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Mitigating Insecure Outputs in Large Language Models(LLMs): A Practical Educational Module

Mitigating Insecure Outputs in Large Language Models(LLMs): ...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： MD Abdul Barek Md Mostafizur Rahman Shapna Akter A.B.M Kamrul Islam Riad Md Abdur Rahman Hossain Shahriar Akond Rahman Fan Wu Department of Intelligent Systems and Robotics University of West Florida USA Dept. of Cybersecurity and Information Technology University of West Florida USA Center for Cybersecurity University of West Florida USA Computer Science and Software Engineering Auburn University USA Dept. of Computer Science Tuskegee University USA

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Large Language Models (LLMs) have extensive ability to produce promising output. Nowadays, people are increasingly relying on them due to easy accessibility, rapid and outstanding outcomes. However, the use of these results without appropriate scrutiny poses serious security risks, particularly when they are integrated with other software, APIs, or plugins. This is because the LLM outputs are highly dependent on the prompts they receive. Therefore, it is essential to carefully clean these outputs before using them in additional software environments. This paper is designed to teach students about the potential dangers of contaminated LLM output within the context of web development through prelab, hands-on, and postlab experiences. Hands-on lab provides practical guidance on how to handle LLM vulnerabilities to make applications safe with some real-world examples in Python. This approach aims to provide students with a deeper understanding of the precautions necessary to ensure software against the vulnerabilities introduced by LLM output.

关键词： Training Navigation Large language models Computational modeling Software Security Software development management

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A New Robust Hybrid Active Noise control System

A New Robust Hybrid Active Noise Control System

引用

IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Z. Wang Y. Xiao Y. Ma L. Ma K. Khorasani Dept. of Management & Information Systems Prefectural University of Hiroshima Hiroshima Japan Institute of Automation Jiangnan University Wuxi China Dept. of Electrical & Computer Engineering Concordia University Montreal Canada

The conventional hybrid active noise control (ANC, HANC) may significantly degrade if the reference signal for the feedforward ANC (FFANC) subcontroller consists of not only a broadband component but also a low-frequency sinusoidal component that is uncorrelated or partially correlated with the narrowband noise component that is attenuated by the feedback ANC (FBANC) subcontroller. In this paper, a new robust HANC system is proposed to mitigate the performance degradation resulting from the low-frequency sinusoidal component. A band-pass filter bank (BPFB) is applied to the FFANC reference signal to separate the low-frequency sinusoidal component from the broadband one and each of them is fed to an FFANC subcontroller that solely focuses on a single noise component. A supporting filter takes the extracted broadband component and the residual error as its input and desired signal, respectively. The same BPFB is then applied to the supporting filter error in order to separate the remaining low-frequency sinusoidal component from the narrowband component that persists in the residual error. The use of the two BPFBs and the supporting filter allows the three HANC subcontrollers to operate practically independently, each taking care of one of the pre-processed noise components which are uncorrelated with each other irrespective of the relationship between the two original noise sources. Extensive simulations are provided to demonstrate the improved effectiveness and robust capability of the proposed HANC as compared to its counterpart, even in a case that the low-frequency sinusoidal component in the FFANC reference signal is partially corrected with the primary narrowband noise component that is targeted by the FBANC.

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A Sentiment Analysis Study of Twitter Users' Reactions to the COVID-19 Vaccine

A Sentiment Analysis Study of Twitter Users' Reactions to th...

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International Conference on Information and Communication systems (ICICS)

作者： Suboh Alkhushayni Zakaria Alomari Du'a Al-Zaleq Dept. Information Systems Faculty of Information Technology and Computer Science Yarmouk University Irbid Jordan Dept. Computer Science New York Institute of Technology Vancouver BC Canada Dept. Robotics and Artificial Intelligence Engineering Al-Ahliyya Amman University Amman Jordan

This study investigates public attitudes towards the COVID-19 vaccine through Twitter data analysis. Using the Twitter API, tweets were collected, preprocessed, and labeled. Features were extracted using the Bag of Words representation, and sentiment analysis was conducted using Text Blob and Vader. Machine learning and deep learning models were trained and tested, revealing that deep learning models achieved the highest accuracy and F1 score. The research underscores the efficacy of machine learning and deep learning in analyzing COVID-19 vaccine-related tweets, shedding light on factors influencing vaccine resistance. These insights are crucial for pharmaceutical companies and public health officials, enabling them to address barriers to vaccine acceptance and enhance the societal benefits of widespread vaccination, contributing to the pandemic's resolution.

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Private Balance-Checking on Blockchain Accounts Using Private Integer Addition

Private Balance-Checking on Blockchain Accounts Using Privat...

