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Articles 631 - 660 of 4669
Full-Text Articles in Information Security
Assessing Open Source Tools For Enhanced Forensic Analysis Of Unmanned Aerial Vehicles (Uavs), Nura Shifa Hamed
Assessing Open Source Tools For Enhanced Forensic Analysis Of Unmanned Aerial Vehicles (Uavs), Nura Shifa Hamed
Theses
The widespread applications of Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, has given rise to significant national security threats due to their illicit activities. Consequently, the domain of UAV forensics is rapidly evolving, presenting a substantial knowledge deficit among forensic experts. Open source tools provide accessible and affordable resources, making it easier for investigators to bridge this gap by gaining expertise in the use of these tools. This helps ensure that forensic professionals can keep up with the ever-changing UAV technology landscape. This thesis undertakes the mission of navigate the complex field of drone forensics and conducting a …
Security Analysis Of Holystone Drones: Examining Attack Vectors And Data Extraction Techniques, Sandesh Ambadas More
Security Analysis Of Holystone Drones: Examining Attack Vectors And Data Extraction Techniques, Sandesh Ambadas More
Theses and Dissertations
In recent years, the surge in popularity of small-scale Unmanned Aerial Vehicles (UAVs), especially Holy Stone models, has raised significant security concerns. This study examines specific Holy Stone drone models, including the HS 175D, HS 430, HS 360S, and HS720, focusing on sub-250g drones exempt from FAA registration and those requiring registration and Remote ID. Despite advancements in drone technology, our research reveals persistent vulnerabilities that could be exploited by malicious actors for illicit purposes, posing a substantial security risk. Our comprehensive analysis involved simulated attacks in identifying and exploiting these vulnerabilities, leading to the successful acquisition of flight logs, …
Security Compliance And Work-Issued Mobile Devices: Out Of Sight, Out Of Mind?, Kent Marett, Shan Xiao, Sumin Kim
Security Compliance And Work-Issued Mobile Devices: Out Of Sight, Out Of Mind?, Kent Marett, Shan Xiao, Sumin Kim
Business and Information Technology Faculty Research & Creative Works
For security, economic, and efficiency reasons, many businesses supply mobile devices to employees to use both in the workplace and remotely, accompanied by policies governing their appropriate use. Extant research has shown that work-issued mobile devices can disrupt employees' perceptions of work-life balance (WLB) and, indeed, WLB can impact employees' job satisfaction and performance. The global COVID-19 pandemic meant that more employees than usual performed their work remotely, but this situation may have not fit the preferred WLB for some. Did this encroachment mean that appropriate use policies were forgotten? We conducted two rounds of surveys, one pre-pandemic and the …
Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum
Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum
Honors Theses
Satellite communication is essential for the exploration and study of space. Satellites allow communications with many devices and systems residing in space and on the surface of celestial bodies from ground stations on Earth. However, with the rise of Ground Station as a Service (GsaaS), the ability to efficiently send action commands to distant satellites must ensure non-repudiation such that an attacker is unable to send malicious commands to distant satellites. Distant satellites are also constrained devices and rely on limited power, meaning security on these devices is minimal. Therefore, this study attempted to propose a novel algorithm to allow …
Enhanced Content-Based Fake News Detection Methods With Context-Labeled News Sources, Duncan Arnfield
Enhanced Content-Based Fake News Detection Methods With Context-Labeled News Sources, Duncan Arnfield
Electronic Theses and Dissertations
This work examined the relative effectiveness of multilayer perceptron, random forest, and multinomial naïve Bayes classifiers, trained using bag of words and term frequency-inverse dense frequency transformations of documents in the Fake News Corpus and Fake and Real News Dataset. The goal of this work was to help meet the formidable challenges posed by proliferation of fake news to society, including the erosion of public trust, disruption of social harmony, and endangerment of lives. This training included the use of context-categorized fake news in an effort to enhance the tools’ effectiveness. It was found that term frequency-inverse dense frequency provided …
Mitigating Membership Inference Attacks Via Weighted Smoothing, Minghan Tan, Xiaofei Xie, Jun Sun, Tianhao Wang
Mitigating Membership Inference Attacks Via Weighted Smoothing, Minghan Tan, Xiaofei Xie, Jun Sun, Tianhao Wang
Research Collection School Of Computing and Information Systems
