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OLBR: Optimization of Location-Based Routing Protocols in Vehicular Ad Hoc Networks

OLBR: Optimization of Location-Based Routing Protocols in Ve...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Thangam, S. Srikar Reddy, M. Vivek Ullas, Karthik Khadar Jilani, N. Abdul Venkatesh, K. Janet Kumari, J. Jesy Saleem Raja, A. Amrita School of Computing Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India University of Technology and Applied Sciences-Shinas College of Computing and Information Sciences It Department Oman

ISBN: (纸本)9798350309140

The proposed work employs ns-3, SUMO, and NetAnim to create geographical routing in vehicular ad hoc networks (VANETs). The research attempts to assess the performance of three well-known protocols AODV, DSDV, and OLSR in VANET settings. Utilizing SUMO's realistic mobility models and NS3's simulation capabilities, the project simulates node communication, protocol behaviour, and vehicle movement. The main purpose is to know how well various routing techniques work in dynamic vehicular situations. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Comparative Analysis of Password Storage Security using Double Secure Hash Algorithm

Comparative Analysis of Password Storage Security using Doub...

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2022 IEEE North Karnataka Subsection Flagship International Conference, NKCon 2022

作者： Chethana, Savarala Charan, Sreevathsa Sree Srihitha, Vemula Radha, D. Kavitha, C.R. Amrita School of Computing Bengaluru Dept. of Computer Science & Engineering Amrita Vishwa Vidyapeetham India

ISBN: (纸本)9781665453424

Passwords are generally used to keep unauthorized users out of the system. Password hacking has become more common as the number of internet users has extended, causing a slew of issues. These problems include stealing the confidential information of a company or a country by adversaries which harm the economy or the security of the organization. Hackers often use password hacking for criminal activities. It is indispensable to protect passwords from hackers. There are many hacking methods such as credential stuffing, social engineering, traffic interception, and password spraying for hacking the passwords. So, in order to control hacking, there are hashing algorithms that are mostly used to hash passwords making password cracking more difficult. In this proposed work, different hashing algorithms such as SHA-1, MD-5, Salted MD-5, SHA-256, and SHA-512 have been used. And the MySQL database is used to store the hash values of passwords that are generated using various hash functions. It is proven that SHA is better than MD-5 and Salted MD-5. Whereas in the SHA family, SHA-512 and SHA-256 have their own benefits. Four new hashing functions have been proposed using the combination of existing algorithms like SHA-256, and SHA-512 namely SHA-256-with-SHA-256, SHA-256- With-SHA-512,SHA-512-With-SHA-512,and SHA-512- With-SHA-256. They provide strong hash value for passwords by which the security of passwords increases, and hacking can be controlled to an extent. © 2022 IEEE.

关键词： Hash functions

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Accounting for systemic risk in analysis of crisis scenarios 21

Accounting for systemic risk in analysis of crisis scenarios

引用

21st International ISCRAM Conference, ISCRAM 2024

作者： Gonzalez, Jose J. Abbas, Reem Paulsen, Sigurd University of Agder Kristiansand Norway Department of Computer Science and Software Engineering Auckland University of Technology Auckland New Zealand Dept. of Organization Crisis Management and Information Security Kristiansand Norway

systemic risk is ubiquitous in our increasingly globalised world owing to the interconnections within and across sectors. However, a review of National Risk Assessments performed in OECD member countries reveals that systemic risk is rarely mentioned, and it is never accounted for in those assessments. A powerful method accounts for systemic risk and identifies mitigating strategies using participatory modelling with stakeholders: strategy mapping with Strategyfinder. The risk model is represented as a directed graph consisting of risk nodes and directed edges (arrows) expressing causal influences. The method originated in the management of large, complex projects, and it has been applied to systemic risks in critical infrastructures and pandemics. We demonstrate the Strategyfinder method using a scenario describing a cyberattack on electronic communication infrastructure leading to serious consequences for health and lives. The scenario is borrowed from the report Analysis of Risk Scenarios by the Norwegian Directorate for Civil Protection. © 2024 Information systems for Crisis Response and Management, ISCRAM. All rights reserved.

