Non-Fungible Token Security

Non-fungible tokens (NFTs) are unique digital assets stored on the blockchain and is used to certify ownership and authenticity of the digital asset. NFTs were first created in 2014 while their popularity peaked between 2021 and 2022. In this paper, the authors dive into the world of Non-Fungible Tokens (NFTs), their history, the Future of NFTs, as well as the security concerns

SENTIMENT AND BEHAVIORAL ANALYSIS IN EDISCOVERY

A suspect or person-of-interest during legal case review or forensic evidence review can exhibit signs of their individual personality through the digital evidence collected for the case. Such personality traits of interest can be analytically harvested for case investigators or case reviewers. However, manual review of evidence for such flags can take time and contribute to increased costs. This study focuses on certain use-case scenarios of behavior and sentiment analysis as a critical requirement for a legal case’s success. This study aims to quicken the review and analysis phase and offers a software prototype as a proof-of-concept. The study starts with the build and storage of Electronic Stored Information (ESI) datasets for three separate fictitious legal cases using publicly available data such as emails, Facebook posts, tweets, text messages and a few custom MS Word documents. The next step of this study leverages statistical algorithms and automation to propose approaches towards identifying human sentiments, behavior such as, evidence of financial fraud behavior, and evidence of sexual harassment behavior of a suspect or person-of-interest from the case ESI. The last stage of the study automates these approaches via a custom software and presents a user interface for eDiscovery teams and digital forensic investigators

IoT Network Attack Detection using Supervised Machine Learning

Article originally published in International Journal of Artificial Intelligence and Expert SystemsThe use of supervised learning algorithms to detect malicious traffic can be valuable in designing intrusion detection systems and ascertaining security risks. The Internet of things (IoT) refers to the billions of physical, electronic devices around the world that are often connected over the Internet. The growth of IoT systems comes at the risk of network attacks such as denial of service (DoS) and spoofing. In this research, we perform various supervised feature selection methods and employ three classifiers on IoT network data. The classifiers predict with high accuracy if the network traffic against the IoT device was malicious or benign. We compare the feature selection methods to arrive at the best that can be used for network intrusion predictio

Combinatorial Multi-Access Coded Caching: Improved Rate-Memory Trade-off with Coded Placement

This work considers the combinatorial multi-access coded caching problem introduced in the recent work by Muralidhar \textit{et al.} [P. N. Muralidhar, D. Katyal, and B. S. Rajan, ``Maddah-Ali-Niesen scheme for multi-access coded caching,'' in \textit{IEEE Inf. Theory Workshop (ITW)}, 2021] The problem setting consists of a central server having a library of $N$ files and $C$ caches each of capacity $M$. Each user in the system can access a unique set of $r<C$ caches, and there exist users corresponding to every distinct set of $r$ caches. Therefore, the number of users in the system is $\binom{C}{r}$. For the aforementioned combinatorial multi-access setting, we propose a coded caching scheme with an MDS code-based coded placement. This novel placement technique helps to achieve a better rate in the delivery phase compared to the optimal scheme under uncoded placement, when $M> N/C$. For a lower memory regime, we present another scheme with coded placement, which outperforms the optimal scheme under uncoded placement if the number of files is no more than the number of users. Further, we derive an information-theoretic lower bound on the optimal rate-memory trade-off of the combinatorial multi-access coded caching scheme. Finally, using the derived lower bound, we show that the first scheme is optimal in the higher memory regime, and the second scheme is optimal if $N\leq \binom{C}{r}$.Comment: 15 pages and 5 figure

Smartphone Forensic Challenges

Article originally published in Internation Journal of Computer Science and SecurityGlobally, the extensive use of smartphone devices has led to an increase in storage and transmission of enormous volumes of data that could be potentially be used as digital evidence in a forensic investigation. Digital evidence can sometimes be difficult to extract from these devices given the various versions and models of smartphone devices in the market. Forensic analysis of smartphones to extract digital evidence can be carried out in many ways, however, prior knowledge of smartphone forensic tools is paramount to a successful forensic investigation. In this paper, the authors outline challenges, limitations and reliability issues faced when using smartphone device forensic tools and accompanied forensic techniques. The main objective of this paper is intended to be consciousness-raising than suggesting best practices to these forensic work challenges

Security in Drones

Drones are used in our everyday world for private, commercial, and government uses. It is important to establish both the cyber threats drone users face and security practices to combat those threats. Privacy will always be the main concern when using drones. Protecting information legally collected on drones and protecting people from the illegal collection of their data are topics that security professionals should consider before their organization uses drones. In this article, the authors discuss the importance of security in drones

Knowledge And Awareness of Needle Stick Injury Among Dental Students

Background: Needle Stick Injury(NSI) and Sharp Injuries are major hazards in transmission of infectious blood borne diseases among Health Care Workers and Medical students who are at a risk of injuries because of daily procedures in performing clinical activities in hospitals. To reduce the risk of increased growth rate of NSIs, there should be an essential need to improve and update knowledge of NSIs and its management by lectures and seminars. Aim: To assess the knowledge and awareness regarding sharp injuries amongst dental students. Materials and Methods: This cross-sectional survey study was conducted among 103 voluntarily participating dental students who were receiving their undergraduate clinical training in a private Dental College. Data was recorded on a Structured questionnaire to elicit knowledge and awareness towards Needle Stick Injuries. Statistical analysis was done by SPSS Software-23. Results: 76.7% Dental students experienced NSI. 57.28% students aren’t aware of the Universal Precaution Guidelines. Adequate number of students had good knowledge and awareness regarding Needle Stick Injury. In practice, a maximum number of students washed hands, used gloves, and recapped needles after use. Pearson chi square test was done and p value obtained for comparing the knowledge between male and female on the awareness of Universal Precaution Guidelines is 0.882(>0.5). Conclusion: Dental students require training and teaching regarding management of Needle Stick Injury and should be encouraged to report it to the concerned authority