Recent advancements in deep learning have spotlighted a crucial privacy vulnerability to membership inference attack (MIA), where adversaries can determine if specific data was present in a training set, thus potentially revealing sensitive information. In this paper, we introduce a technique, weighted smoothing (WS), to mitigate MIA risks. Our approach is anchored on the observation that training samples differ in their vulnerability to MIA, primarily based on their distance to clusters of similar samples. The intuition is clusters will make model predictions more confident and increase MIA risks. Thus WS strategically introduces noise to training samples, depending on whether they …
Interoperability In Blockchain: A Survey, Kunpeng Ren, Nhut-Minh Ho, Dumitrel Loghin, Thanh-Toan Nguyen, Beng Chin Ooi, Quang-Trung Ta, Feida Zhu
Interoperability In Blockchain: A Survey, Kunpeng Ren, Nhut-Minh Ho, Dumitrel Loghin, Thanh-Toan Nguyen, Beng Chin Ooi, Quang-Trung Ta, Feida Zhu
Research Collection School Of Computing and Information Systems
This paper presents a systematic and comprehensive survey on blockchain interoperability, where interoperability is defined as the ability of blockchains to flexibly transfer assets, share data, and invoke smart contracts across a mix of public, private, and consortium blockchains without any changes to the underlying blockchain systems. Analyzing the vast landscape of both research papers and industry projects, we classify the existing works into five categories, namely, (1) sidechains, (2) notary schemes, (3) hashed time lock contracts (HTLC), (4) relays, and (5) blockchain agnostic protocols. We analyze the existing works under a taxonomy that consists of system and safety characteristics, …
Learning Program Semantics For Vulnerability Detection Via Vulnerability-Specific Inter-Procedural Slicing, Bozhi Wu, Shangqing Liu, Xiao Yang, Zhiming Li, Jun Sun, Shang-Wei Lin
Learning Program Semantics For Vulnerability Detection Via Vulnerability-Specific Inter-Procedural Slicing, Bozhi Wu, Shangqing Liu, Xiao Yang, Zhiming Li, Jun Sun, Shang-Wei Lin
Research Collection School Of Computing and Information Systems
Learning-based approaches that learn code representations for software vulnerability detection have been proven to produce inspiring results. However, they still fail to capture complete and precise vulnerability semantics for code representations. To address the limitations, in this work, we propose a learning-based approach namely SnapVuln, which first utilizes multiple vulnerability-specific inter-procedural slicing algorithms to capture vulnerability semantics of various types and then employs a Gated Graph Neural Network (GGNN) with an attention mechanism to learn vulnerability semantics. We compare SnapVuln with state-of-the-art learning-based approaches on two public datasets, and confirm that SnapVuln outperforms them. We further perform an ablation study …
Comparison And Evaluation On Static Application Security Testing (Sast) Tools For Java, Kaixuan Li, Sen Chen, Lingling Fan, Ruitao Feng, Han Liu, Chengwei Liu, Yang Liu, Yixiang Chen
Comparison And Evaluation On Static Application Security Testing (Sast) Tools For Java, Kaixuan Li, Sen Chen, Lingling Fan, Ruitao Feng, Han Liu, Chengwei Liu, Yang Liu, Yixiang Chen
Research Collection School Of Computing and Information Systems
Static application security testing (SAST) takes a significant role in the software development life cycle (SDLC). However, it is challenging to comprehensively evaluate the effectiveness of SAST tools to determine which is the better one for detecting vulnerabilities. In this paper, based on well-defined criteria, we first selected seven free or open-source SAST tools from 161 existing tools for further evaluation. Owing to the synthetic and newly-constructed real-world benchmarks, we evaluated and compared these SAST tools from different and comprehensive perspectives such as effectiveness, consistency, and performance. While SAST tools perform well on synthetic benchmarks, our results indicate that only …
Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua
Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, they still possess limitations, such as failing to ask clarifying questions to ambiguous queries or refuse users' unreasonable requests, both of which are considered as key aspects of a conversational agent's proactivity. This raises the question of whether LLM-based conversational systems are equipped to handle proactive dialogue problems. In this work, we conduct a comprehensive analysis of LLM-based conversational systems, specifically focusing on three key aspects of proactive dialogues: clarification, target-guided, and non-collaborative dialogues. To trigger the proactivity of …
Beyond Factuality: A Comprehensive Evaluation Of Large Language Models As Knowledge Generators, Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
