• Journal of Information Processing Systems
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• v.14 no.2
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• pp.346-376
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• 2018

Digital forensics is a vital part of almost every criminal investigation given the amount of information available and the opportunities offered by electronic data to investigate and evidence a crime. However, in criminal justice proceedings, these electronic pieces of evidence are often considered with the utmost suspicion and uncertainty, although, on occasions are justifiable. Presently, the use of scientifically unproven forensic techniques are highly criticized in legal proceedings. Nevertheless, the exceedingly distinct and dynamic characteristics of electronic data, in addition to the current legislation and privacy laws remain as challenging aspects for systematically attesting evidence in a court of law. This article presents a comprehensive study to examine the issues that are considered essential to discuss and resolve, for the proper acceptance of evidence based on scientific grounds. Moreover, the article explains the state of forensics in emerging sub-fields of digital technology such as, cloud computing, social media, and the Internet of Things (IoT), and reviewing the challenges which may complicate the process of systematic validation of electronic evidence. The study further explores various solutions previously proposed, by researchers and academics, regarding their appropriateness based on their experimental evaluation. Additionally, this article suggests open research areas, highlighting many of the issues and problems associated with the empirical evaluation of these solutions for immediate attention by researchers and practitioners. Notably, academics must react to these challenges with appropriate emphasis on methodical verification. Therefore, for this purpose, the issues in the experiential validation of practices currently available are reviewed in this study. The review also discusses the struggle involved in demonstrating the reliability and validity of these approaches with contemporary evaluation methods. Furthermore, the development of best practices, reliable tools and the formulation of formal testing methods for digital forensic techniques are highlighted which could be extremely useful and of immense value to improve the trustworthiness of electronic evidence in legal proceedings.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.51-60
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• 2019

The purpose of this study is to examine the issues that can be expected in the smart intelligent information society led by artificial intelligence and the Internet of Things, and how to resolve the issues in terms of PR.The results were as follows. First, there are three major issues that can be expected Second, in order to resolve the issue, it is necessary to prepare and carry out a public interest campaign to create and participate in a new paradigm for the alienated public. Third, welfare technology can be considered as an alternative to the issues.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.399-408
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• 2021

Information security reports four types of basic attacks on information. One of the attacks is named as fabrication. Even though mobile devices and applications are showing its maturity in terms of performance, security and ubiquity, location-based applications still faces challenges of quality of service, privacy, integrity, authentication among mobile devices and hence mobile users associated with the devices. There is always a continued fear as how location information of users or IoT appliances is used by third party LB Service providers. Even adversary or malicious attackers get hold of location information in transit or fraudulently hold this information. In this paper, location information fabrication scenarios are presented after knowing basic model of information attacks. Peer-to-Peer broadcast model of location privacy is proposed. This document contains introduction to fabrication, solutions to such threats, management of fabrication mitigation in collaborative or peer to peer location privacy and its cost analysis. There are various infrastructure components in Location Based Services such as Governance Server, Point of interest POI repository, POI service, End users, Intruders etc. Various algorithms are presented and analyzed for fabrication management, integrity, and authentication. Moreover, anti-fabrication mechanism is devised in the presence of trust. Over cost analysis is done for anti-fabrication management due to nature of various cryptographic combinations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.23-29
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• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.