Current Search: Internet -- Security measures (x)
View All Items
- Title
- A Network Telescope Approach for Inferring and Characterizing IoT Exploitations.
- Creator
- Neshenko, Nataliia, Bou-Harb, Elias, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
While the seamless interconnection of IoT devices with the physical realm is envisioned to bring a plethora of critical improvements on many aspects and in diverse domains, it will undoubtedly pave the way for attackers that will target and exploit such devices, threatening the integrity of their data and the reliability of critical infrastructure. The aim of this thesis is to generate cyber threat intelligence related to Internet-scale inference and evaluation of malicious activities...
Show moreWhile the seamless interconnection of IoT devices with the physical realm is envisioned to bring a plethora of critical improvements on many aspects and in diverse domains, it will undoubtedly pave the way for attackers that will target and exploit such devices, threatening the integrity of their data and the reliability of critical infrastructure. The aim of this thesis is to generate cyber threat intelligence related to Internet-scale inference and evaluation of malicious activities generated by compromised IoT devices to facilitate prompt detection, mitigation and prevention of IoT exploitation. In this context, we initially provide a unique taxonomy, which sheds the light on IoT vulnerabilities from five di↵erent perspectives. Subsequently, we address the task of inference and characterization of IoT maliciousness by leveraging active and passive measurements. To support large-scale empirical data analytics in the context of IoT, we made available corresponding raw data through an authenticated platform.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013089
- Subject Headings
- Internet of things., Internet of things--Security measures., Cyber intelligence (Computer security)
- Format
- Document (PDF)
- Title
- Data mining heuristic-¬based malware detection for android applications.
- Creator
- Peiravian, Naser, Zhu, Xingquan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The Google Android mobile phone platform is one of the dominant smartphone operating systems on the market. The open source Android platform allows developers to take full advantage of the mobile operation system, but also raises significant issues related to malicious applications (Apps). The popularity of Android platform draws attention of many developers which also attracts the attention of cybercriminals to develop different kinds of malware to be inserted into the Google Android Market...
Show moreThe Google Android mobile phone platform is one of the dominant smartphone operating systems on the market. The open source Android platform allows developers to take full advantage of the mobile operation system, but also raises significant issues related to malicious applications (Apps). The popularity of Android platform draws attention of many developers which also attracts the attention of cybercriminals to develop different kinds of malware to be inserted into the Google Android Market or other third party markets as safe applications. In this thesis, we propose to combine permission, API (Application Program Interface) calls and function calls to build a Heuristic-Based framework for the detection of malicious Android Apps. In our design, the permission is extracted from each App’s profile information and the APIs are extracted from the packed App file by using packages and classes to represent API calls. By using permissions, API calls and function calls as features to characterize each of Apps, we can develop a classifier by data mining techniques to identify whether an App is potentially malicious or not. An inherent advantage of our method is that it does not need to involve any dynamic tracking of the system calls but only uses simple static analysis to find system functions from each App. In addition, Our Method can be generalized to all mobile applications due to the fact that APIs and function calls are always present for mobile Apps. Experiments on real-world Apps with more than 1200 malwares and 1200 benign samples validate the algorithm performance. Research paper published based on the work reported in this thesis: Naser Peiravian, Xingquan Zhu, Machine Learning for Android Malware Detection Using Permission and API Calls, in Proc. of the 25th IEEE International Conference on Tools with Artificial Intelligence (ICTAI) – Washington D.C, November 4-6, 2013.
Show less - Date Issued
- 2013
- PURL
- http://purl.flvc.org/fau/fd/FA0004045
- Subject Headings
- Computer networks -- Security measures, Data encryption (Computer science), Data structures (Computer science), Internet -- Security measures
- Format
- Document (PDF)
- Title
- Microservices-based approach for Healthcare Cybersecurity.
- Creator
- Trivedi, Ohm H., Shankar, Ravi, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Healthcare organizations, realizing the potential of the Internet of Things (IoT) technology, are rapidly adopting the technology to bring signi cant improvements in the quality and e ectiveness of the service. However, these smart and interconnected devices can act as a potential \back door" into a hospital's IT network, giving attack- ers access to sensitive information. As a result, cyber-attacks on medical IoT devices have been increasing since the last few years. It is a growing concern...