Beyond Factuality: A Comprehensive Evaluation Of Large Language Models As Knowledge Generators, Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Large language models (LLMs) outperform information retrieval techniques for downstream knowledge-intensive tasks when being prompted to generate world knowledge. Yet, community concerns abound regarding the factuality and potential implications of using this uncensored knowledge. In light of this, we introduce CONNER, a COmpreheNsive kNowledge Evaluation fRamework, designed to systematically and automatically evaluate generated knowledge from six important perspectives - Factuality, Relevance, Coherence, Informativeness, Helpfulness and Validity. We conduct an extensive empirical analysis of the generated knowledge from three different types of LLMs on two widely-studied knowledge-intensive tasks, i.e., open-domain question answering and knowledge-grounded dialogue. Surprisingly, our study reveals that the …
Customer Cybersecurity And Supplier Cost Management Strategy, Xu Yang, Peng Liang, Nan Hu, Fujing Xue
Customer Cybersecurity And Supplier Cost Management Strategy, Xu Yang, Peng Liang, Nan Hu, Fujing Xue
Research Collection School Of Computing and Information Systems
In this paper, we explore the spillover effect of customer firms’ data breaches on their upstream supplier firms’ cost management strategies, proxied by cost stickiness. Our primary analyses suggest that data breaches suffered by customer firms are associated with a decrease in cost stickiness among supplier firms. Furthermore, the reductions in supplier cost stickiness are stronger if suppliers are managed by CEOs from national cultural groups with high uncertainty avoidance, low long-term orientations, and/or low individualism. In sum, the findings contribute to both Information Systems (IS) and Operations Management (OM) disciplines in terms of data breach, cost management strategy, and …
The Propagation And Execution Of Malware In Images, Piper Hall
The Propagation And Execution Of Malware In Images, Piper Hall
Cybersecurity Undergraduate Research Showcase
Malware has become increasingly prolific and severe in its consequences as information systems mature and users become more reliant on computing in their daily lives. As cybercrime becomes more complex in its strategies, an often-overlooked manner of propagation is through images. In recent years, several high-profile vulnerabilities in image libraries have opened the door for threat actors to steal money and information from unsuspecting users. This paper will explore the mechanisms by which these exploits function and how they can be avoided.
An Empirical Study On The Use Of Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi
An Empirical Study On The Use Of Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi
Thesis/ Dissertation Defenses
Trade contributes to the United Arab Emirates' economic growth. This thesis focuses on trade dynamics in the UAE using Long Short-Term Memory (LSTM) neural networks. The study focuses on both import and export activities, providing understandings into the complex patterns and impacts of international trade on the UAE's economic growth. The research begins by constructing an LSTM model to forecast the UAE's Gross Domestic Product (GDP) through the utilization of historical trade data. We use time series data for imports and exports as key input features. This innovative approach highlights the relevance of trade statistics as a leading indicator of …
Assessing Open Source Tools For Enhanced Forensic Analysis Of Unmanned Aerial Vehicles (Uavs), Nura Shifa Hamed
Assessing Open Source Tools For Enhanced Forensic Analysis Of Unmanned Aerial Vehicles (Uavs), Nura Shifa Hamed
Thesis/ Dissertation Defenses
The widespread applications of Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, has given rise to significant national security threats due to their illicit activities. Consequently, the domain of UAV forensics is rapidly evolving, presenting a substantial knowledge deficit among forensic experts. Open-source tools provide accessible and affordable resources, making it easier for investigators to bridge this gap by gaining expertise in the use of these tools. This helps ensure that forensic professionals can keep up with the ever-changing UAV technology landscape. This thesis undertakes the mission of navigate the complex field of drone forensics and conducting a comprehensive …
Preparing Uk Students For The Workplace: The Acceptability Of A Gamified Cybersecurity Training, Oliver J. Mason, Siobhan Collman, Stella Kazamia, Ioana Boureanu
Preparing Uk Students For The Workplace: The Acceptability Of A Gamified Cybersecurity Training, Oliver J. Mason, Siobhan Collman, Stella Kazamia, Ioana Boureanu
Journal of Cybersecurity Education, Research and Practice
This pilot study aims to assess the acceptability of Open University’s training platform called Gamified Intelligent Cyber Aptitude and Skills Training course (GICAST), as a means of improving cybersecurity knowledge, attitudes, and behaviours in undergraduate students using both quantitative and qualitative methods. A mixed-methods, pre-post experimental design was employed. 43 self-selected participants were recruited via an online register and posters at the university (excluding IT related courses). Participants completed the Human Aspects of Information Security Questionnaire (HAIS-Q) and Fear of Missing Out (FoMO) Scale. They then completed all games and quizzes in the GICAST course before repeating the HAIS-Q and …
