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- Title
- Event detection in surveillance video.
- Creator
- Castellanos Jimenez, Ricardo Augusto., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Digital video is being used widely in a variety of applications such as entertainment, surveillance and security. Large amount of video in surveillance and security requires systems capable to processing video to automatically detect and recognize events to alleviate the load on humans and enable preventive actions when events are detected. The main objective of this work is the analysis of computer vision techniques and algorithms used to perform automatic detection of events in video...
Show moreDigital video is being used widely in a variety of applications such as entertainment, surveillance and security. Large amount of video in surveillance and security requires systems capable to processing video to automatically detect and recognize events to alleviate the load on humans and enable preventive actions when events are detected. The main objective of this work is the analysis of computer vision techniques and algorithms used to perform automatic detection of events in video sequences. This thesis presents a surveillance system based on optical flow and background subtraction concepts to detect events based on a motion analysis, using an event probability zone definition. Advantages, limitations, capabilities and possible solution alternatives are also discussed. The result is a system capable of detecting events of objects moving in opposing direction to a predefined condition or running in the scene, with precision greater than 50% and recall greater than 80%.
Show less - Date Issued
- 2010
- PURL
- http://purl.flvc.org/FAU/1870694
- Subject Headings
- Computer systems, Security measures, Image processing, Digital techniques, Imaging systems, Mathematical models, Pattern recognition systems, Computer vision, Digital video
- Format
- Document (PDF)
- Title
- Adaptive power control in 802.11 networks.
- Creator
- Dural, Serkan., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
IEEE 802.11 networks successfully satisfy high data demands and are cheaper compared to cellular networks. Modern mobile computers and phones are equipped with 802.11 and are VoIP capable. Current network designs do not dynamically accommodate changes in the usage. We propose a dynamic power control algorithm that provides greater capacity within a limited geographic region. Most other power algorithms necessitate changes in 802.11 requiring hardware changes. Proposed algorithm only requires...
Show moreIEEE 802.11 networks successfully satisfy high data demands and are cheaper compared to cellular networks. Modern mobile computers and phones are equipped with 802.11 and are VoIP capable. Current network designs do not dynamically accommodate changes in the usage. We propose a dynamic power control algorithm that provides greater capacity within a limited geographic region. Most other power algorithms necessitate changes in 802.11 requiring hardware changes. Proposed algorithm only requires firmware updates to enable dynamic control of APs transmit power. We use earlier studies to determine the limit of the number of users to optimize power. By lowering transmit power of APs with large number of users, we can effectively decrease the cell size. The resulting gap is then covered by dynamically activating additional APs. This also provides greater flexibility and reduces the network planning costs.
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/221941
- Subject Headings
- IEEE 802.11 (Standard), Computer networks, Security measures, Computer network protocols, Mobile communication systems, Power supply
- Format
- Document (PDF)
- Title
- A class-based search system in unstructured peer-to-peer networks.
- Creator
- Huang, Juncheng., Florida Atlantic University, Wu, Jie
- Abstract/Description
-
Efficient searching is one of the important design issues in peer-to-peer (P2P) networks. Among various searching techniques, semantic-based searching has drawn significant attention recently. Gnutella-like efficient searching system (GES) [29] is such a system. GES derives node vector , a semantic summary of all documents on a node based on vector space model (VSM). The node-based topology adaptation algorithm and search protocol are then discussed. However, when there are many categories of...
Show moreEfficient searching is one of the important design issues in peer-to-peer (P2P) networks. Among various searching techniques, semantic-based searching has drawn significant attention recently. Gnutella-like efficient searching system (GES) [29] is such a system. GES derives node vector , a semantic summary of all documents on a node based on vector space model (VSM). The node-based topology adaptation algorithm and search protocol are then discussed. However, when there are many categories of documents at each node, the node vector representation may be inaccurate. We extend the idea of GES and present a class-based search system (CSS). It makes use of a document clustering algorithm: OSKM [27] to cluster all documents on a node into several classes. Each class can be viewed as a virtual node. As a result, class vector replaces node vector and plays an important role in class-based topology adaptation and search process, which makes CSS very efficient. Our simulation demonstrates that CSS outperforms GES.
