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A Taxonomic Classification of Insider Threats: Existing Techniques, Future Directions & Recommendations

Journal of Cyber Security and Mobility 2023年第2期12卷 221-252页

作者： Rauf, Usman Mohsen, Fadi Wei, Zhiyuan Dept. of Math. & Computer Science Mercy College NY United States Information Systems Group Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen9712 CP Netherlands

In the last two decades, the number of rapidly increasing cyber incidents (i.e., data theft and privacy breaches) shows that it is becoming enormously difficult for conventional defense mechanisms and architectures to neutralize modern cyber threats in a real-time situation. Disgruntled and rouge employees/agents and intrusive applications are two notorious classes of such modern threats, referred to as Insider Threats, which lead to data theft and privacy breaches. To counter such state-of-the-art threats, modern defense mechanisms require the incorporation of active threat analytics to proactively detect and mitigate any malicious intent at the employee or application level. Existing solutions to these problems intensively rely on co-relation, distance-based risk metrics, and human judgment. Especially when humans are kept in the loop for access-control policy-related decision-making against advanced persistent threats. As a consequence, the situation can escalate and lead to privacy/data breaches in case of insider threats. To confront such challenges, the security community has been striving to identify anomalous intent for advanced behavioral anomaly detection and auto-resiliency (the ability to deter an ongoing threat by policy tuning). Towards this dimension, we aim to review the literature in this domain and evaluate the effectiveness of existing approaches per our proposed criteria. According to our knowledge, this is one of the first endeavors toward developing evaluation-based standards to assess the effectiveness of relevant approaches in this domain while considering insider employees and intrusive applications simultaneously. There have been efforts in literature towards describing and understanding insider threats in general. However, none have addressed the detection and deterrence element in its entirety, hence making our contribution one of a kind. Towards the end of this article, we enlist and discuss the existing data sets. The data sets can help

关键词： Machine learning

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(POSTER) Insights from Executing TinyML Models on Smartphones and Microcontrollers 19

(POSTER) Insights from Executing TinyML Models on Smartphone...

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19th Annual International Conference on Distributed Computing in Smart systems and the Internet of Things, DCOSS-IoT 2023

作者： Singh, Harman M. Agashe, Shrishailya Jain, Shreyans Ghosh, Surjya Challa, Aditya Danda, Sravan Sen, Sougata Bits Pilani K K Birla Goa Campus Dept. of Computer Science and Information Systems India

ISBN: (纸本)9798350346497

In this paper, we empirically compare the system-level performances of executing a machine learning task on a resource-constrained IoT device and compare its performance to offloading the task to a more capable device, a smartphone. Our results indicate that although the resource-constrained device cannot run complex machine learning models, they can provide reasonable accuracy using similar models that can load on their memory. For running simpler models on the microcontroller, the best case accuracy for the machine learning task was 94.32% (SD: 1.7%). Furthermore, local computation resulted in almost 50% lesser current draw as compared to the offloading. These observations make a case for adopting an adaptive approach to ensure that applications meet the energy-accuracy-latency balance. © 2023 IEEE.

关键词： Microcontrollers

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Design of a Graduate level Software Engineering Program with a Product Perspective and a Product Management Specialization 35

Design of a Graduate level Software Engineering Program with...

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35th IEEE International Conference on Software Engineering Education and Training, CSEE and T 2023

作者： Pawar, Pravin Balasubramaniam, Sundar Ramachandran, Anita Bits Pilani Dept. of Computer Science & Information Systems Pune India Independent Consultant Bangalore India

