstation, personal computer commonly uses SRAM for storage. Due to side-channel leakage power in SRAM, illegal data extraction had become a serious threat.6T SRAM cells are often prone to this power analysis attack [4]. This data attack often happens in standby mode of a memory cell. To provide resiliency to these types of attacks, a symmetric 8T SRAM cell was used which incorporates two more transistors than the conventional 6T cell to significantly reduce the correlation between the stored data and the leakage currents. The main purpose of this paper is to simulate & analyze leakage current distribution for the conventional 6T SRAM cell and a symmetric 8T SRAM cell using Cadence (version 14.6) simulation tool. In addition to this, an effort is made to reduce the leakage current by using the W/L ratio of the transistor. A 16X16 SRAM array using the 6T & 8T SRAM cell is designed. With this design, the reduced standby static power & leakage current of 8T SRAM Cell is compared with convention 6T SRAM Cell. Standard GPDK (generic process design kit) 90nm library in Cadence (version 14.6) simulation tool is used for designing.

Forensic Data Extraction and Analysis of Left Artifacts on emulated Android Phones: A Case Study of Instant Messaging Applications

2017 ◽  
Vol 2 (11) ◽  
pp. 8-16
Author(s):  
Moses Ashawa ◽  
Innocent Ogwuche
Keyword(s):  
Mobile Phones ◽  
Instant Messaging ◽  
Data Extraction ◽  
Digital Evidence ◽  
Cyber Attack ◽  
Forensic Evidence ◽  
Digital Forensic ◽  
Proportional Increase ◽  
Forensic Tools

The fast-growing nature of instant messaging applications usage on Android mobile devices brought about a proportional increase on the number of cyber-attack vectors that could be perpetrated on them. Android mobile phones store significant amount of information in the various memory partitions when Instant Messaging (IM) applications (WhatsApp, Skype, and Facebook) are executed on them. As a result of the enormous crimes committed using instant messaging applications, and the amount of electronic based traces of evidence that can be retrieved from the suspect’s device where an investigation could convict or refute a person in the court of law and as such, mobile phones have become a vulnerable ground for digital evidence mining. This paper aims at using forensic tools to extract and analyse left artefacts digital evidence from IM applications on Android phones using android studio as the virtual machine. Digital forensic investigation methodology by Bill Nelson was applied during this research. Some of the key results obtained showed how digital forensic evidence such as call logs, contacts numbers, sent/retrieved messages, and images can be mined from simulated android phones when running these applications. These artefacts can be used in the court of law as evidence during cybercrime investigation.

scholarly journals An Adaptive Scheduler for Real-Time Operating Systems to Extend WSN Nodes Lifetime

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Roberto Rodriguez-Zurrunero ◽  
Ramiro Utrilla ◽  
Elena Romero ◽  
Alvaro Araujo
Keyword(s):  
Operating System ◽  
Real Time ◽  
Operating Systems ◽  
Research Area ◽  
Rechargeable Batteries ◽  
Wireless Sensor ◽  
Portable Devices ◽  
Wireless Devices ◽  
Changing Environments ◽  
Tasks Scheduling

Wireless Sensor Networks (WSNs) are a growing research area as a large of number portable devices are being developed. This fact makes operating systems (OS) useful to homogenize the development of these devices, to reduce design times, and to provide tools for developing complex applications. This work presents an operating system scheduler for resource-constraint wireless devices, which adapts the tasks scheduling in changing environments. The proposed adaptive scheduler allows dynamically delaying the execution of low priority tasks while maintaining real-time capabilities on high priority ones. Therefore, the scheduler is useful in nodes with rechargeable batteries, as it reduces its energy consumption when battery level is low, by delaying the least critical tasks. The adaptive scheduler has been implemented and tested in real nodes, and the results show that the nodes lifetime could be increased up to 70% in some scenarios at the expense of increasing latency of low priority tasks.

scholarly journals On-Device Deep Learning Inference for System-on-Chip (SoC) Architectures

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 689
Author(s):  
Tom Springer ◽  
Elia Eiroa-Lledo ◽  
Elizabeth Stevens ◽  
Erik Linstead
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Real Time ◽  
Operating Systems ◽  
System On Chip ◽  
Low Latency ◽  
Management Framework ◽  
On Chip ◽  
Specialized Hardware ◽  
Deterministic Behavior

As machine learning becomes ubiquitous, the need to deploy models on real-time, embedded systems will become increasingly critical. This is especially true for deep learning solutions, whose large models pose interesting challenges for target architectures at the “edge” that are resource-constrained. The realization of machine learning, and deep learning, is being driven by the availability of specialized hardware, such as system-on-chip solutions, which provide some alleviation of constraints. Equally important, however, are the operating systems that run on this hardware, and specifically the ability to leverage commercial real-time operating systems which, unlike general purpose operating systems such as Linux, can provide the low-latency, deterministic execution required for embedded, and potentially safety-critical, applications at the edge. Despite this, studies considering the integration of real-time operating systems, specialized hardware, and machine learning/deep learning algorithms remain limited. In particular, better mechanisms for real-time scheduling in the context of machine learning applications will prove to be critical as these technologies move to the edge. In order to address some of these challenges, we present a resource management framework designed to provide a dynamic on-device approach to the allocation and scheduling of limited resources in a real-time processing environment. These types of mechanisms are necessary to support the deterministic behavior required by the control components contained in the edge nodes. To validate the effectiveness of our approach, we applied rigorous schedulability analysis to a large set of randomly generated simulated task sets and then verified the most time critical applications, such as the control tasks which maintained low-latency deterministic behavior even during off-nominal conditions. The practicality of our scheduling framework was demonstrated by integrating it into a commercial real-time operating system (VxWorks) then running a typical deep learning image processing application to perform simple object detection. The results indicate that our proposed resource management framework can be leveraged to facilitate integration of machine learning algorithms with real-time operating systems and embedded platforms, including widely-used, industry-standard real-time operating systems.