Show less - Date Issued
- 2006
- PURL
- http://purl.flvc.org/fcla/dt/13367
- Subject Headings
- Peer-to-peer architecture (Computer networks), Management information systems, Computer security, Cascading style sheets, Web sites--Design
- Format
- Document (PDF)
- Title
- DEEP LEARNING BASED ANOMALY DETECTION IN SPACE SYSTEMS AND OPERATIONS.
- Creator
- Akbarian, Hamid, Mahgoub, Imadeldin, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
The relentless expansion of space exploration necessitates the development of robust and dependable anomaly detection systems (ADS) to safeguard the safety and efficacy of space missions. Conventional anomaly detection methods often falter in the face of the intricate and nuanced dynamics of space systems, resulting in a proliferation of false positives and/or false negatives. In this study, we explore into cutting-edge techniques in deep learning (DL) to tackle the challenges inherent in ADS...
Show moreThe relentless expansion of space exploration necessitates the development of robust and dependable anomaly detection systems (ADS) to safeguard the safety and efficacy of space missions. Conventional anomaly detection methods often falter in the face of the intricate and nuanced dynamics of space systems, resulting in a proliferation of false positives and/or false negatives. In this study, we explore into cutting-edge techniques in deep learning (DL) to tackle the challenges inherent in ADS. This research offers an in-depth examination of recent breakthroughs and hurdles in deep learning-driven anomaly detection tailored specifically for space systems and operations. A key advantage of deep learning-based anomaly detection lies in its adaptability to the diverse data encountered in space missions. For instance, Convolutional Neural Networks (CNNs) excel at capturing spatial dependencies in high-dimensional data, rendering them well-suited for tasks such as satellite imagery analysis. Conversely, Recurrent Neural Networks (RNNs), with their temporal modeling prowess, excel in identifying anomalies in time-series data generated by spacecraft sensors. Despite the potential of deep learning, several challenges persist in its application to anomaly detection in space systems. The scarcity of labeled data presents a formidable hurdle, as acquiring labeled anomalies during space operations is often prohibitively expensive and impractical. Additionally, the interpretability of deep learning models remains a concern, particularly in mission-critical scenarios where human operators need to comprehend the rationale behind anomaly predictions.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014390
- Subject Headings
- Anomaly detection (Computer security), Outer space—Exploration, Deep learning (Machine learning), Neural networks (Computer science), Convolutional neural networks
- Format
- Document (PDF)
- Title
- An innovative pixel scoring method for watermarking of binary document images.
- Creator
- Furht, Borko, Muharemagic, Edin
- Date Issued
- 2008-07-09 - 2006-07-12
- PURL
- http://purl.flvc.org/fcla/dt/363492
- Subject Headings
- Digital watermarking., Multimedia systems --Security measures., Data encryption (Computer science) --Technological innovations.
- Format
- Document (PDF)
- Title
- New approaches to encryption and steganography for digital videos.
- Creator
- Furht, Borko, Socek, Daniel, Kalva, Hari, Magliveras, Spyros S., Marques, Oge, Culibrk, Dubravko
- Date Issued
- 2007
- PURL
- http://purl.flvc.org/fcla/dt/337435
- Subject Headings
- Multimedia systems --Security measures., Digital video., Digital watermarking., Data encryption (Computer science) --Technological innovations., Cryptography.
- Format
- Document (PDF)
- Title
- Content identification using video tomography.
- Creator
- Leon, Gustavo A., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Video identification or copy detection is a challenging problem and is becoming increasingly important with the popularity of online video services. The problem addressed in this thesis is the identification of a given video clip in a given set of videos. For a given query video, the system returns all the instance of the video in the data set. This identification system uses video signatures based on video tomography. A robust and low complexity video signature is designed and implemented....
Show moreVideo identification or copy detection is a challenging problem and is becoming increasingly important with the popularity of online video services. The problem addressed in this thesis is the identification of a given video clip in a given set of videos. For a given query video, the system returns all the instance of the video in the data set. This identification system uses video signatures based on video tomography. A robust and low complexity video signature is designed and implemented. The nature of the signature makes it independent to the most commonly video transformations. The signatures are generated for video shots and not individual frames, resulting in a compact signature of 64 bytes per video shot. The signatures are matched using simple Euclidean distance metric. The results show that videos can be identified with 100% recall and over 93% precision. The experiments included several transformations on videos.