ISBN: (纸本)9798350322026

While Software Engineering practice in the industry had matured well over the second half of the twentieth century, the first two decades of this millennium have witnessed disruptive growth of the field arising out of the evolution of new problem domains (e.g., intelligent applications and data management) as well as diverse deployment patterns (e.g., cloud, mobile and embedded devices). More subtle and impactful for practitioners is the change in perspective and approach-from a project-driven lifecycle to a product-driven lifecycle of software. Academic programs have kept up with the former set of changes as evidenced in curricular aspects or components such as DevOps, Mobile Application Development, Cloud-Native Application Development, Data Engineering, Big Data systems, Software Engineering for AI, etc. But there is a distinct lack of representation of the product perspective or approach and the emerging role of Product Management in typical University-level Software Engineering programs and curricula. We propose to address this gap by identifying-and then incorporating into a curriculum-the following:(i)requirements and features of a Software Product Life Cycle,(ii)practices of a product-driven approach to Software Engineering, and(iii)competencies of a Software Product *** show how these aspects can be addressed by a graduate level Software Engineering program with an optional specialization in Software Product Management targeted at practicing Software Engineers. We present the design of such a program in sufficient detail along with validation from industry and comparison with other programs. © 2023 IEEE.

关键词： Curricula

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Architecture development of middleware and API for IOT-based Red Onion farming

Architecture development of middleware and API for IOT-based...

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2023 International Seminar on Application for Technology of information and Communication, iSemantic 2023

作者： Steven, Alvin Suharnawi Alzami, Farrikh Saputra, Filmada Ocky Megantara, Rama Aria Andono, Pulung Nurtantio Universitas Dian Nuswantoro Dept. of Information Systems Indonesia Universitas Dian Nuswantoro Dept. of Information Engineering Indonesia Universitas Dian Nuswantoro Faculty of Computer Science Indonesia

ISBN: (纸本)9798350339215

IoT plays a crucial role in transforming the agricultural industry by offering diverse use cases starting from crop monitoring and precision farming to yield optimization. The fundamental reason why the agricultural community benefits immensely from IoT is due to its capacity to gather real-time data straight from their fields. Farming requires considerable attention, and wireless sensor networks enable farmers to deploy IoT devices throughout various parts of their farm so they can obtain information on soil moisture levels, temperature, humidity, among other essential parameters that are integral for effective agriculture management. This gathered data empowers farmers with accurate weather forecasts through machine learning techniques which assist them in making informed decisions related to planting or harvesting of crops - vital components critical for successful outcomes towards better yields. Moreover, middleware architectures/APIs developed specifically for IOT-based red onion farming utilize cloud computing services wherein these enlightening patterns generated get stored safely using analytics tools & automated systems. These intensify insights derived as it simplifies accessing important metrics aiding ease while analyzing historical trends advantageously helping make prudent future course corrective measures concerning planting/harvesting schedules based entirely on solid empirical evidence combined with artificial intelligence ensuring unprecedented efficiency gains and higher returns than previously achievable without technology guidance. © 2023 IEEE.

关键词： Crops

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A Sequential Pattern Mining Approach for Situation-Aware Human Activity Projection

A Sequential Pattern Mining Approach for Situation-Aware Hum...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： D'Aniello, Giuseppe Falcone, Roberto Gaeta, Matteo Rehman, Zia Ur Fortino, Giancarlo University of Salerno Dept. Information and Electrical Engineering and Applied Mathematics SA Fisciano Italy University of Calabria Dept. Computer Engineering Modeling Electronics and Systems Cs Rende Italy

ISBN: (纸本)9781665410205

Human activity prediction has become increasingly prevalent in a plethora of time-critical applications. To realize accurate identification and prediction of human behaviour, we propose a situation-aware wearable computing system. A wearable computing system has the capability to perceive, comprehend and project situations by analyzing the human behavioral patterns in different environments. In particular, this work proposes a situation-aware human activity prediction (SA-HAP) approach based on sequential pattern mining that aims to anticipate future activities and tailor its responses according to situations by analyzing frequent sequential patterns and their correlations to understand how these situations are interrelated. The approach not only improves prediction accuracy but also provide the foundation for a more informed decision-making process, as the projected situations can be explained using the identified behavioral patterns. The approach is compared with other traditional techniques for activity prediction (LSTM and HMM), achieving better performance on the Extrasensory dataset. © 2024 IEEE.

关键词： Prediction models

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Mobile-Based Monitoring Application for Self-Isolation of COVID-19 Patients 6

Mobile-Based Monitoring Application for Self-Isolation of CO...

