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2024 International Conference on engineering and computing, ICECT 2024

作者： Fiza, Inbasat Khurshid, Fizza Fatima, Manahil Noor, Umara Rashid, Zahid International Islamic University Faculty of Computing and Information Technology Department of Software Engineering Islamabad Pakistan College of Engineering Seoul National University Technology Management Economics and Policy Program 1 Gwanak-Ro Gwanak-Gu Seoul08826 Korea Republic of

ISBN: (纸本)9798350349719

The ATT&CK MITRE framework serves as an expansive repository of adversary tactics, techniques, and procedures. Given the sheer volume of these intricate attack patterns, the conventional manual navigation method proves to be time-intensive and less efficient for security analysts. As a remedy, there arises a compelling necessity to present the rich content encapsulated within the ATT&CK MITRE repository through interactive visualizations. In this paper ATT&CKViz an interactive web-based cyber-Attack patterns visualization tool is presented that aims to empower security analysts with the ability to effortlessly explore the repository from diverse angles, which facilitates deep insights into cyber threats. The aim is to understand cyber threat efficiently with a timely response. The empirical evaluations depict that effectiveness and user-friendliness of ATT&CKViz. © 2024 IEEE.

关键词： Cybersecurity

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Sentiment Analysis in Social Media for Competitive Environment Using Content Analysis

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Computers, Materials & Continua 2022年第6期71卷 5603-5618页

作者： Shahid Mehmood Imran Ahmad Muhammad Adnan Khan Faheem Khan T.Whangbo Riphah School of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Engineering Gachon UniversitySeongnam13557Korea

Education sector has witnessed several changes in the recent *** changes have forced private universities into fierce competition with each other to get more students *** competition has resulted in the adoption of marketing practices by private universities similar to commercial *** get competitive gain,universities must observe and examine the students’feedback on their own social media sites along with the social media sites of their *** study presents a novel framework which integrates numerous analytical approaches including statistical analysis,sentiment analysis,and text mining to accomplish a competitive analysis of social media sites of the *** techniques enable local universities to utilize social media for the identification of the most-discussed topics by students as well as based on the most unfavorable comments received,major areas for improvement.A comprehensive case study was conducted utilizing the proposed framework for competitive analysis of few top ranked international universities as well as local private universities in Lahore *** results show that diversity of shared content,frequency of posts,and schedule of updates,are the key areas for improvement for the local *** on the competitive intelligence gained several recommendations are included in this paper that would enable local universities generally and Riphah international university(RIU)Lahore specifically to promote their brand and increase their attractiveness for potential students using social media and launch successful marketing campaigns targeting a large number of audiences at significantly reduced cost resulting in an increased number of enrolments.

关键词： Social media higher education sentiment analysis content analysis competitive analysis text mining

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Web Service QoS Prediction Based on Reputation and Location Aware Matrix Factorization 19

Web Service QoS Prediction Based on Reputation and Location ...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Chen, Fan Du, Yugen Zhong, Wenhao Wang, Hanting East China Normal University Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute Shanghai China

ISBN: (纸本)9798350346558

With the development of cloud computing and Internet technologies, the number of Web services has increased dramatically. It is increasingly difficult for users to locate applicable services among a large number of functionally equivalent candidates. Considering the high cost of time and resources, users cannot invoke all Web services to obtain the desired quality of service (QoS). Therefore, the problem of QoS prediction of Web services has attracted much attention in recent years. Although QoS is often used as a measure of Web service performance, the value of QoS may vary significantly between users depending on their network and geographical location. Furthermore, most traditional approaches perform QoS prediction directly based on historical QoS values provided by users. However, these historical QoS data may contain unreliable values from unreliable users, resulting in significantly lower prediction accuracy. To overcome the above limitations, we propose a reputation and location aware matrix factorization (RLMF) approach for QoS prediction of Web services in this paper. First, we cluster the users and calculate their reputation based on the clustering information through Dirichlet distribution. Then, we integrate the user's reputation and location information into the matrix factorization model to obtain more accurate prediction results. Additionally, we use Cauchy loss to measure the difference between the observed and predicted QoS values, which makes our approach robust to even outliers. We conducted experiments on a largescale dataset of 1,974,675 QoS values to evaluate our approach. The experimental results show that our approach performs better than state-of-the-art baseline approaches. © 2022 IEEE.