关键词： Cascading effects Disaster risk reduction National Risk Assessments Risk scenarios Vicious cycles

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Integrating Network Security into Software Defined Networking (SDN) Architectures 2

Integrating Network Security into Software Defined Networkin...

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2nd IEEE International Conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Vadakkethil Somanathan Pillai, Sanjaikanth E Polimetla, Kiran University Of North Dakota School of Electrical Engineering and Computer Science Grand ForksND United States Adobe Inc. Dept. of Information Technology AustinTX United States

ISBN: (纸本)9798350317558

The decision for introduced green and cozy networking solutions has grown as the era continues to evolve. With centralized network control and programmability functions, software applications defined as Networking (SDN) have emerged as a promising method to address this call. But, as SDN architectures become vaster, the need for strong community protection turns into even extra important. Integrating community protection into SDN structure includes enforcing safety mechanisms straight away into the manipulate aircraft, considering actual-time-grained manipulation over community site visitors. This may be done through protection guidelines and policies that can be dynamically completed and updated via the centralized controller. With the aid of leveraging the programmable nature of SDN, network protection may be, without troubles, tailored to satisfy the changing hazard panorama. The open API in SDN also permits integration with gift-day protection answers, firewalls, and intrusion detection systems, similarly, to improving the community's overall safety. © 2024 IEEE.

关键词： Architecture Dynamically Networking Protection Technology Visitors

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Microgrid Using Intelligent Controlled DSTATCOM for Power Quality Enhancement 6

Microgrid Using Intelligent Controlled DSTATCOM for Power Qu...

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6th International Symposium on computer, Consumer and Control, IS3C 2023

作者： Tan, Kuang-Hsiung Li, Meng-Yang Hu, Chih-Chan Chung Cheng Institute of Technology National Defense University Dept. of Electrical and Electronic Engineering Taoyuan Taiwan National Central University Dept. of Electrical Engineering Chungli Taiwan National Chung-Shan Institute of Science and Technology System Manufacturing Center New Taipei Taiwan

ISBN: (纸本)9798350301953

A droop controlled microgrid with distribution static compensator (DSTATCOM) is developed to improve the power quality in this study. Due to the reactive power/voltage QV droop characteristic and the existence of the unbalanced, linear inductive and nonlinear loads, the power quality problems, including the voltage drop, unbalanced currents, lagging power factor (PF) and current harmonics, are very serious in the islanded microgrid. Moreover, owing to the instantaneous power following into or out of the DC-link capacitor of the DSTATCOM under load variation, the performance of the DSTATCOM for power quality improvement is seriously degenerated. Hence, to effectively improve the power quality of the droop controlled microgrid and the transient response of the DC-link voltage of the DSTATCOM under load variation, an online trained polynomial petri fuzzy neural network (PPFNN) controller is firstly proposed as the DC-link voltage controller to supersede the conventional proportional-integral (PI) controller in the DSTATCOM. The network structure and the online learning strategy of the proposed PPFNN are detailedly derived. Finally, the effectiveness of the DSTATCOM using the proposed PPFNN controller to improve the unbalanced currents, the total harmonic distortion (THD) reduction of the current and to compensate the reactive power for the voltage support and PF correction in the droop controlled microgrid is certified. © 2023 IEEE.