Privacy Preserving Data Mining as Proof of Useful Work

2021 ◽  
Vol 32 (1) ◽  
pp. 69-85
Author(s):  
Hjalmar K. Turesson ◽  
Henry Kim ◽  
Marek Laskowski ◽  
Alexandra Roatis
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Challenging Problem ◽  
Privacy Preserving Data Mining ◽  
Physical Resource ◽  
Digital World ◽  
General Utility ◽  
Tremendous Amount ◽  
Specialized Hardware ◽  
Computational Resources

Blockchains rely on a consensus among participants to achieve decentralization and security. However, reaching consensus in an online, digital world where identities are not tied to physical users is a challenging problem. Proof-of-work provides a solution by linking representation to a valuable, physical resource. While this has worked well, it uses a tremendous amount of specialized hardware and energy, with no utility beyond blockchain security. Here, the authors propose an alternative consensus scheme that directs the computational resources to the optimization of machine learning (ML) models – a task with more general utility. This is achieved by a hybrid consensus scheme relying on three parties: data providers, miners, and a committee. The data provider makes data available and provides payment in return for the best model, miners compete about the payment and access to the committee by producing ML optimized models, and the committee controls the ML competition.

Computer and Network Forensics

2011 ◽  
pp. 55-74
Author(s):  
Sriranjani Sitaraman ◽  
Subbarayan Venkatesan
Keyword(s):  
Legal System ◽  
Single Machine ◽  
Computer Forensics ◽  
Digital Evidence ◽  
Disk Drives ◽  
Network Forensics ◽  
Digital World ◽  
The World

This chapter introduces computer and network forensics. The world of forensics is well understood in the non-digital world, whereas this is a nascent field in the digital cyberworld. Digital evidence is being increasingly used in the legal system such as e-mails, disk drives containing damaging evidence, and so on. Computer forensics deals with preserving and collecting digital evidence on a single machine while network forensics deals with the same operations in a connected digital world. Several related issues and available tools are discussed in this chapter.

“I have the right to a private life”: Medical students’ views about professionalism in a digital world

2013 ◽  
Vol 35 (10) ◽  
pp. 826-831 ◽  
Author(s):  
Shelley Ross ◽  
Krista Lai ◽  
Jennifer M. Walton ◽  
Paul Kirwan ◽  
Jonathan S. White
Keyword(s):  
Medical Students ◽  
Private Life ◽  
Digital World ◽  
The Right

scholarly journals A Metode Offline Forensik Untuk Analisis Digital Artefak Pada TOR Browser Di Sistem Operasi Linux

2020 ◽  
Vol 4 (2) ◽  
pp. 41-51
Author(s):  
Wisnu Sanjaya ◽  
Bambang Sugiantoro ◽  
Yudi Prayudi
Keyword(s):  
Operating System ◽  
Operating Systems ◽  
Rapid Development ◽  
Digital Evidence ◽  
Forensic Investigation ◽  
User Privacy ◽  
Web Browser ◽  
Digital Footprint ◽  
Technology Products ◽  
The Creation

The rapid development of the IT world has covered all aspects of life and among IT technology products is the creation of Operating Systems and Web browser applications. Privacy in the use of IT in the open era is now highly expected, therefore now widely developed Operating Systems and Web browser applications that have facilities to protect user privacy. Linux and TOR Browser is a combination that is widely used in the field of security, but unfortunately many are misused by the person in a crime. The motivation to use both is to eliminate or minimize the digital footprint of the browsing activity so that it will complicate the search of digital evidence in a crime. This research proposes a framework of stages for TOR Browser analysis in Linux Operating System which aims to provide solution in forensic investigation using offline forensic method. The use of offline forensic methods to obtain detailed information from a digital proof on a computer in a off state

scholarly journals A Forensic Evidence Recovery from Android Device Applications

2021 ◽  
pp. 135-140
Author(s):  
Axay Patel ◽  
Dr. Priyanka Sharma ◽  
Prof. Dharti Dholariya
Keyword(s):  
Open Source ◽  
Operating Systems ◽  
Digital Evidence ◽  
Smartphone Applications ◽  
Forensic Evidence ◽  
Device Applications ◽  
Unlawful Conduct

In a computerized world, indeed unlawful conduct and/or violations may be named as advanced. This world is expanding. Getting to be versatile, where the fundamental computation and communication substances are Little Scale Computerized Gadgets (SSDDs) such as standard versatile phones, individual computerized collaborators, smartphones, and tablets. The ought to recoup information, which might refer to illegal and unethical exercises gave rise to the teaching of portable forensics, which has ended up a fundamental portion of computerized forensics. The literature relevant to Smartphone forensics, as explored in this paper, focuses on the architecture of Smartphone operating systems. It also addresses the digital evidence of Smartphone applications. in this paper undertakes practical experiments to identified sources for evidence that can later be used in the judiciary system. In this research, I'll use open-source Tools that can recover deleted data from the application.

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