Closing The Gap: Leveraging Aes-Ni To Balance Adversarial Advantage And Honest User Performance In Argon2i, Nicholas Harrell, Nathaniel Krakauer
Closing The Gap: Leveraging Aes-Ni To Balance Adversarial Advantage And Honest User Performance In Argon2i, Nicholas Harrell, Nathaniel Krakauer
CERIAS Technical Reports
The challenge of providing data privacy and integrity while maintaining efficient performance for honest users is a persistent concern in cryptography. Attackers exploit advances in parallel hardware and custom circuit hardware to gain an advantage over regular users. One such method is the use of Application-Specific Integrated Circuits (ASICs) to optimize key derivation function (KDF) algorithms, giving adversaries a significant advantage in password guessing and recovery attacks. Other examples include using graphical processing units (GPUs) and field programmable gate arrays (FPGAs). We propose a focused approach to close the gap between adversarial advantage and honest user performance by leveraging the …
Optimization Of Biomedical Imaging Filters For Use In Recaptured Identity Document Classification, John Magee, Stephen Sheridan Phd, Christina Thorpe Phd
Optimization Of Biomedical Imaging Filters For Use In Recaptured Identity Document Classification, John Magee, Stephen Sheridan Phd, Christina Thorpe Phd
Conference papers
As banks and online financial institutions move toward full remote onboarding services, the attack vectors for bad actors increases to include those of recaptured identity documents. This type of fraud opens banking customers to potential crimes of identity theft, as well as causing reputational damage to the institutions involved. In this paper we extend existing research focusing on the use of biomedical imaging filters and their usefulness when classifying recaptured identity documents. We perform a grid search and demonstrate that different filter configurations exist that dramatically reduce the classification error rates compared to those achieved using only the default filter …
Integrity, Confidentiality, And Equity: Using Inquiry-Based Labs To Help Students Understand Ai And Cybersecurity, Richard C. Alexander, Liran Ma, Ze-Li Dou, Zhipeng Cai, Yan Huang
Integrity, Confidentiality, And Equity: Using Inquiry-Based Labs To Help Students Understand Ai And Cybersecurity, Richard C. Alexander, Liran Ma, Ze-Li Dou, Zhipeng Cai, Yan Huang
Journal of Cybersecurity Education, Research and Practice
Recent advances in Artificial Intelligence (AI) have brought society closer to the long-held dream of creating machines to help with both common and complex tasks and functions. From recommending movies to detecting disease in its earliest stages, AI has become an aspect of daily life many people accept without scrutiny. Despite its functionality and promise, AI has inherent security risks that users should understand and programmers must be trained to address. The ICE (integrity, confidentiality, and equity) cybersecurity labs developed by a team of cybersecurity researchers addresses these vulnerabilities to AI models through a series of hands-on, inquiry-based labs. Through …
A Novel Chatbot System For Digitizing Service Management To Improve Business Continuity, Asraa Mohammed Albeshr
A Novel Chatbot System For Digitizing Service Management To Improve Business Continuity, Asraa Mohammed Albeshr
Thesis/ Dissertation Defenses
The COVID-19 pandemic underscored the importance of businesses transitioning to digital platforms to reduce human contact and maintain operations. Digital transformation is the act of leveraging digital technologies to enhance and update business operations, corporate culture, and customer interactions to address evolving market needs. IT service management (ITSM) stands to gain significantly from this shift, as many of its processes are currently manual and labor-intensive. In our research, we introduced a model designed to refine chatbot responses to user questions, making it an invaluable asset for our study. The model performed admirably, achieving an accuracy rate of 90%. Moreover, we …
Understanding The Non-Traditional Security Dimensions: Cyber Threat Landscape In Pakistan, Minhas Majeed Khan
Understanding The Non-Traditional Security Dimensions: Cyber Threat Landscape In Pakistan, Minhas Majeed Khan
CBER Conference
The research analyzes the vulnerabilities and consequences of cyber-attacks on essential infrastructure sectors such as energy, telecommunications, and finance, which are vital for the country’s stability and development. It also evaluates the economic, political, and social effects of cyber incidents on the country’s governance and society. Moreover, the research assesses the current cyber security measures and frameworks in Pakistan and identifies the gaps and opportunities for improvement.