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6th International Conference on computer and Informatics Engineering, IC2IE 2023

作者： Miranda, Eka Zakiyyah, Alfi Yusrotis Richard Arvuni, Mediyana Kumbangsila, Meyske Dian Sano, Albert Verasius School of Information Systems Bina Nusantara University Dept. of Information Systems Karawang Indonesia School of Computer Science Bina Nusantara University Dept. of Mathematics Jakarta Indonesia Medical Doctor Community Health Service Jakarta Indonesia School of Computer Science Bina Nusantara University Dept. of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350345162

This researcher intended to create a mobile-based Covid-19 patient monitoring application for primary health care as a safeguard for public health services to answer the research question of how to build a mobile-based monitoring application for self-isolation of Covid-19 patients for medical doctor view. Patients could be adequately monitored by doctors while self-isolating with this application. The Sawah Besar primary health care center in central Jakarta served as our research subject. We employed the Agile Design Science Research Methodology (ADSRM) during our study and development of this application. Following that, we evaluated our application result using the user acceptability technique and estimated the readiness of our application result using the Indonesian Ministry of Research, technological, and Higher Education (Ristekdikti) framework's technological readiness level (TKT). The evaluation found that a medical doctor accepted our application to help them with their work of monitoring Covid-19 patients' self-isolation. Furthermore, Based on the TKT framework, our application achieved level 5, which indicated that our application validated components/subsystems in a relevant context. © 2023 IEEE.

关键词： agile design science research methodology covid-19 primary health care self-isolation

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Enhancing Human Resources Management with Blockchain Technology: A Case Study Approach 3

Enhancing Human Resources Management with Blockchain Technol...

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3rd International Conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Indiyati, Dian Rahardja, Untung Rusilowati, Umi Millah, Shofiyul Faturahman, Adam Fitriani, Anandha Telkom University School of Economics and Business Bandung Indonesia Universiti Teknologi Malaysia Dept. of Computer Science Johor Malaysia Pamulang University Dept. of Management South Tangerang Indonesia University of Raharja Dept. of Information Systems Tangerang Indonesia University of Raharja Dept. of Computer Systems Tangerang Indonesia Cai Sejahtera Indonesia0 Dept. of Digital Business Tangerang Indonesia

ISBN: (纸本)9798350367492

Blockchain technology has emerged as a transformative force in various sectors, including Human Resources (HR), promising enhanced security, transparency, and efficiency. The objective of this study is to explore the integration of blockchain in HR through a comprehensive case study analysis. Methodologically, the research employs Structural Equation Modeling (SEM) facilitated by SmartPLS, investigating the impact of blockchain adoption on data security enhancement, transparency, trust, efficiency in HR processes, and ultimately, employee satisfaction. A survey of 200 HR professionals was conducted to capture insights into their perceptions and experiences with blockchain integration. The results indicate a significant shift in HR management practices, where blockchain adoption not only improves data security but also fosters transparency and trust within HR processes. Additionally, the study highlights blockchain's role in streamlining HR operations, leading to increased efficiency and higher employee satisfaction. However, challenges in implementation and adaptation persist. The conclusion emphasizes the necessity for HR departments to embrace blockchain technology, recognizing its potential to revolutionize traditional HR practices. By leveraging blockchain's capabilities, organizations can mitigate data breaches, enhance process efficiency, and foster a more engaged workforce. This research adds to the growing body of literature on blockchain in HR, providing valuable insights and recommendations for organizations aiming to harness blockchain for HR innovation and optimization. © 2024 IEEE.

关键词： and Transparency Blockchain Adoption Data Security Enhancement Efficiency in HR Processes Employee Satisfaction

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Human Activity Recognition in Free Living Using a Wearable Sensor: A Two-Stage Approach 12

Human Activity Recognition in Free Living Using a Wearable S...