Show less - Date Issued
- 2008
- PURL
- http://purl.flvc.org/FAU/2783207
- Subject Headings
- Biometric identification, High performance computing, Image processing, Digital techniques, Multimedia systems, Security measures
- Format
- Document (PDF)
- Title
- Deep Learning for Android Application Ransomware Detection.
- Creator
- Wongsupa, Panupong, Zhu, Xingquan, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Smartphones and mobile tablets are rapidly growing, and very important nowadays. The most popular mobile operating system since 2012 has been Android. Android is an open source platform that allows developers to take full advantage of both the operating system and the applications itself. However, due to the open source community of an Android platform, some Android developers took advantage of this and created countless malicious applications such as Trojan, Malware, and Ransomware. All...
Show moreSmartphones and mobile tablets are rapidly growing, and very important nowadays. The most popular mobile operating system since 2012 has been Android. Android is an open source platform that allows developers to take full advantage of both the operating system and the applications itself. However, due to the open source community of an Android platform, some Android developers took advantage of this and created countless malicious applications such as Trojan, Malware, and Ransomware. All which are currently hidden in a large number of benign apps in official Android markets, such as Google PlayStore, and Amazon. Ransomware is a malware that once infected the victim’s device. It will encrypt files, unlock device system, and display a popup message which asks the victim to pay ransom in order to unlock their device or system which may include medical devices that connect through the internet. In this research, we propose to combine permission and API calls, then use Deep Learning techniques to detect ransomware apps from the Android market. Permissions setting and API calls are extracted from each app file by using a python library called AndroGuard. We are using Permissions and API call features to characterize each application, which can identify which application has potential to be ransomware or is benign. We implement our Android Ransomware Detection framework based on Keras, which uses MLP with back-propagation and a supervised algorithm. We used our method with experiments based on real-world applications with over 2000 benign applications and 1000 ransomware applications. The dataset came from ARGUS’s lab [1] which validated algorithm performance and selected the best architecture for the multi-layer perceptron (MLP) by trained our dataset with 6 various of MLP structures. Our experiments and validations show that the MLPs have over 3 hidden layers with medium sized of neurons achieved good results on both accuracy and AUC score of 98%. The worst score is approximately 45% to 60% and are from MLPs that have 2 hidden layers with large number of neurons.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013151
- Subject Headings
- Deep learning, Android (Electronic resource)--Security measures, Malware (Computer software)--Prevention
- Format
- Document (PDF)
- Title
- Object detection in low resolution video sequences.
- Creator
- Pava, Diego F., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
With augmenting security concerns and decreasing costs of surveillance and computing equipment, research on automated systems for object detection has been increasing, but the majority of the studies focus their attention on sequences where high resolution objects are present. The main objective of this work is the detection and extraction of information of low resolution objects (e.g. objects that are so far away from the camera that they occupy only tens of pixels) in order to provide a...
Show moreWith augmenting security concerns and decreasing costs of surveillance and computing equipment, research on automated systems for object detection has been increasing, but the majority of the studies focus their attention on sequences where high resolution objects are present. The main objective of this work is the detection and extraction of information of low resolution objects (e.g. objects that are so far away from the camera that they occupy only tens of pixels) in order to provide a base for higher level information operations such as classification and behavioral analysis. The system proposed is composed of four stages (preprocessing, background modeling, information extraction, and post processing) and uses context based region of importance selection, histogram equalization, background subtraction and morphological filtering techniques. The result is a system capable of detecting and tracking low resolution objects in a controlled background scene which can be a base for systems with higher complexity.
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/186685
- Subject Headings
- Computer systems, Security measures, Remote sensing, Image processing, Digital techniques, Imaging systems, Mathematical models
- Format
- Document (PDF)
- Title
- A Biometrics Based Secure Communication Scheme for Bluetooth Environment.
- Creator
- Soni, Puneet, Pandya, Abhijit S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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A novel personnel authentication and verification system for devices communicating through Bluetooth protocol has been proposed in this thesis. Unlike existing verification systems which provide password or a PIN as a key, the system uses biometrics features as a key. In the implementation of the scheme, ridges and bifurcation based parameters are derived to generate a 128 bit Bluetooth pairing PIN. In this thesis a unique translational and rotational invariant feature set has been developed....