Building A Diverse Cybersecurity Workforce: A Study On Attracting Learners With Varied Educational Backgrounds, Mubashrah Saddiqa, Kristian Helmer Kjær Larsen1 Helmer Kjær Larsen, Robert Nedergaard Nielsen, Jens Myrup Pedersen
Building A Diverse Cybersecurity Workforce: A Study On Attracting Learners With Varied Educational Backgrounds, Mubashrah Saddiqa, Kristian Helmer Kjær Larsen1 Helmer Kjær Larsen, Robert Nedergaard Nielsen, Jens Myrup Pedersen
Journal of Cybersecurity Education, Research and Practice
Cybersecurity has traditionally been perceived as a highly technical field, centered around hacking, programming, and network defense. However, this article contends that the scope of cybersecurity must transcend its technical confines to embrace a more inclusive approach. By incorporating various concepts such as privacy, data sharing, and ethics, cybersecurity can foster diversity among audiences with varying educational backgrounds, thereby cultivating a richer and more resilient security landscape. A more diverse cybersecurity workforce can provide a broader range of perspectives, experiences, and skills to address the complex and ever-evolving threats of the digital age. The research focuses on enhancing cybersecurity education …
Evaluating Attack Surface Management In An Industrial Control System (Ics) Environment: Leveraging A Recon Ftw For Threat Classification And Incident Response, Nathalia De Sa Soares
Evaluating Attack Surface Management In An Industrial Control System (Ics) Environment: Leveraging A Recon Ftw For Threat Classification And Incident Response, Nathalia De Sa Soares
LSU Master's Theses
Protecting Industrial Control Systems (ICS) from cyber threats is paramount to
ensure the reliability and security of critical infrastructure. Organizations must proactively identify vulnerabilities and strengthen their incident response capabilities as attack vectors evolve. This research explores implementing an Attack Surface Management (ASM) approach, utilizing Recon FTW, to assess an operating ICS environment’s security posture comprehensively.
The primary objective of this research is to develop a tool for performing recon-
naissance in an ICS environment with a non-intrusive approach, enabling the realistic simulation of potential threat scenarios and the identification of critical areas requiring immediate attention and remediation. We aim …
An Empirical Study On The Use Of Secure Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi
An Empirical Study On The Use Of Secure Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi
Theses
Trade contributes to the United Arab Emirates' economic growth. This thesis focuses on trade dynamics in the UAE using Long Short-Term Memory (LSTM) neural networks. The study focuses on both import and export activities, providing understandings into the complex patterns and impacts of international trade on the UAE's economic growth. The research begins by constructing an LSTM model to forecast the UAE's Gross Domestic Product (GDP) through the utilization of historical trade data. We use time series data for imports and exports as key input features. This innovative approach highlights the relevance of trade statistics as a leading indicator of …
Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman
Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman
Research outputs 2022 to 2026
Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, …
Designing Secure Mental Healthcare Chatbots For Older Adults, Aishwarya Surani
Designing Secure Mental Healthcare Chatbots For Older Adults, Aishwarya Surani
Electronic Theses and Dissertations
The landscape of mental health support has evolved as a result of the rising demand for digital mental healthcare services. Users now have an opportunity to seek mental health support online due to the growth of digital platforms. For those looking for mental health treatments, chatbots have evolved as user-friendly, accessible platforms that provide remote access and convenience. However, for chatbots to be effective, users must divulge personal and sensitive information, such as demographics, insurance information, and a history of mental illness. While chatbots offer services to a variety of demographic users, older adults face unique challenges related to usability, …
