Digital forensics denotes the analysis, investigation of shreds of evidence against internal and external attackers. Generally, in an incident response system, digital forensics plays a significant role for individuals, organizations, and courts. For instance: In an organization, it is denoted utilizing policies, plans, standards, and employees. All these strategies should increase the efficiency of digital forensics operations. In this, the specific policy should provide the procedure for digital forensics. 

This page is about to give innovative digital forensics project ideas with add-on research and development information!!!

Aim of Digital Forensics 

The primary objective of digital forensics is to support the court of law to take time-critical decisions over cybercrimes. In this, digital forensics enables the investigator to identify, collect and store pieces of evidence. Then, let extract the essential features from stored data and apply investigation techniques for comprehensive interpretation. Moreover, it uses big data from different sources like networks, the cloud, and devices. Beyond digital forensics, there are numerous forensic types to craft novel digital forensics project ideas and they are as follows,

Types of Digital Forensics 

• Web Forensics
• Mobile Forensics
• Cyber Forensics
• Data Forensics
• System Forensics
• Email Forensics
• Network Forensics
• Proactive Forensics
• Enterprise Forensics

Now, we can see that how the digital forensics model is developed and what are two primary modules associated with the model. The primary modules are attack detection and forensic analysis. Here, the attack detection module depicts how the attacker attacks the network/data and how it can be detected. Similarly, the forensic analysis module describes how the evidence is collected and analysed.

Digital Forensics Model

• Attack Detection Module
  • Detect the compromised network by monitoring the network
  • Identify the flaws of network performance
  • Recognize the unauthorized access
  • Collect the security threats, vulnerabilities, and attacks information
• Forensics Analysis Module 
  • Apply forensic analysis strategies on collected data
  • Packing of content 
  • Store the network security for remote access

In addition, we have also given the necessity of a digital forensics model. It gives you information on how the increased cases will increase the evidence and number of devices used in the digital forensic model.

Why use Digital Forensics Model? 

• Increases of cases will maximize the possible relevant evidence
• Maximize the number of devices that are held for analyzing specific case 
• The capacity of evidence increases on each item will increase its size

Next, we can see the research issues associated with digital forensics. However, digital forensics is more useful in real-time court law or other individual/business purposes; it has challenges in acquiring the expected results. Since the input data are gathered from different sources of different types and sizes. So, it creates issues related to large-scale data volume, mismatch data type, technical complexity, ununiformed time, consistency, and correlation. If you are interested to know more about latest digital forensics project ideas, reach our expert digital forensic panel team. Below, we have specified issues of each classification.

Current Challenges of Digital Forensics 

• Volume Issue
  • Huge-scale storage capacity but not automated
• Diversity Issue
  • No proper technique to handle huge data from various sources
  • Lack of calibration in the evidence storage system
  • Uncertainty in metadata formatting while sharing evidence among global law enforcement agencies
• Complexity Issue
  • Increase volume of heterogeneous data with low quality
  • Need techniques to reduce data before start investigation
• Unified Timeline Issue
  • Data collected from multiple sources give different time references so it causes confusion in the creation of a unified timeline
• Steadiness and Correlation Issue
  • Existing tools only perform identification of fragmented evidence but do not enable to perform other operations like reassembly, storing, etc.
  • Lack of finding the relation between fragmented evidence

In addition, we have given the different kinds of security threats/attacks in digital forensics. Since security is the most important aspect that everyone is demanding to protect their own digital data from attacks. Therefore, it becomes an evergreen area in digital forensics. Here, we have listed the few common attacks with their appropriate defensive measures. Further, we also support you to tackle other security attacks by our own way of solutions.