Show moreHealthcare organizations, realizing the potential of the Internet of Things (IoT) technology, are rapidly adopting the technology to bring signi cant improvements in the quality and e ectiveness of the service. However, these smart and interconnected devices can act as a potential \back door" into a hospital's IT network, giving attack- ers access to sensitive information. As a result, cyber-attacks on medical IoT devices have been increasing since the last few years. It is a growing concern for all the stakeholders involved, as the impact of such attacks is not just monetary or privacy loss, but the lives of many patients are also at risk. Considering the various kinds of IoT devices one may nd connected to a hospital's network, traditional host-centric security solutions (e.g. antivirus, software patches) are at odds with realistic IoT infrastructure (e.g. constrained hardware, lack of proper built-in security measures). There is a need for security solutions which consider the challenges of IoT devices like heterogeneity of technology and protocols used, limited resources in terms of battery and computation power, etc. Accordingly, the goals of this thesis have been: (1) to provide an in-depth understanding of vulnerabilities of medical IoT devices; (2) to in- troduce a novel approach which uses a microservices-based framework as an adaptive and agile security solution to address the issue. The thesis focuses on OS Fingerprint- ing attacks because of its signi cance for attackers to understand a target's network. In this thesis, we developed three microservices, each one designed to serve a speci c functionality. Each of these microservices has a small footprint with RAM usage of approximately 50 MB. We also suggest how microservices can be used in a real-life scenario as a software-based security solution to secure a hospital's network consisting of di erent IoT devices.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013140
- Subject Headings
- Cybersecurity, Healthcare, Internet of things--Security measures, Medical care--Information technology--Security measures
- Format
- Document (PDF)
- Title
- Security in voice over IP networks.
- Creator
- Pelaez, Juan C., Florida Atlantic University, Fernandez, Eduardo B., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Voice over IP (VoIP) is revolutionizing the global communications system by allowing human voice and fax information to travel over existing packet data networks along with traditional data packets. The convergence of voice and data in one simplified network brings both benefits and constraints to users. Among the several issues that need to be addressed when deploying this technology, security is one of the most critical. This thesis will present a combination of security patterns based on...
Show moreVoice over IP (VoIP) is revolutionizing the global communications system by allowing human voice and fax information to travel over existing packet data networks along with traditional data packets. The convergence of voice and data in one simplified network brings both benefits and constraints to users. Among the several issues that need to be addressed when deploying this technology, security is one of the most critical. This thesis will present a combination of security patterns based on the systematic analysis of attacks against a VoIP network and the existing techniques to mitigate these attacks, providing good practices for all IP telephony systems. The VoIP Security Patterns which are based on object-oriented modeling, will help network designers to improve the level of security not only in voice but also in data, video, and fax over IP networks.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13190
- Subject Headings
- Internet telephony--Security measures, Computer network protocols, Multimedia systems
- Format
- Document (PDF)
- Title
- Implementing security in an IP Multimedia Subsystem (IMS) next generation network - a case study.
- Creator
- Ortiz-Villajos, Jose M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The IP Multimedia Subsystem (IMS) has gone from just a step in the evolution of the GSM cellular architecture control core, to being the de-facto framework for Next Generation Network (NGN) implementations and deployments by operators world-wide, not only cellular mobile communications operators, but also fixed line, cable television, and alternative operators. With this transition from standards documents to the real world, engineers in these new multimedia communications companies need to...
Show moreThe IP Multimedia Subsystem (IMS) has gone from just a step in the evolution of the GSM cellular architecture control core, to being the de-facto framework for Next Generation Network (NGN) implementations and deployments by operators world-wide, not only cellular mobile communications operators, but also fixed line, cable television, and alternative operators. With this transition from standards documents to the real world, engineers in these new multimedia communications companies need to face the task of making these new networks secure against threats and real attacks that were not a part of the previous generation of networks. We present the IMS and other competing frameworks, we analyze the security issues, we present the topic of Security Patterns, we introduce several new patterns, including the basis for a Generic Network pattern, and we apply these concepts to designing a security architecture for a fictitious 3G operator using IMS for the control core.
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/186763
- Subject Headings
- Electronic digital computers, Programming, Computer networks, Security measures, TCP/IP (Computer network protocol), Security measures, Internet Protocol Multimedia Subsystem (IMS), Security measures, Multimedia communications, Security measures
- Format
- Document (PDF)
- Title
- MACHINE LEARNING ALGORITHMS FOR PREDICTING BOTNET ATTACKS IN IOT NETWORKS.
- Creator
- Leevy, Joffrey, Khoshgoftaar, Taghi M., Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
The proliferation of Internet of Things (IoT) devices in various networks is being matched by an increase in related cybersecurity risks. To help counter these risks, big datasets such as Bot-IoT were designed to train machine learning algorithms on network-based intrusion detection for IoT devices. From a binary classification perspective, there is a high-class imbalance in Bot-IoT between each of the attack categories and the normal category, and also between the combined attack categories...