A Smart Chatbot System For Digitizing Service Management To Improve Business Continuity, Asraa Mohammed Albeshr
A Smart Chatbot System For Digitizing Service Management To Improve Business Continuity, Asraa Mohammed Albeshr
Theses
Chatbots, also called digital systems that require a natural language-based interface for user interaction, are increasingly being integrated into our daily lives. These chatbots respond intelligently to voice and text and function as sophisticated entities. Its functioning includes the recognition of multiple human languages through the application of Natural Language Processing (NLP) techniques. These chatbots find applications in various areas such as e-commerce services, medical assistance, recommendation systems, and educational purposes. This reflects the versatility and widespread adoption of this technology. AI chatbots play a crucial role in improving IT support in IT Service Management (ITSM) for better business continuity. …
Rethinking Conversational Agents In The Era Of Large Language Models: Proactivity, Non-Collaborativity, And Beyond, Yang Deng, Wenqiang Lei, Minlie Huang, Tat-Seng Chua
Rethinking Conversational Agents In The Era Of Large Language Models: Proactivity, Non-Collaborativity, And Beyond, Yang Deng, Wenqiang Lei, Minlie Huang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Conversational systems are designed to offer human users social support or functional services through natural language interactions. Typical conversation researches mainly focus on the response-ability of the system, such as dialogue context understanding and response generation. In the era of large language models (LLMs), LLM-augmented conversational systems showcase exceptional capabilities of responding to user queries for different language tasks. However, as LLMs are trained to follow users' instructions, LLM-augmented conversational systems typically overlook the design of an essential property in intelligent conversations, i.e., goal awareness. In this tutorial, we will introduce the recent advances on the design of agent's awareness …
Privacy-Preserving Bloom Filter-Based Keyword Search Over Large Encrypted Cloud Data, Yanrong Liang, Jianfeng Ma, Yinbin Miao, Da Kuang, Xiangdong Meng, Robert H. Deng
Privacy-Preserving Bloom Filter-Based Keyword Search Over Large Encrypted Cloud Data, Yanrong Liang, Jianfeng Ma, Yinbin Miao, Da Kuang, Xiangdong Meng, Robert H. Deng
Research Collection School Of Computing and Information Systems
To achieve the search over encrypted data in cloud server, Searchable Encryption (SE) has attracted extensive attention from both academic and industrial fields. The existing Bloom filter-based SE schemes can achieve similarity search, but will generally incur high false positive rates, and even leak the privacy of values in Bloom filters (BF). To solve the above problems, we first propose a basic Privacy-preserving Bloom filter-based Keyword Search scheme using the Circular Shift and Coalesce-Bloom Filter (CSC-BF) and Symmetric-key Hidden Vector Encryption (SHVE) technology (namely PBKS), which can achieve effective search while protecting the values in BFs. Then, we design a …
Krover: A Symbolic Execution Engine For Dynamic Kernel Analysis, Pansilu Madhura Bhashana Pitigalaarachchi Pitigala Arachchillage, Xuhua Ding, Haiqing Qiu, Haoxin Tu, Jiaqi Hong, Lingxiao Jiang
Krover: A Symbolic Execution Engine For Dynamic Kernel Analysis, Pansilu Madhura Bhashana Pitigalaarachchi Pitigala Arachchillage, Xuhua Ding, Haiqing Qiu, Haoxin Tu, Jiaqi Hong, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
We present KRover, a novel kernel symbolic execution engine catered for dynamic kernel analysis such as vulnerability analysis and exploit generation. Different from existing symbolic execution engines, KRover operates directly upon a live kernel thread's virtual memory and weaves symbolic execution into the target's native executions. KRover is compact as it neither lifts the target binary to an intermediary representation nor uses QEMU or dynamic binary translation. Benchmarked against S2E, our performance experiments show that KRover is up to 50 times faster but with one tenth to one quarter of S2E memory cost. As shown in our four case studies, …