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IEEE International Symposium on Information Theory

作者： Birenjith Sasidharan Emanuele Viterbo Dept. of Electronics &amp Communication Engineering Govt. Engineering College Trivandrum India Dept. of Electrical and Computer Systems Engineering Monash University Clayton Australia

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

A transaction record in a sharded blockchain can be represented as a two-dimensional array of integers with row-index associated to an account, column-index to a shard and the entry to the transaction amount. In a blockchain-based cryptocurrency system with coded sharding, a transaction record of a given epoch of time is encoded using a maximum-distance-separable code considering the entries as finite-field symbols. Each column of the resultant coded array is then stored in a server. In this paper, we propose a privacy-preserving multi-round protocol that allows a remote client to retrieve from a coded blockchain system the sum of transaction amounts belonging to two different epochs of time, but to the same ac-count. At the core of the protocol lies an algorithm for a remote client to privately compute a non-linear function referred to as integer addition of two finite-field symbols representing integer numbers, in the presence of curious-but-honest adversaries. Applying it to balance-checking in a cryptocurrency system, the protocol guarantees information-theoretic privacy on account number and shard number thereby ensuring perfect user anonymity, and also maintains confidentiality of half of the input bits on average. The protocol turns out to be a useful primitive for balance-checking in lightweight clients of a PolyShard-ed blockchain.

关键词： Privacy Protocols Codes Symbols Blockchains Cryptocurrency Servers

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Blockchain-Enhanced Framework for Secure Third-Party Vendor Risk Management and Vigilant Security controls

Blockchain-Enhanced Framework for Secure Third-Party Vendor ...

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IEEE International Conference on Big Data

作者： Deepti Gupta Lavanya Elluri Avi Jain Shafika Showkat Moni Omer Aslan Dept. of Computer Information Systems Texas A&M University - Central Texas Texas USA College of Business University of Tampa Florida USA Dept. of Electrical Engineering and Computer Science Embry-Riddle Aeronautical University Florida USA Department of Software Engineering Bandırma Onyedi Eylül University Bandırma Turkey

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

In an era of heightened digital interconnectedness, businesses increasingly rely on third-party vendors to enhance their operational capabilities. However, this growing dependency introduces significant security risks, making it crucial to develop a robust framework to mitigate potential vulnerabilities. This paper proposes a comprehensive secure framework for managing third-party vendor risk, integrating blockchain technology to ensure transparency, traceability, and immutability in vendor assessments and interactions. By leveraging blockchain, the framework enhances the integrity of vendor security audits, ensuring that vendor assessments remain up-to-date and tamperproof. This proposed framework leverages smart contracts to reduce human error while ensuring real-time monitoring of compliance and security controls. By evaluating critical security controls—such as data encryption, access control mechanisms, multi-factor authentication, and zero-trust architecture—this approach strengthens an organization’s defense against emerging cyber threats. Additionally, continuous monitoring enabled by blockchain ensures the immutability and transparency of vendor compliance processes. In this paper, a case study on iHealth’s transition to AWS Cloud demonstrates the practical implementation of the framework, showing a significant reduction in vulnerabilities and marked improvement in incident response times. Through the adoption of this blockchain-enabled approach, organizations can mitigate vendor risks, streamline compliance, and enhance their overall security posture. Our findings highlight the importance of employing blockchain to enforce security controls and maintain compliance with healthcare regulations such as HIPAA. In this paper, we present a comprehensive set of security controls and demonstrate how blockchain technology enhances their effectiveness, ensuring greater transparency, accountability, and automation in vendor assessments. By reducing human error, enabl

关键词： Multi-factor authentication Smart contracts Organizations Real-time systems Regulation Blockchains Security Time factors Risk management Resilience

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Mobile Health Intervention System in Optimizing Healthcare Delivery for Cardiac Patients

Mobile Health Intervention System in Optimizing Healthcare D...

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Advancements in Computing (ICAC), International Conference on

作者： R.P.K. Prabashana G.A.J.W. Nanayakkara W.K.D.C. Wanniachchi S.B.A.M.B.S. Arampath Samantha Rajapaksha S.M.B. Harshanath Dept. of Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka dept. of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

The advent of mobile health (mHealth) technologies has ushered in a new era in healthcare delivery, transforming the way cardiac patients receive medical care and support. This research paper explores the role of a mobile health intervention system in optimizing healthcare delivery for cardiac patients. The prevalence of heart attacks has necessitated innovative solutions to enhance patient outcomes and reduce the burden on healthcare systems. The proposed mHealth intervention system leverages the ubiquity of mobile devices to provide real-time monitoring, personalized interventions with environment prediction, and seamless communication between patients and healthcare providers. Through a comprehensive review of existing literature and empirical studies, this paper examines the impact of the mHealth intervention system on patient engagement, adherence to treatment plans, early detection of cardiac events, and overall quality of care. The integration of wearable device, CardioCare mobile application, and telemedicine platforms creates a holistic approach to cardiac care, empowering patients to actively participate in their health management and enabling healthcare professionals to make informed decisions. The potential benefits, challenges, and ethical considerations surrounding the implementation of this system are discussed.