Show moreThe proliferation of Internet of Things (IoT) devices in various networks is being matched by an increase in related cybersecurity risks. To help counter these risks, big datasets such as Bot-IoT were designed to train machine learning algorithms on network-based intrusion detection for IoT devices. From a binary classification perspective, there is a high-class imbalance in Bot-IoT between each of the attack categories and the normal category, and also between the combined attack categories and the normal category. Within the scope of predicting botnet attacks in IoT networks, this dissertation demonstrates the usefulness and efficiency of novel machine learning methods, such as an easy-to-classify method and a unique set of ensemble feature selection techniques. The focus of this work is on the full Bot-IoT dataset, as well as each of the four attack categories of Bot-IoT, namely, Denial-of-Service (DoS), Distributed Denial-of-Service (DDoS), Reconnaissance, and Information Theft. Since resources and services become inaccessible during DoS and DDoS attacks, this interruption is costly to an organization in terms of both time and money. Reconnaissance attacks often signify the first stage of a cyberattack and preventing them from occurring usually means the end of the intended cyberattack. Information Theft attacks not only erode consumer confidence but may also compromise intellectual property and national security. For the DoS experiment, the ensemble feature selection approach led to the best performance, while for the DDoS experiment, the full set of Bot-IoT features resulted in the best performance. Regarding the Reconnaissance experiment, the ensemble feature selection approach effected the best performance. In relation to the Information Theft experiment, the ensemble feature selection techniques did not affect performance, positively or negatively. However, the ensemble feature selection approach is recommended for this experiment because feature reduction eases computational burden and may provide clarity through improved data visualization. For the full Bot-IoT big dataset, an explainable machine learning approach was taken using the Decision Tree classifier. An easy-to-learn Decision Tree model for predicting attacks was obtained with only three features, which is a significant result for big data.
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00013933
- Subject Headings
- Machine learning, Internet of things--Security measures, Big data, Intrusion detection systems (Computer security)
- Format
- Document (PDF)
- Title
- MODELING AND SECURITY IN CLOUD AND RELATED ECOSYSTEMS.
- Creator
- Syed, Madiha Haider, Fernandez, Eduardo B., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Software systems increasingly interact with each other, forming ecosystems. Cloud is one such ecosystem that has evolved and enabled other technologies like IoT and containers. Such systems are very complex and heterogeneous because their components can have diverse origins, functions, security policies, and communication protocols, which makes it difficult to comprehend, utilize and consequently secure them. Abstract architectural models can be used to handle this complexity and...
Show moreSoftware systems increasingly interact with each other, forming ecosystems. Cloud is one such ecosystem that has evolved and enabled other technologies like IoT and containers. Such systems are very complex and heterogeneous because their components can have diverse origins, functions, security policies, and communication protocols, which makes it difficult to comprehend, utilize and consequently secure them. Abstract architectural models can be used to handle this complexity and heterogeneity but there is lack of work on precise, implementation/vendor neutral and holistic models which represent ecosystem components and their mutual interactions. We attempted to find similarities in systems and generalize to create abstract models for adding security. We represented the ecosystem as a Reference architecture (RA) and the ecosystem units as patterns. We started with a pattern diagram which showed all the components involved along with their mutual interactions and dependencies. We added components to the already existent Cloud security RA (SRA). Containers, being relatively new virtualization technology, did not have a precise and holistic reference architecture. We have built a partial RA for containers by identifying and modeling components of the ecosystem. Container security issues were identified from the literature as well as analysis of our patterns. We added corresponding security countermeasures to container RA as security patterns to build a container SRA. Finally, using container SRA as an example, we demonstrated an approach for RA validation. We have also built a composite pattern for fog computing that is an intermediate platform between Cloud and IoT devices. We represented an attack, Distributed Denial of Service (DDoS) using IoT devices, in the form of a misuse pattern which explains it from the attacker’s perspective. We found this modelbased approach useful to build RAs in a flexible and incremental way as components can be identified and added as the ecosystems expand. This provided us better insight to analyze security issues across boundaries of individual ecosystems. A unified, precise and holistic view of the system is not just useful for adding or evaluating security, this approach can also be used to ensure compliance, privacy, safety, reliability and/or governance for cloud and related ecosystems. This is the first work we know of where patterns and RAs are used to represent ecosystems and analyze their security.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013345
- Subject Headings
- Software ecosystems, Cloud computing--Security measures, Internet of things, Software architecture--Security measures, Computer modeling
- 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)