Design and Development of Ternary-Based Anomaly Detection in Semantic Graphs Using Metaheuristic Algorithm

At present, the field of homeland security faces many obstacles while determining abnormal or suspicious entities within the huge set of data. Several approaches have been adopted from social network analysis and data mining; however, it is challenging to identify the objective of abnormal instances within the huge complicated semantic graphs. The abnormal node is the one that takes an individual or abnormal semantic in the network. Hence, for defining this notion, a graph structure is implemented for generating the semantic profile of each node by numerous kinds of nodes and links that are associated to the node in a specific distance via edges. Once the graph structure is framed, the ternary list is formed on the basis of its adjacent nodes. The abnormalities in the nodes are detected by introducing a new optimization concept referred to as biogeography optimization with fitness sorted update (BO-FBU), which is the extended version of the standard biogeography optimization algorithm (BBO). The abnormal behavior in the network is identified by the similarities among the derived rule features. Further, the performance of the proposed model is compared to the other classical models in terms of certain performance measures. These techniques will be useful to detect digital crime and forensics.

A Survey on Digital Forensic Investigation Practitioners Approach and Challenges

Digital crimes are taking place over the entire world. For any digital crime which commit at any part of world, computer or any electronic devices are used. The devices which are used to commit the crime are useful evidences which must be identified and protected for further use. The crimes involving electronic devices are called as cyber-crime. To investigate such crimes, a scientific procedures needs to be followed. The data collection, analysis, preservation and presentation of digital evidence is must in order investigate the cybercrime. This paper highlights the practices that are used worldwide in the investigation process of cyber-crime. Keywords: Digital Forensics, Analysis, Investigation, models of investigation.

Detecting Phishing Websites Using an Efficient Feature-based Machine Learning Framework

Phishing is a form of digital crime where spam messages and spam sites attract users to exploit sensitive information on fishermen. Sensitive information obtained is used to take notes or to access money. To combat the crime of identity theft, Microsoft's cloud-based program attempts to use logical testing to determine how you can build trust with the characters. The purpose of this paper is to create a molded channel using a variety of machine learning methods. Separation is a method of machine learning that can be used effectively to identify fish, assemble and test models, use different mixing settings, and look at different mechanical learning processes, and measure the accuracy of the modified model and show multiple measurement measurements. The current study compares predictive accuracy, f1 scores, guessing and remembering multiple machine learning methods including Naïve Bayes (NB) and Random forest (RF) to detect criminal messages to steal sensitive information and improve the process by selecting highlighting strategies and improving crime classification accuracy. to steal sensitive information.

Cyber Crime Investigation and Preventing in Reference for Cloud Forensics : A Review

We are aware that cloud computing evolves as a transformative and No Doubt helpful field for futures generations on account of its several economic benefits in each domain as well as commercial, public, governmental, organizational, etc. Cloud forensics one of the most important areas within the developing field is that the means that investigators conduct researches in the relevant ways in which a digital crime took place over the cloud. This area is known as cloud forensics. Cloud forensics is a relevant field that works on all of this problem. This paper gives an overall research perspective of cloud forensics including its logging measures that need forensics challenges and what is the help of the cybercrime investigation and preventing for cloud forensics and the currently available solutions.

Palingenesis of Criminal Law in the Conditions of Digital Reality

The article proves that the influence of exponential and combinatorial technological changes has led to a crisis of criminal law, which is expressed in the inability to perform its basic functions due to the permanent and dynamic external environmental impact. The author identifies the following fundamental provisions that should be relied on when making decisions on the modernization of criminal law: the emergence of a new (informational) method of committing a crime does not a priori indicate that it is more dangerous than the traditional one, but in many respects indicates the problem of lag social control from the development of society and changes in crime; the adaptation of the norms of the criminal law to the conditions of the information society should not be associated with the construction of “digital twins” of traditional criminal law prohibitions; the introduction of appropriate amendments to the content of the norms is justified only in cases where the adaptive capacity of criminal legislation to manifestations of digital crime exhausts itself; the recognition of the use of information technologies as a qualifying feature of a crime in general must comply with the criteria for differentiating criminal liability justified in science. The article separately substantiates that the emergence of a “digital personality” will complete the beginning of the transition from the traditional criminal law of the industrial society of the 20th century towards the criminal law of the digital world of the 21th century (criminal law 2.0). First of all, this is due to the fact that artificial intelligence and “digital personality” will fundamentally change the scope of criminal law protection.