Show moreA novel personnel authentication and verification system for devices communicating through Bluetooth protocol has been proposed in this thesis. Unlike existing verification systems which provide password or a PIN as a key, the system uses biometrics features as a key. In the implementation of the scheme, ridges and bifurcation based parameters are derived to generate a 128 bit Bluetooth pairing PIN. In this thesis a unique translational and rotational invariant feature set has been developed. These extracted feature data, unlike traditional systems which include the extracted data into payload, is used for device connection by generating the 128 bit PIN. The system performance is analyzed using the pairing PIN for inter-sample and intra-sample recognition. To validate the stability of the system the performance is analyzed with external samples which are not a part of the internal database.
Show less - Date Issued
- 2007
- PURL
- http://purl.flvc.org/fau/fd/FA00012556
- Subject Headings
- Bluetooth technology--Security measures, Network performance (Telecommunication), Computer network protocols
- Format
- Document (PDF)
- Title
- Signature schemes in single and multi-user settings.
- Creator
- Villanyi, Viktoria., Charles E. Schmidt College of Science, Department of Mathematical Sciences
- Abstract/Description
-
In the first chapters we will give a short introduction to signature schemes in single and multi-user settings. We give the definition of a signature scheme and explain a group of possible attacks on them. In Chapter 6 we give a construction which derives a subliminal-free RSA public key. In the construction we use a computationally binding and unconditionally hiding commitment scheme. To establish a subliminal-free RSA modulus n, we have to construct the secret primes p and q. To prove p and...
Show moreIn the first chapters we will give a short introduction to signature schemes in single and multi-user settings. We give the definition of a signature scheme and explain a group of possible attacks on them. In Chapter 6 we give a construction which derives a subliminal-free RSA public key. In the construction we use a computationally binding and unconditionally hiding commitment scheme. To establish a subliminal-free RSA modulus n, we have to construct the secret primes p and q. To prove p and q are primes we use Lehmann's primality test on the commitments. The chapter is based on the paper, "RSA signature schemes with subliminal-free public key" (Tatra Mountains Mathematical Publications 41 (2008)). In chapter 7 a one-time signature scheme using run-length encoding is presented, which in the random oracle model offers security against chosen-message attacks. For parameters of interest, the proposed scheme enables about 33% faster verification with a comparable signature size than a construction of Merkle and Winternitz. The public key size remains unchanged (1 hash value). The main cost for the faster verification is an increase in the time required for signing messages and for key generation. The chapter is based on the paper "A one-time signature using run-length encoding" (Information Processing Letters Vol. 108, Issue 4, (2008)).
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/215289
- Subject Headings
- Information technology, Security measures, Cryptography, Coding theory, Data encryption (Computer science), DIgital watermarking
- Format
- Document (PDF)
- Title
- Smart campus.
- Creator
- Danda, Naga Prakash, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The Smart Campus project envisions a university campus where technology assists faculty, staff, students and visitors to improve and more efficiently accomplish their daily activities. The objective of this project is to develop a smart phone application that assists users in finding a certain location on campus, locating their friends and professors, interacting with any student or professors of the campus, get the count of users at certain locations and remain updated about all the events...
Show moreThe Smart Campus project envisions a university campus where technology assists faculty, staff, students and visitors to improve and more efficiently accomplish their daily activities. The objective of this project is to develop a smart phone application that assists users in finding a certain location on campus, locating their friends and professors, interacting with any student or professors of the campus, get the count of users at certain locations and remain updated about all the events and campus news. Through this project, an idea of ‘Futuristic Social Network’ in a Campus is modeled and developed on Android platform.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004098, http://purl.flvc.org/fau/fd/FA00004098
- Subject Headings
- Mobile communication systems -- Security measures, Technological innovations -- Social aspects, Ubiquitous computing, Universities and colleges -- Design
- Format
- Document (PDF)
- Title
- An authorization model for object-oriented and semantic databases.
- Creator
- Song, Haiyan., Florida Atlantic University, Fernandez, Eduardo B., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The incorporation of object-oriented and semantic modeling concepts to databases is one of the most significant advances in the evolution of database systems. Among the many issues brought along by this integration, one that becomes important is the protection of the information. This thesis presents an authorization model that applies two basic aspects: control of users' access to data values, and control of administrators' access to data definitions and authorization rules. The model...