Security Attacks and Countermeasures    

• Sensitive Data Exposure
  • Create man-in-the-middle attacks or data theft in data transmission between client and server
• Solution
  • Implement secure protocol, key management, and encryption techniques (TLS, HSTS, PFS)
  • Use Salted hashing functions with delay factor (for password storage)
  • Disable caching and test the system configuration
• Injection
  • Attack on any data source such as environmental variable, web services, parameters, vector, etc.
  • Happen only in the presence of hostile data in the interpreter
  • Solution 
    • Use defensive APIs, whitelist server-side scripting, etc.
• Broken Access Control
  • Attacker deploys access control tools (DAST, SAST) which are detected by manual process or system automation
  • Solution
    • Employ access control in server-side (sere has no accessibility)
    • Deny the access control deployment by an attacker in default
    • Use advance access control mechanisms
    • Record the ownership while designing access control
    • Alert administrator while log control failure
    • Disable the directory of the webserver (if not in web roots)
    • Ad unique policies and needs in modeling access control
• Broken Authentication 
  • An attacker attempts to break authentication by following methods,
    • Administrative Account lists
    • Credential stuffing
    • Dictionary attacks
    • Credential re-use attacks
    • Session management attacks
    • Brute force attacks
  • Solutions
    • Multi-factor authentication
    • Weak-password checks
    • Default Password Avoidance
    • Limit login attempts
    • Administrator alert-service while wrong login attempts
    • Random session identity with high entropy (unacceptable after session expiries)
• XML External Entities (XXE)
  • Attacker use weak XML processors as a launch point to add hostile data on existing XML file or upload own XML file
  • Solution
    • Use defensive whitelist server-side scripting, sanitization, filtering, etc.

In the earlier section, we have seen how the digital model will be developed with their important modules in implementing digital forensic project ideas. Here, we can see in what way we can improve the performance of the digital forensic model. Using the below-specified points in the designing phase of the model will surely provide you the best outcome.

How to design an effective digital forensic model? 

• Zero Error
  • Forensic operations should not create untraceable errors and even a small error is needed to be recorded
• Original Meaning
  • Forensic operations should not affect the originality of evidence (very slight changes is acceptable)
• Precise Study
  • Forensic operations should be conducted by legal users who have sufficient practice/skills
• High Clearness and Reliability
  • Forensic operations should guarantee correctness and reliability of evidence even assessed by an external authority (court)

So far, we have discussed the fundamentals, challenges, security attacks with solutions of digital forensics. Now, we can see the recent digital forensics research ideas for final year students/scholars. To provide you up-to-the-minute digital forensics project ideas, we work tirelessly on emerging research areas. Also, we assure you that we cover all the areas in the research field to fulfill the needs of our clients. From our research, we found the following ideas gain more interest on students and the research community.

Latest Digital Forensics Project Ideas

• Cyber Criminal Profiling System
• Realization of Graphic Systems and Registry Data  
• Presentation of Evidence in Digital Forensic 
• Network Traffic Management
• Secret Communication in Multimedia Forensics
• Digital Proof Abstraction and Investigation
• Improved Security Mechanisms for Multimedia Forensics 
• Applied Cryptography and Steganography
• Cybercrime Detection and Analysis Schemes for Evidence Collection
• Comparative Study on Various Evidence Investigation Practices

From the above list, we have taken the “Improved security mechanisms for multimedia forensics” topic as a sample for discussion. In today’s technologies, there are countless researches are conducted to increase forensic developments. Also, it increases not only the developments but also the development tools. These tools and technologies are intended to detect all probabilities of digital data tampering for organizational purposes.      

 On the other hand, it also increases the counter-forensic tools for the corrective investigation. These tools are more effective than multimedia forensics tools which are not suitable for the adversarial platform. In this case, designing advanced forensic gives effective results even in the adversarial platform. Our developers are unique in developing a solution for complicated problems. Here, we have given you some commonly used techniques that give the best results.

Multimedia Forensics & Security 

• Re-sampling
  • Statistical Strategies (EM)
• Copy-move (Data Cloning)
  • Autocorrelation
  • Principle Component Analysis (PCA)
  • Block Signature Matching
  • Discrete Cosine Transform (DCT)
• Multimedia Improvement
  • Blind Statistical Estimators (geometry, noise, and blur)
• Compression of Double JPEG 
  • Valuation of JPEG artifacts (by frequencies)
• Modification (noise nonlinearities, luminance)
  • Higher-Order Statistics
  • EM Approaches
• Post Processing
  • Remove the modification (sharp edges)
• Splicing
  • Bi-coherence and Bi-spectral Inquiry
  • Higher Oder Statistics
  • Noise Variation Computation
• Transformation of Geometric 
  • Spatial data among duplicated blocks and neighbors

We hope, you are clear in the major techniques used for multimedia forensics and security. Furthermore, we have also included widely used datasets that are more apt for multimedia forensics-related projects. Here, we have classified the datasets into two aspects as image-based datasets and video-based datasets with their features. We also recommend other datasets based on your handpicked forensic type and topic.