关键词： Forecasting

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A new hybrid teaching learning based Optimization -Extreme learning Machine model based Intrusion-Detection system

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Materials Today: Proceedings 2023年 80卷 2701-2705页

作者： Qahatan Alsudani, Mustafa Abbdal Reflish, Salah H. Moorthy, Kohbalan Mundher Adnan, Myasar Computer Techniques Engineering Department Faculty of Information Technology Imam Ja'afar Al-sadiq University Najaf Iraq Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang Kuantan Malaysia Islamic University Najaf Iraq Faculty of Engineering School of Computing Universiti Teknologi Malaysia Johor Bahru81310 Malaysia

Currently, effective Intrusion-detection systems (IDS) still represent one of the important security tools. However, hybrid models based on the IDS achieve better results compared with intrusion detection based on a single algorithm. But even so, the hybrid models based on traditional algorithms still face different limitations. This work is focused on providing two main goals;firstly, analysis based on the main methods and limitations of the most-recent hybrid model-based on intrusion detection, secondly, to propose a novel hybrid IDS model called TLBO-ELM based on the Firefly algorithm and Fast Learning Network. © 2021

关键词： Optimization

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Introducing on-chain graph data to consortium blockchain for commercial transactions

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Frontiers of Computer Science 2024年第2期18卷 255-257页

作者： Pengyi ZHANG Yuchen YUAN Jie SONG Yu GU Qiang QU Yongjie BAI Software College Northeastern UniversityShenyang 110819China School of Computer Science and Engineering Northeastern UniversityShenyang 110819China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Blockchain Lab Huawei Cloud Computing Technologies Co.Ltd.Shenzhen 518101China

1 Introduction A blockchain can be referred to as a distributed ledger[1].Nowadays,according to our previous work[2],the graphrelated blockchain grows efficiently in both academic studies and commercial *** data,algor... 详细信息

关键词： transactions ledge commercial

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Multi-authority (t,n) Threshold Identity-based Matchmaking Encryption 3

Multi-authority (t,n) Threshold Identity-based Matchmaking E...

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Ding, Xiangyu Shanghai Key Laboratory of Trustworthy Computing School of Software Engineering East China Normal University 3663 N. Zhongshan Rd. Shanghai200062 China

ISBN: (纸本)9781510666375

In this work, we propose a Multi-authority (t, n) Threshold Identity-based Matchmaking Encryption (MAT-IBME) scheme under the standard assumptions in the standard model, in which multiple authorities share the secrets for constructing users’ secret keys. The MAT-IBME scheme satisfies the requirement that the receiver can only get the decryption key with the "joint permission" of t ones among n authorities. Meanwhile, only when the identity of the sender satisfies the policy proposed by the receiver, and the identity of the receiver satisfies the policy proposed by the sender, the receiver can decrypt correctly. In this way, the scheme realizes precise ciphertext access control when deployed in cloud services. Security and performance analysis shows that MAT-IBME not only achieves authenticity security but also system-level robustness when no less than t authorities are alive in the system. © 2023 SPIE.

关键词： Cryptography

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EagerLog: Active Learning Enhanced Retrieval Augmented Generation for Log-based Anomaly Detection

EagerLog: Active Learning Enhanced Retrieval Augmented Gener...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Duan, Chiming Jia, Tong Yang, Yong Liu, Guiyang Liu, Jinbu Zhang, Huxing Zhou, Qi Li, Ying Huang, Gang School of Software and Microelectronics Peking University Beijing China Institute for Artificial Intelligence Peking University Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China National Key Laboratory of Data Space Technology and System Beijing China Alibaba Cloud Computing Company Hangzhou China

ISBN: (纸本)9798350368741

Logs record essential information about system operations and serve as a critical source for anomaly detection, which has generated growing research interest. Utilizing large language models (LLMs) within a retrieval-augmented generation (RAG) framework for log-based anomaly detection is an effective approach due to its strong generalization capabilities and efficient few-shot performance. However, the effectiveness of this method hinges on the quality of the knowledge source, which can be impacted by noise and changes within the software systems. Facing these problems, in this paper, we propose a novel log-based anomaly detection method named EagerLog, employing active learning to choose the logs for humans to label, thereby adding them to the knowledge source, thus enhancing the knowledge source and maintaining its quality. Our experiments on three open datasets (BGL, Thunderbird, Zookeeper) and one industrial dataset demonstrate that EagerLog can achieve 93.65% F1 score with approximately 10 labeled log sequences, surpassing existing methods by 15.32%. © 2025 IEEE.