关键词： Power quality

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Semantic Role Labeling for Code-Switched Data 3

Semantic Role Labeling for Code-Switched Data

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Nikitha, M. Savaram, Padmaja Bandu, Sasidhar Saketh Keshav Memorial Institute of Technology Department of Cse Hyderabad India College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Dept. of Computer Science Al-Kharj Saudi Arabia Prince Sattam bin Abdulaziz University Dept. of English Al-Kharj Saudi Arabia University College of Engineering Osmania University Department of Aiml Hyderabad India

ISBN: (纸本)9798331518592

In natural language processing, pre-trained language models have shown significant promise in various linguistic tasks. This study investigates the efficacy of various pre-trained models, namely XLM-RoBERTa, M-BERT, and HING-MBERT, within an extensive classification framework encompassing semantic role labeling and part-of-speech tagging. The dataset was meticulously pre-processed to include tokenization, semantic role and POS tagging, and language ID encoding. The token vectors were then standardized in length through padding or truncation and fed into the models using tensor representations. Model training was executed with K-Fold cross-validation, leveraging an AdamW optimizer to fine-tune the weights over 5 epochs. The evaluation metrics-precision, recall, accuracy, and F1 score-were employed to assess model efficacy. Among the models assessed, HING-MBERT demonstrated superior performance across all metrics, achieving the highest precision (0.7843), recall (0.7168), accuracy (0.9239), and F1 score (0.7985). This suggests its enhanced capability in semantic understanding and classification tasks compared to XLM-RoBERTa and M-BERT. © 2024 IEEE.

关键词： Semantics

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Dataset Construction and Classification Based on Pre-trained Models for Opinion Holder Detection 12

Dataset Construction and Classification Based on Pre-trained...

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12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022

作者： Al-Mahmud, Al Shimada, Kazutaka Kyushu Institute of Technology Dept. of Computer Science and Systems Engineering Fukuoka850-8502 Japan

ISBN: (数字)9781665497558

ISBN: (纸本)9781665497558

Nowadays, it is getting increased in the massive amount of internet users. People express subjective thinking (i.e., opinion) implicitly and explicitly on online platforms such as Facebook, Twitter, Amazon product reviews, etc. Opinion holders are the people or entities who express opinions implicitly and explicitly on the online platform. With the increasing trends of online opinion mass information, it is impossible to detect them manually. For this reason, an automatic approach for opinion holder detection is essential. Opinion holder detection is useful to detect specific person's/entity's concerns about a particular topic, product, or problem. Opinion holder detection consists of two steps: the presence of opinion holders in text and identification of opinion holders. In this paper, we focus on the first step, namely the presence of opinion holders in text. We handle this task as a binary classification problem: INSIDE or OUTSIDE. At first, we prepare a new English dataset for this task. Then, we apply two types of pre-trained models, BERT and DistilBERT, to the INSIDE/OUTSIDE classification task. BERT is a transformer-based pre-trained language model. DistilBERT is a small, fast, cheap, and light model based on knowledge distillation from the BERT architecture. As to the binary classification task, we employ a logistic regression model on the top layer of the pre-trained models. We compare the language models employed in our experiment in terms of the F1 score and accuracy. The experimental result shows that DistilBERT obtained superior performance among the models: 0.901 on the F1 score and 0.924 on the accuracy. © 2022 IEEE.

关键词： Distillation

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Early Detection of Type 2 Diabetes Using Oversampling-Based Ensemble Learning for Classification of Imbalanced Dataset

Early Detection of Type 2 Diabetes Using Oversampling-Based ...

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International Conference on Signal Processing, Communication, Power and Embedded system (SCOPES)

作者： P Rajasekhar Sridhar Mourya Narasimha Reddy Bathala G Lavanya S Gayatri Munni Shaik Dept. of Computer Science Engineering Vignan's Institute of engineering for women Visakhapatnam India Dept. of Information Technology Malla Reddy University Hyderabad India Dept. of Computer Science Engineering Malla Reddy University Hyderabad India