Latest Datasets for Digital Forensics 

Image-Based Datasets 

• PS-Battles
  • Format – JPG and PNG
  • Image Size – 130*60 – 10000 * 8558
• Forged / 
  • Prist – 102,028 / 11,142
• FaceSwap
  • Format – JPG
  • Image Size – 450*338 – 7360 * 4912
• Forged / 
  • Prist – 1,927 / 1,758
• DEFACTO
  • Format – TIF
  • Image Size – 240*320 – 640 * 640
  • Forged – 229,000
• MFCC2019
  • Format – JPG, PNG, TIF, RAW and BMP
  • Image Size – 160*120 – 2624 * 19680
• Forged / 
  • Prist – 10,279 / 5,750
• GAN Collection
  • Format – PNG
  • Image Size – 256*256 – 1024 * 1024
• Forged / 
  • Prist – 596,000 / 356,000

Video based Datasets 

• DDD
  • Format – CRF=0, 23, 40 and H264
  • Frame Size – 1080p
  • Forged / Prist – 3,068 / 363
• FFW
  • Format – YouTube, H264
  • Frame Size – 1080p, 480p and 720p
  • Forged – 150
• DFDC
  • Format – H264
  • Frame Size – 240p to 2160p
  • Forged / Prist – 100,000 / 19,154
• Celeb-DF
  • Format – MPEG4
  • Frame Size – various
  • Forged / Prist – 5,639 / 590
• FaceForensics++
  • Format – CRF=0, 23, 40 and H264
  • Frame Size – 1080p, 480p and 720p
  • Forged / Prist – 4,000 / 1,000

Artificial Intelligence for Digital Forensics 

Let’s take the image forensic type which has a key player role in both criminality analysis and a civil lawsuit. Specifically, machine learning techniques are largely recognized in many mage forensics applications. Although it is highly utilized, it has certain constraints and weaknesses in Adversarial Image Forensics that are correlated with real-world moments. Here, we have given you different techniques that give the best result in Adversarial Image Forensics.

Techniques for Adversarial Image Forensics 

• Machine Learning-based Image Forensics
  • Conventional Neural Network (CNN)
  • Support Vector Machine (SVM)
• Image Forensics
  • Coding-based
  • Editing-based
  • Acquisition-based
• Anti-Counter based Forensics (Adversary-Aware Detectors)
  • One Class Classifier
  • Data Randomization
  • GAN Defense
  • Defense Layer
  • Ensemble Scheme
• Counter based Forensics (perfect and limited knowledge)
  • Universal Attack
  • Laundering Attack
  • Surrogate Detector

Similar to machine learning techniques, deep learning techniques also attract the attention of developers. Further, it is moving the researchers in the direction of new algorithms. Further, Convolutional neural networks (CNNs) algorithms give prominent results for extracting significant features automatically by the dynamic learning process. As a result, it addresses the following issues in image forensics,  

• Camera Model Detection
• Manipulation Identification 

Last but not least, here we have presented you the procedure to be followed in the cyber-forensics investigation based on deep learning algorithms.

Steps in Cyber-based Forensic Investigation using Deep Learning

• At first, initialize the event
• Next, identify the PDE data sources
• Then, perform data collection, storage, analysis, and interpretation
• After that, report the forensic data
• At last, take effective decision

Overall, we have uncountable novelty assured Digital Forensics Project Ideas for creating a masterpiece of research in your final year projects/research profession. Also, we extend our helping hand in the development phase to effectively implement your research thought into the practice model to yield accurate results. So, make a bond with us to reach your goal as soon as possible with satisfactory results.