Show moreThe incorporation of object-oriented and semantic modeling concepts to databases is one of the most significant advances in the evolution of database systems. Among the many issues brought along by this integration, one that becomes important is the protection of the information. This thesis presents an authorization model that applies two basic aspects: control of users' access to data values, and control of administrators' access to data definitions and authorization rules. The model consists of a set of policies, a structure for authorization rules, algorithms for access request validation and procedures for administrative functions. Even though this model is developed in the context of a particular data model, the discussion is sufficiently general and can be applied to similar environments.
Show less - Date Issued
- 1990
- PURL
- http://purl.flvc.org/fcla/dt/14592
- Subject Headings
- Object-oriented databases, Data base security, Computers--Access control
- Format
- Document (PDF)
- Title
- VoIP Network Security and Forensic Models using Patterns.
- Creator
- Pelaez, Juan C., Fernandez, Eduardo B., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Voice over Internet Protocol (VoIP) networks is becoming the most popular telephony system in the world. However, studies of the security of VoIP networks are still in their infancy. VoIP devices and networks are commonly attacked, and it is therefore necessary to analyze the threats against the converged network and the techniques that exist today to stop or mitigate these attacks. We also need to understand what evidence can be obtained from the VoIP system after an attack has occurred....
Show moreVoice over Internet Protocol (VoIP) networks is becoming the most popular telephony system in the world. However, studies of the security of VoIP networks are still in their infancy. VoIP devices and networks are commonly attacked, and it is therefore necessary to analyze the threats against the converged network and the techniques that exist today to stop or mitigate these attacks. We also need to understand what evidence can be obtained from the VoIP system after an attack has occurred. Many of these attacks occur in similar ways in different contexts or environments. Generic solutions to these issues can be expressed as patterns. A pattern can be used to guide the design or simulation of VoIP systems as an abstract solution to a problem in this environment. Patterns have shown their value in developing good quality software and we expect that their application to VoIP will also prove valuable to build secure systems. This dissertation presents a variety of patterns (architectural, attack, forensic and security patterns). These patterns will help forensic analysts as well, as secure systems developers because they provide a systematic approach to structure the required information and help understand system weaknesses. The patterns will also allow us to specify, analyze and implement network security investigations for different architectures. The pattern system uses object-oriented modeling (Unified Modeling Language) as a way to formalize the information and dynamics of attacks and systems.
Show less - Date Issued
- 2007
- PURL
- http://purl.flvc.org/fau/fd/FA00012576
- Subject Headings
- Internet telephony--Security measures, Computer network protocols, Global system for mobile communications, Software engineering
- Format
- Document (PDF)
- Title
- MULTI-CLASS CLASSIFICATION TECHNIQUE TO DETECT IOT ATTACKS IN REAL TIME.
- Creator
- Alrefaei, Ahmed, Ilyas, Mohammad, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
The Internet of Things (IoT) has undergone remarkable expansion in recent years, leading to a proliferation of devices capable of connecting to the internet, collecting data, and sharing information. However, this rapid growth has also introduced a myriad of security challenges, resulting in an uptick in cyber-attacks targeting IoT infrastructures. To mitigate these threats and ensure the integrity of data, researchers have been actively engaged in the development of robust Intrusion...
Show moreThe Internet of Things (IoT) has undergone remarkable expansion in recent years, leading to a proliferation of devices capable of connecting to the internet, collecting data, and sharing information. However, this rapid growth has also introduced a myriad of security challenges, resulting in an uptick in cyber-attacks targeting IoT infrastructures. To mitigate these threats and ensure the integrity of data, researchers have been actively engaged in the development of robust Intrusion Detection Systems (IDS) utilizing various machine learning (ML) techniques. This dissertation presents a comprehensive overview of three distinct approaches toward IoT intrusion detection, each leveraging ML methodologies to enhance security measures. The first approach focuses on a multi-class classification algorithm, integrating models such as random forest, logistic regression (LR), decision tree (DT), and Xgboost. Through meticulous evaluation utilizing evaluation metrics including F1 score, recall, and precision under the Receiver Operating Characteristics (ROC) curve, this approach demonstrates a remarkable 99 % accuracy in detecting IoT attacks. In the second approach, a deep ensemble model comprising Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) architectures is proposed for intrusion detection in IoT environments. Evaluation on the UNSW 2018 IoT Botnet dataset showcases the proficiency of this approach, achieving an accuracy of 98.4 % in identifying malicious activities. Lastly, the dissertation explores a real-time Intrusion Detection System (IDS) framework deployed within the Pyspark architecture, aimed at efficiently detecting IoT attacks while minimizing detection time.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014498
- Subject Headings
- Internet of things, Intrusion detection systems (Computer security), Deep learning (Machine learning)
- Format
- Document (PDF)
- Title
- BINARY AND MULTI-CLASS INTRUSION DETECTION IN IOT USING STANDALONE AND HYBRID MACHINE AND DEEP LEARNING MODELS.