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12th International Conference on Awareness Science and Technology, iCAST 2023

作者： Li, Tianhui Zhou, Xue Kokubun, Kota Chen, Wenxi Division of Information System The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer and Information Systems The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer Science and Engineering The University of Aizu Aizu-Wakamatsu Japan

ISBN: (纸本)9798350324693

A novel two-stage approach for human activity recognition (HAR) using a wearable sensor is proposed in this study. The goal is to achieve both coarse-level and fine-level recognition of activities. The study focuses on five common activities: desk-working, driving, walking, downstairs, and upstairs. Three-axis acceleration signals were collected using a wrist-worn accelerometer sensor, and the activities were annotated during the participant’s daily routines. The acceleration data were preprocessed through segmentation, feature extraction, and normalization. In the first s tage, a t raditional m achine learning model (decision tree) was used for coarse-level classification, distinguishing between activities with exercise and without exercise. In the second stage, deep learning models were employed for fine-level classification to recognize specific activities within the coarse classes. The performance of the models was evaluated using accuracy, sensitivity, and specificity. T he p roposed approach showed promising results with accuracies of 93.53%, 93.52%, 85.70%, 98.11%, and 85.91% respectively for desk-working, driving, walking, downstairs, and upstairs, demonstrating the effectiveness of the two-stage strategy for HAR. The proposed two-stage approach outperforms the one-stage method (decision tree classifier a nd d eep l earning m odel), p articularly i n imbalanced data, achieving a graceful equilibrium between sensitivity and specificity. T he s tudy h ighlights t he i mportance o f considering the complexity and variability of daily activities for accurate classification a nd r esource optimization. © 2023 IEEE.

关键词： Wearable sensors

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Evaluation of Meteorological Factors’ Effect on Daily Heart Rate Variability Over Five Years 12

Evaluation of Meteorological Factors’ Effect on Daily Heart...

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12th International Conference on Awareness Science and Technology, iCAST 2023

作者： Kokubun, Kota Li, Tianhui Chen, Wenxi Dept. of Computer and Information Systems The University of Aizu Aizu-Wakamatsu Japan Division of Information System The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer Science and Engineering The University of Aizu Aizu-Wakamatsu Japan

ISBN: (纸本)9798350324693

The aim of this study is to investigate the effect of meteorological factors on heart rate variability (HRV) derived from daily electrocardiogram (ECG) data. Daily meteorological data were obtained from the Japan Meteorological Agency’s database. Daily ECG data were measured while bathing for five y ears. T he s ubject w as a h ealthy m ale i n h is fi fties. After collecting ECG data, R-R intervals were calculated to perform HRV analysis in time domain and frequency domain. The evaluation of link between meteorological factors and HRV parameters was realized by utilizing meteorological factors’ importance calculated by Random Forest, and Steel-Dwass significant difference analysis of the values. Additionally, the evaluation was also performed by analyzing the obtained meteorological factors’ importance values using Granger Causality test. In Steel-Dwass test, several significant d ifferences (p © 2023 IEEE.

关键词： Electrocardiograms

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Security in remote access, based on Zero Trust Model concepts and SSH authentication with signed certificates 11

Security in remote access, based on Zero Trust Model concept...

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Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies XI 2022

作者： Iță, Cristina-Raluca Constantinescu, Rodica-Claudia Vlădescu, Alexandru Alexandrescu, Bogdan Information and Computer Systems Engineering POLITEHNICA University of Bucharest Romania Applied Electronics and Information Engineering Dept. POLITEHNICA University of Bucharest Romania

ISBN: (纸本)9781510660939

This paper aims to resume the information on the various ways in which security can be achieved when it comes to accessing external resources from the outside through company devices or personal devices. When planning security policies, it is essential to start with the idea that anything outside is exposed to the risk of infection. We will analyze the Zero Trust model and other security concepts in order to use them for remote access. The model has been designed to adapt to the modern needs of the workforce and employers, including remote work in terms of maximum cyber security, minimizing the risk of resource exploitation (people, devices, applications or data). In order to make the transition to such a model, this paper will implement and test a solution for remote management of resources (applications, servers), which implements some of the principles of Zero Trust architectures, starting from the classic version SSH (Secure Shell) access. The solution involves accessing, securing and authorizing a secure virtual machine via SSH, and then securing access to production resources. The technical mechanism by which these operations are performed presupposes that after authentication on the buffer machine a user certificate is automatically requested which will be signed by a certification authority. This certificate contains the group to which the operator belongs so that, by presenting this certificate, it is allowed to authenticate, authorize and audit access to the resources that will be managed by the user in that session. © 2023 SPIE.

关键词： Authentication

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