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IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)
2024 IEEE 6th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)
28-31 Oct. 2024
Showing 1-25 of 79
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
62245 - TPS-ISA, 2024 (PRT)
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Large Language Models to Enhance Malware Detection in Edge Computing
Christian Rondanini;Barbara Carminati;Elena Ferrari;Ashish Kundu;Akshay Jajoo
Publication Year: 2024,Page(s):1 - 10
The increasing sophistication of malware in recent years has underscored the need for more advanced detection approaches, particularly in edge computing environments. Traditional methods and machine learning models, have shown promise but face significant limitations in handling evolving malware types. To address these challenges, we explore the application of Large Language Models (LLMs) for malw...Show More
Digital Evidence Chain of Custody: Navigating New Realities of Digital Forensics
Publication Year: 2024,Page(s):11 - 20
In the era of ubiquitous digital platforms and pervasive mobile device usage, digital evidence has become increasingly integral to civil and criminal justice systems. However, the unique characteristics of digital evidence present significant challenges to maintaining its integrity and ensuring its admissibility in legal proceedings. This paper explores the critical role of Chain of Custody (CoC) ...Show More
Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum
Nashrah Haque;Xiang Li;Zhehui Chen;Yanzhao Wu;Lei Yu;Arun Iyengar;Wenqi Wei
Publication Year: 2024,Page(s):21 - 30
We propose a novel framework, Stable Diffusion-based Momentum Integrated Adversarial Examples (SD-MIAE), for generating adversarial examples that can effectively mislead neural network classifiers while maintaining visual imperceptibility and preserving the semantic similarity to the original class label. Our method leverages the text-to-image generation capabilities of the Stable Diffusion model ...Show More
Analyzing location data from many individuals can provide valuable insights, especially when linked with private attributes like personal health information. A recent application includes identifying COVID-19 outbreaks by aggregating individuals’ health data across a geographical hierarchy. However, analyzing such sensitive information can threaten the individuals’ privacy, especially when honest-...Show More
Utility-Privacy Aware Mobile Diminished Reality Framework for 3D Visual Privacy
Publication Year: 2024,Page(s):41 - 48
Engaging in immersive technologies has obvious benefits, but the increasing pervasiveness of these technologies, specifically Augmented Reality (AR) and Mixed Reality poses privacy risks, especially since AR cameras are continually capturing information about users’ surroundings, including people and personal places. Current privacy-preserving techniques are either designed for a two-dimensional s...Show More
A Privacy-Preserving Cyber Threat Intelligence Sharing System
Philip Huff;Spencer Massengale;Tran Viet Xuan Phuong;Sri Nikhil Gupta Gourisetti
Publication Year: 2024,Page(s):49 - 58
Cyber Threat Intelligence (CTI) is a key resource for developing defensive strategies against potential cyber adversaries. Entities typically access CTI through open-source platforms, national agencies, or specialized commercial services. However, the bi-directional exchange of CTI is hindered by organizational trust boundaries, which complicate the sharing processes between entities and CTI provi...Show More
Improved Ethereum Fraud Detection Mechanism with Explainable Tabular Transformer Model
Publication Year: 2024,Page(s):59 - 68
Blockchain technology has gained popularity due to its key features of decentralization, cryptographic verification, and immutability, which have proven extremely useful in various industries. However, despite their impressive security features, blockchain networks are not immune to cyber threats. In recent times, the blockchain system has been threatened by fraudulent attacks that require quick r...Show More
Unsupervised Approach for Electricity Theft Detection Combining Recurrent Neural Networks and Rule-Based Policy
Publication Year: 2024,Page(s):69 - 76
The Advanced Metering Infrastructure (AMI) is a bi-directional communication system between utilities and consumers and is an integral part of smart energy grid development. AMI offers several benefits such as automated collection of energy measurements, outage management, connection and disconnection requests, and system status tracking. However, given the increased dependency on connectivity and...Show More
Bias Detection and Mitigation in Zero-Shot Spam Classification using LLMs
Publication Year: 2024,Page(s):77 - 86
There is a growing number of scams through various communication mediums, including social media, phone calls and messages, search engine advertising, etc. Often these scams are realized via sending spam texts on any of these communication mediums, and therefore, prior research has investigated the task of spam classification to design information filtering systems. However, existing works have ex...Show More
Towards Transparent Intrusion Detection: A Coherence-Based Framework in Explainable AI Integrating Large Language Models
Publication Year: 2024,Page(s):87 - 96
Intrusion Detection Systems (IDS) are essential for maintaining cybersecurity by identifying potential threats within networks. However, the black-box nature of the Artificial Intelligence models used in many IDS deployments hinders their effectiveness. Explainable AI (XAI) methods have emerged to provide transparency, but their evaluation metrics—such as faithfulness, completeness, and stability—...Show More
PrivComp-KG: Leveraging KG and LLM for Compliance Verification
Leon Garza;Lavanya Elluri;Aritran Piplai;Anantaa Kotal;Deepti Gupta;Anupam Joshi
Publication Year: 2024,Page(s):97 - 106
Regulatory documents are complex and lengthy, making full compliance a challenging task for businesses. Similarly, privacy policies provided by vendors frequently fall short of the necessary legal standards due to insufficient detail. To address these issues, we propose a solution that leverages a Large Language Model (LLM) in combination with Semantic Web technology. This approach aims to clarify...Show More
A Qualitative Study on Using ChatGPT for Software Security: Perception vs. Practicality
Publication Year: 2024,Page(s):107 - 117
Artificial Intelligence (AI) advancements have enabled the development of Large Language Models (LLMs) that can perform a variety of tasks with remarkable semantic understanding and accuracy. ChatGPT is one such LLM that has gained significant attention due to its impressive capabilities for assisting in various knowledge-intensive tasks. Due to the knowledge-intensive nature of engineering secure...Show More
Generative AI (Gen AI) with large language models (LLMs) are being widely adopted across the industry, academia and government. Cybersecurity is one of the key sectors where LLMs can be and/or are already being used. There are a number of problems that inhibit the adoption of trustworthy Gen AI and LLMs in cybersecurity and such other critical areas. One of the key challenge to the trustworthiness...Show More
Bridging the Legal Divide: Contractual Enforceability and Acceptability in the AI-Driven Automated Conversion of Smart Legal Contracts
Shriyaa Balaji;Ram Dantu;Kritagya Upadhyay;Thomas McCullough
Publication Year: 2024,Page(s):128 - 137
Many people find the legal system to be convoluted and resource-intensive with all of the complications, which often derive from the vagueness and ambiguity of legal texts, that arise in its processes. Oftentimes, legal processes become inconvenient or even inaccessible to parts of the general population. The integration of artificial intelligence (AI) and blockchain technology into legal processe...Show More
Counter Denial of Service for Next-Generation Networks within the Artificial Intelligence and Post-Quantum Era
Publication Year: 2024,Page(s):138 - 147
Given the rise in cyber threats to networked systems, coupled with the proliferation of AI techniques and enhanced processing capabilities, Denial of Service (DoS) attacks are becoming increasingly sophisticated and easily executable. They target system availability, compromising entire systems without breaking underlying security protocols. Consequently, numerous studies have focused on preventin...Show More
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
62245 - TPS-ISA, 2024 (PRT)
- Print on DemandPurchase at Partner
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