- Creator
- Akif, MD Ahnaf, Mahgoub, Imadeldin, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
Maintaining security in IoT systems depends on intrusion detection since these networks' sensitivity to cyber-attacks is growing. Based on the IoT23 dataset, this study explores the use of several Machine Learning (ML) and Deep Learning (DL) along with the hybrid models for binary and multi-class intrusion detection. The standalone machine and deep learning models like Random Forest (RF), Extreme Gradient Boosting (XGBoost), Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Support...
Show moreMaintaining security in IoT systems depends on intrusion detection since these networks' sensitivity to cyber-attacks is growing. Based on the IoT23 dataset, this study explores the use of several Machine Learning (ML) and Deep Learning (DL) along with the hybrid models for binary and multi-class intrusion detection. The standalone machine and deep learning models like Random Forest (RF), Extreme Gradient Boosting (XGBoost), Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Convolutional Neural Network (CNN) were used. Furthermore, two hybrid models were created by combining machine learning techniques: RF, XGBoost, AdaBoost, KNN, and SVM and these hybrid models were voting based hybrid classifier. Where one is for binary, and the other one is for multi-class classification. These models were tested using precision, recall, accuracy, and F1-score criteria and compared the performance of each model. This work thoroughly explains how hybrid, standalone ML and DL techniques could improve IDS (Intrusion Detection System) in terms of accuracy and scalability in IoT (Internet of Things).
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014514
- Subject Headings
- Internet of things, Machine learning, Deep learning (Machine learning), Intrusion detection systems (Computer security)
- Format
- Document (PDF)
- Title
- Adaptive hierarchical weighted fair queuing scheduling in WiMAX networks.
- Creator
- AL-Ghanem, Waleed Khalid, Ilyas, Mohammad, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The growing demand for faster connection to the Internet service and wireless multimedia applications has motivated the development of broadband wireless access technologies in recent years. WiMAX has enabled convergence of mobile and fixed broadband networks through a common wide-area radio-access technology and flexible network architecture. Scheduling is a fundamental component in resource management in WiMAX networks and plays the main role in meeting QoS requirements such as delay,...
Show moreThe growing demand for faster connection to the Internet service and wireless multimedia applications has motivated the development of broadband wireless access technologies in recent years. WiMAX has enabled convergence of mobile and fixed broadband networks through a common wide-area radio-access technology and flexible network architecture. Scheduling is a fundamental component in resource management in WiMAX networks and plays the main role in meeting QoS requirements such as delay, throughput and packet loss for different classes of service. In this dissertation work, the performance of uplink schedulers at the fixed WiMAX MAC layer has been considered, we proposed an Adaptive Hierarchical Weighted Fair Queuing Scheduling algorithm, the new scheduling algorithm adapts to changes in traffic, at the same time; it is able to heuristically enhance the performance of WiMAX network under most circumstances. The heuristic nature of this scheduling algorithm enables the MAC layer to meet the QoS requirements of the users. The performance of this adaptive WiMAX Uplink algorithm has been evaluated by simulation using MATLAB. Results indicate that the algorithm is efficient in scheduling the Base Stations’ traffic loads, and improves QoS. The utilization of relay stations is studied and simulation results are compared with the case without using relay stations. The results show that the proposed scheduling algorithm improves Quality of Service of WiMAX system.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004178, http://purl.flvc.org/fau/fd/FA00004178
- Subject Headings
- Computer networks -- Technological innovations, Optical fiber communication, Wireless communication systems -- Technological innovations, Wireless metropolitan area networks -- Security measures
- Format
- Document (PDF)
- Title
- Physical Layer Security of Wireless Transmissions Over Fading Channels.