关键词： Active Learning Anomaly Detection Log Analysis Retrieval Augmented Generation

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Secure software Development in Google Colab

Secure Software Development in Google Colab

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2023 IEEE World AI IoT Congress, AIIoT 2023

作者： Potluri, Tarun Shi, Yong Shahriar, Hossain Lo, Dan Parizi, Reza Chi, Hongmei Qian, Kai Kennesaw State University College of Computing and Software Engineering United States Florida A&M University Department of Computer and Information Sciences TallahasseeFL United States

ISBN: (纸本)9798350337617

software is said to be secure if it has been developed and designed with security as its top priority. This entails implementing secure coding practices, performing vulnerability testing and repair, as well as continuing to monitor and maintain the product to ensure the program remains secure over time. Since it may lessen the likelihood of security breakdowns, protect sensitive data and infrastructure, and maintain users' and clients' trust, secure software is essential. As technology advances and more aspects of our lives rely on it, the need for secure software has become more critical to preserving the safety and security of our digital environment. In this paper, we discuss vulnerabilities in software development such as SQL Injection and XSS Attacks, analyze the insecure cases related to them, and demonstrate the prevention approaches which are implemented in Google Colab with relevant libraries. © 2023 IEEE.

关键词： Sensitive data

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PEbfs: Implement High-Performance Breadth-First Search on PEZY-SC3s 24th

PEbfs: Implement High-Performance Breadth-First Search on P...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Guo, Weihao Wang, Qinglin Liu, Xiaodong Peng, Muchun Yang, Shun Liang, Yaling Shi, Yongzhen Cao, Ligang Liu, Jie Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology Changsha410073 China Engineering Research Center for National Fundamental Software National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819615506

The breadth-first search (BFS) algorithm is a fundamental algorithm in graph theory, and it’s parallelization can significantly improve performance. Therefore, there have been numerous efforts to leverage the powerful parallel computing capabilities of hardware like GPGPU to implement high-performance BFS algorithms. However, the energy efficiency is relatively low due to the high power consumption of the platforms on which the algorithm is adapted to. To deal with these challenges, this paper introduces PEbfs that is a high-performance BFS algorithm based on the PEZY-SC3s efficient processor. We integrated three search algorithms, two algorithm optimization strategies, and a directional optimization scheme into PEbfs. Through multiple evaluations of the performance of PEbfs on the public SNAP dataset, the results demonstrate that the average energy efficiency ratio of PEbfs is higher than that of Enterprise and Tigr, the two most advanced implementations on Nvidia’s GPGPU: It achieves 3.08× the average energy efficiency ratio of Enterprise and 4.53× that of Tigr. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

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A Fog-assisted Revocable and Auditable Access Control System 2

A Fog-assisted Revocable and Auditable Access Control System

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2nd International Conference on Electronic Information Technology, EIT 2023

作者： Niu, Jiaxu Shanghai Key Laboratory of Trustworthy Computing School of Software Engineering East China Normal University 3663 N. Zhongshan Rd. Shanghai200062 China

ISBN: (数字)9781510666627

ISBN: (纸本)9781510666610

Fog computing is a cutting-edge distributed computing architecture that optimizes resource allocation by fully utilizing the resources within the computing network. However, data security is a major concern in fog computing. The implementation of existing Ciphertext-Policy Attribute-based Encryption (CP-ABE) schemes in the fog computing environment faces challenges such as communication blockage, insufficient security, and poor performance. To tackle these challenges, this paper introduces a novel Fog-assisted Revocable and Auditable Access Control System (FRAACS), which incorporates fog-assisted key generation and decryption, user revocation, and auditing mechanisms. The comparative analysis of the proposed scheme's functionality and performance shows that it is a viable, secure, and fitting scheme for the fog computing environment. © 2023 SPIE.

关键词： Fog computing

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