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Threshold Adjustment of Beta-Alpha Ratio of EEG Signal for Generation of Visual Effects in a VR Live Concert 10

Threshold Adjustment of Beta-Alpha Ratio of EEG Signal for G...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Munoz-Gonzalez, Angel Horie, Ryota Shibaura Institute of Technology Functional Control Systems Tokyo Japan Shibaura Institute of Technology Dept. of Information And Communications Engineering Tokyo Japan

ISBN: (纸本)9781665436762

We have developed a Brain-computer Interface (BCI) experience combining electroencephalogram (EEG) signals with Virtual Reality (VR). In our proposal, the users can attend a VR live concert system while participating in it throughout the generation of visual effects (VE) based on their brain activity. The VE are generated according to the beta and alpha waves of the EEG signal. When the beta-alpha ratio exceeds specific values, a threshold triggers the generation of different VE. A comparison between fixed threshold values and personalized thresholds for each subject is conducted. When conducting VR lives, individual differences on the beta-alpha ratio sometimes prevent the generation of VE based on constant thresholds, causing bigger differences on the experience between users. Thus, towards conducting VR live concert with many users, automatic adjustment of the thresholds for compensating the individual differences is required. In this paper, we proposed a method for adjusting thresholds based on percentiles of the distribution of beta-alpha ratio values and implemented it to our VR live system. We show results of experiments for validating the proposed methods. © 2021 IEEE.

关键词： Electroencephalography

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Executive Conference Chair Welcome

2023 IEEE Gaming, Entertainment, and Media Conference, GEM 2...

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2023 IEEE Gaming, Entertainment, and Media Conference, GEM 2023 2023年

作者： Hogue, Andrew Cannavo, Alberto Game Development & Interactive Media Ontario Tech University Oshawa Canada Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy

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Unity ECC: Unified Memory Protection Against Bit and Chip Errors

Unity ECC: Unified Memory Protection Against Bit and Chip Er...

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Supercomputing Conference

作者： Dongwhee Kim Jaeyoon Lee Wonyeong Jung Michael B. Sullivan Jungrae Kim Dept. of Semiconductor and Display Engineering Sungkyunkwan University Suwon Gyeonggi-do Korea Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Gyeonggi-do Korea NVIDIA Santa Clara California USA Dept. of Semiconductor Systems Engineering Sungkyunkwan University Suwon Gyeonggi-do Korea

DRAM vendors utilize On-Die Error Correction Codes (OD-ECC) to correct random bit errors internally. Meanwhile, system companies utilize Rank-Level ECC (RL-ECC) to protect data against chip errors. Separate protection increases the redundancy ratio to 32.8% in DDR5 and incurs significant performance penalties. This paper proposes a novel RL-ECC, Unity ECC, that can correct both single-chip and double-bit error patterns. Unity ECC corrects double-bit errors using unused syndromes of single-chip correction. Our evaluation shows that Unity ECC without OD-ECC can provide the same reliability level as Chipkill RL-ECC with OD-ECC. Moreover, it can significantly improve system performance and reduce DRAM energy and area by eliminating OD-ECC.

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A Novel Real-Time Redundant System For Aiding Drivers To Increase Their Attention Level

A Novel Real-Time Redundant System For Aiding Drivers To Inc...

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Smart World Congress (SWC), IEEE

作者： Jacopo Sini Luigi Pugliese Pietro D’Agostino Massimo Violante Riccardo Groppo Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy Sleep Advice Technologies S.r.l Turin Italy

Road accidents are a major concern worldwide. Research of technological solutions to improve road safety is an open topic, considering this issue from various perspectives. As widely reported in the literature, driver distraction is one of the most common causes of collisions. Even if vehicles are becoming safer and safer over the years, pedestrians and cyclists are still exposed to severe accidents. Major concerns about driver distraction is mobile phone use and drowsy driving. This paper proposes a virtual buddy designed to help drivers, thanks to warning sound messages, improve their attention level. The main idea is to recognize, thanks to different sources (video camera, physiological data, and interior environmental conditions) interpreted by a data-fusion algorithm, whenever there is a distracted or drowsy behavior, recalling the driver to the road. The effectiveness of the data-fusion algorithm in detecting dangerous conditions has been verified thanks to a driving simulator experimentally, obtaining no false negatives from distraction from drowsiness, a sensitivity of about 85% for the distraction caused by mobile phone usage or other activities different from focusing on driving.

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