Penerapan Metode Localization Tampering dan Hashing untuk Deteksi Rekayasa Video Digital

The development of digital video technology which is increasingly advanced makes digital video engineering crimes prone to occur. The change in digital video has changed information communication, and it is easy to use in digital crime. One way to solve this digital crime case is to use the NIST (National Institute of Standards and Technology) method for video forensics. The initial stage is carried out by collecting data and carrying out the process of extracting the collected results. A local hash and noise algorithm can then be used to analyze the resulting results, which will detect any digital video interference or manipulation at each video frame, and perform hash analysis to detect the authenticity of the video. In digital video engineering, histogram analysis can be performed by calculating the histogram value metric, which is used to compare the histogram values ​​of the original video and video noise and make graphical comparisons. The results of the difference in frame analysis show that the results of the video show that the 2nd to 7th frames experience an attack while the histogram calculation of the original video centroid value and video tampering results in different values ​​in the third frame, namely with a value of 124.318 and the 7th frame of the video experiencing a difference in the value of 105,966 videos. tampering and 107,456 in the original video. Hash analysis on video tampering results in an invalid SHA-1 hash, this can prove that the video has been manipulated.

Two-Level Blockchain System for Digital Crime Evidence Management

Digital evidence, such as evidence from CCTV and event data recorders, is highly valuable in criminal investigations, and is used as definitive evidence in trials. However, there are risks when digital evidence obtained during the investigation of a case is managed through a physical hard disk drive until it is submitted to the court. Previous studies have focused on the integrated management of digital evidence in a centralized system, but if a centralized system server is attacked, major operations and investigation information may be leaked. Therefore, there is a need to reliably manage digital evidence and investigation information using blockchain technology in a distributed system environment. However, when large amounts of data—such as evidence videos—are stored in a blockchain, the data that must be processed only within one block before being created increase, causing performance degradation. Therefore, we propose a two-level blockchain system that separates digital evidence into hot and cold blockchains. In the criminal investigation process, information that frequently changes is stored in the hot blockchain, and unchanging data such as videos are stored in the cold blockchain. To evaluate the system, we measured the storage and inquiry processing performance of digital crime evidence videos according to the different capacities in the two-level blockchain system.

Akuisisi Bukti Digital Viber Messenger Android Menggunakan Metode National Institute of Standards and Technology (NIST)

Viber is one of the most popular social media in the Instant Messenger application category that can be used to send text messages, make voice calls, send picture messages and video messages to other users. As many as 260 million people around the world have used this application. Increasing the number of viber users certainly brings positive and negative impacts, one of the negative impacts of this application is the use of digital forensic crime. This research simulates and removes digital crime evidence from the viber application on Android smartphones using the National Institute of Standards Technology (NIST) method, which is a method that has work guidelines on forensic policy and process standards to ensure each investigator follows the workflow the same so that their work is documented and the results can be accounted for. This study uses three forensic tools, MOBILedit Forensic Express, Belkasoft and Autopsy. The results in this study show that MOBILedit Forensic Express gets digital evidence with a percentage of 100% in getting accounts, contacts, pictures and videos. While proof of digital chat is only 50%. Belkasoft gets digital evidence with a percentage of 100% in getting accounts, contacts, pictures and videos. While proof of digital chat is only 50%. For Autopsy does not give the expected results in the extraction process, in other words the Autopsy application gives zero results. It can be concluded that MOBILedit Forensic Express and Belkasoft have a good performance compared to Autopsy and thus this research has been completed and succeeded in accordance with the expected goals.

Body Shaming Through Social Media As a Digital Crime In The Era of Disruption

Digitalization has ushered in an era of disruption. The negative impact is body shaming. In the case of body shaming in Indonesia in 2018, “there were 966 cases of physical humiliation or body shaming handled by police from all over Indonesia throughout 2018. Most recently in 2019, public figures were also affected. No less surprising, this phenomenon does not only attack adults but also babies. The problem raised in this paper is what legal factors influence the rise of body shaming as a digital crime in the era of disruption. The approach method used is conceptual. In conclusion, the legal factors that influence the prevalence of body shaming are the substance of law and legal culture. In the aspect of legal substance, some areas have not been touched by current regulations, even though the legal realm is often used as a catalyst for digital body-shaming crimes. Meanwhile, in the aspect of legal culture, the problem of legal conflicts and low legal compliance are the main problems. To make matters worse, the attitude of the victim who prefers to ignore the treatment they receive without taking a fight justified by law makes the perpetrators of body shaming even wilder and more frontal, because law enforcers, as part of the legal structure, are unable to take action because this act falls under the complaint offense. Suggestions, improved regulations and the role of the press and the public to change the way they view body-shaming behavior

Anti- Forensics: The Tampering of Videos

In the context of forensic investigations, the traditional understanding of evidence is changing nowadays where most prosecutors, lawyers and judges heavily rely on multimedia substantiations. However, the evolution of easy-to-use media manipulating tools, made it very easy for almost any (technical) person to alter the content of a digital media (e.g. digital image, audio or video) without leaving any traces that can be detectable by human's basic perceptions. Therefore, the validity of the digital media can no longer be guaranteed which in turn leads to a serious problem regarding digital crime investigation. As there are tools which can tamper media, there are also ones that can do the reverse: detect the tampering. This paper sheds the light on the available anti-forensics tools. Experiments were done using some of these tools to detect tampered media – more specifically video tampering. Our experiments showed the efficiency of these tools by differentiating between original and altered evidences.