- Creator
- Blanc, Sadrac, Aalo, Valentine A., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The open nature of the wireless medium makes the wireless communication susceptible to eavesdropping attacks. In addition, fading and shadowing significantly degrade the performance of the communication system in the wireless networks. A versatile approach to circumvent the issues of eavesdropping attacks while exploiting the physical properties of the wireless channel is the so-called physical layer-security. In this work, we consider a model in which two legitimate users communicate in the...
Show moreThe open nature of the wireless medium makes the wireless communication susceptible to eavesdropping attacks. In addition, fading and shadowing significantly degrade the performance of the communication system in the wireless networks. A versatile approach to circumvent the issues of eavesdropping attacks while exploiting the physical properties of the wireless channel is the so-called physical layer-security. In this work, we consider a model in which two legitimate users communicate in the presence of an eavesdropper. We investigate the performance of the wireless network at the physical layer that is subject to a variety of fading environments that may be modeled by the Rayleigh, Nakagami-m, and Generalized-K distributions, to mention a few. We use the secrecy outage probability (SOP) as the standard performance metrics to study the performance of the wireless networks. We propose two different approaches to compute the secrecy outage probability, and derive explicit expressions for the secrecy outage probability that allow us to characterize the performance of the wireless networks. Specifically, we use a direct integration approach as well as a Taylor series base approach to evaluate the secrecy outage probability. Finally, we use computer simulations, based on MATLAB, to confirm the analytical results.
Show less - Date Issued
- 2016
- PURL
- http://purl.flvc.org/fau/fd/FA00004729, http://purl.flvc.org/fau/fd/FA00004729
- Subject Headings
- Data encryption (Computer science), Digital communications -- Reliability -- Mathematics, Internetworking (Telecommunication), Radio wave propagation, Wireless communication systems -- Security measures
- Format
- Document (PDF)
- Title
- Patterns for secure interactions in social networks in Web 2.0.
- Creator
- Marin, Carolina, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
A social network is a structure of individuals and organizations, which are connected by one or more types of interdependency, such as friendship, affinity, common interests or knowledge. Social networks use Web 2.0 technology, which is mostly based on a service-oriented architecture. We are studying patterns for social networks in this environment. A pattern is an encapsulated solution to a software problem in a given context, secure threats are possible in this context. We present a...
Show moreA social network is a structure of individuals and organizations, which are connected by one or more types of interdependency, such as friendship, affinity, common interests or knowledge. Social networks use Web 2.0 technology, which is mostly based on a service-oriented architecture. We are studying patterns for social networks in this environment. A pattern is an encapsulated solution to a software problem in a given context, secure threats are possible in this context. We present a collection of patterns associated with the most important aspects of social networks, with emphasis on controlling the actions of the users of these networks.
Show less - Date Issued
- 2012
- PURL
- http://purl.flvc.org/FAU/3342203
- Subject Headings
- Web 2.0, Computer network architectures, Online social networks, Security measures, Social media, Pattern recognition systems
- Format
- Document (PDF)
- Title
- Efficient implementation of zero-knowledge based identification protocols.
- Creator
- Barella, Michelle Elizabeth., Florida Atlantic University, Mullin, Ronald C.
- Abstract/Description
-
A zero knowledge identification protocol is an interactive proof system that allows a person to prove that he knows a secret key associated with his identity without revealing the secret key. This type of protocol is the topic of a fairy tale, by Gustavus Simmons called the King's Dilemma, about a king and the problem he has with thieves impersonating his tax collectors. It describes a zero-knowledge identification protocol that will rid the king of his problem. I present this system, the...
Show moreA zero knowledge identification protocol is an interactive proof system that allows a person to prove that he knows a secret key associated with his identity without revealing the secret key. This type of protocol is the topic of a fairy tale, by Gustavus Simmons called the King's Dilemma, about a king and the problem he has with thieves impersonating his tax collectors. It describes a zero-knowledge identification protocol that will rid the king of his problem. I present this system, the motivation for this thesis, and the transformations from this protocol, that uses lead weights and containers, to protocols that use mathematical elements. The security of these protocols is determined by the complexity of the underlying mathematical problem, such as the knapsack and discrete logarithm problem, and three properties: completeness, soundness, and zero knowledge.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13181
- Subject Headings
- Cryptography, Telecommunication systems--Security measures, Knapsack problem (Mathematics), Mathematical optimization, Finite fields (Algebra), Data encryption (Computer science)
- Format
- Document (PDF)