ISBN: (数字)9798331506452

ISBN: (纸本)9798331506469

Diabetes is marked by high blood glucose levels and adversely affects various body systems, notably cardiovascular, renal, and visual. Early diagnosis via automated screening is vital for operative treatment. Advances in machine learning (ML), particularly have enhanced diabetes diagnosis but one of the major issues when working with medical datasets is class imbalance. Oversampling is crucial in the medical field to address class imbalance, ensuring that models can effectively learn patterns from minority classes, such as rare diseases or conditions. While feature selection and hyperparameter tuning optimize model performance, oversampling directly improves the model's ability to detect and predict critical, but less frequent, medical events, reducing bias toward the majority class. This paper introduces an oversampling based approach for using ensemble learning (EL) with decision tree as meta-estimators to address data imbalance. To balance the classes and enhance the accuracy of classification performance KMeans SMOTE Boost, SMOTE Bagging, Over Boost, and Over Bagging classifier strategies are been used on training data. This study identifies the most effective combinations of oversampling techniques and classifiers, and finds that using oversampling methods consistently leads to better classification results. These results highlight the effectiveness of oversampling with EL system in diabetes classification on Type 2 Diabetes dataset.

关键词： Visualization Accuracy Training data Signal processing algorithms Predictive models Diabetes Ensemble learning Medical diagnostic imaging Bagging Tuning

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Stealth: A Highly Secured End-to-End Symmetric Communication Protocol

Stealth: A Highly Secured End-to-End Symmetric Communication...

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2022 International Symposium on Networks, computers and Communications, ISNCC 2022

作者： Patgiri, Ripon Muppalaneni, Naresh Babu National Institute of Technology Silchar Dept. Computer Science & Engineering Assam Cachar788010 India

ISBN: (数字)9781665485449

ISBN: (纸本)9781665485449

Symmetric key cryptography is applied in almost all secure communications to protect all sensitive information from attackers, for instance, banking, and thus, it requires extra attention due to diverse applications. Moreover, it is vulnerable to various attacks, for example, cryptanalysis attacks. Cryptanalysis attacks are possible due to a single-keyed encryption system. The state-of-the-art symmetric communication protocol uses a single secret key to encrypt/decrypt the entire communication to exchange data/message that poses security threats. Therefore, in this paper, we present a new secure communication protocol based on Diffie-Hellman cryptographic algorithms, called Stealth. It is a symmetric-key cryptographic protocol to enhance the security of modern communication with truly random numbers. Additionally, it applies a pseudo-random number generator. Initially, Stealth uses the Diffie-Hellman algorithm to compute four shared secret keys. These shared secret keys are used to generate four different private keys to encrypt for the first block of the message for symmetric communication. Stealth changes its private keys in each communication, making it very hard to break the security protocol. Moreover, the four shared secret keys create additional complexity for the adversary to overcome, and hence, it can provide highly tight security in communications. Stealth neither replaces the existing protocol nor authentication mechanism, but it creates another security layer to the existing protocol to ensure the security measurement's tightness. © 2022 IEEE.

关键词： Cryptography

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OCSK-SMOTE: An improved minority oversampling technique for unbalanced dataset using One-Class SVM and K-means 2

OCSK-SMOTE: An improved minority oversampling technique for ...

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2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Pandey, Utkarsh Shukla, Sanyam Wadhvani, Rajesh Maulana Azad National Institute of Technology Dept. of Computer Science and Engineering Bhopal462003 India

ISBN: (纸本)9781665437899

Classification of dataset that have an imbalance in there classes still a challenge to the real world problem and a lot of research has been done and continuously being done to get a resolution to this problem, SMOTE has achieved tremendous triumph in this regard and in this paper we have focused on extension of SMOTE and developed an algorithm to overcome its shortcomings, The Highlight of the algorithm is that it removes the outliers from the Dataset and then proceeds to oversampling by first dividing into clusters of majority and minority and then oversampling only in clusters where there is more minority data so to also tackle data distribution problem of class imbalance, to test the proposed method it has been tested on 10 UCI datasets with varying degree of class imbalance ratio. © 2022 IEEE.

关键词： Classification (of information)

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