Dynamic Taint Analysis for Automatic Detection, Analysis, and Signature Generation of Exploits on Commodity Software, Network and Distributed System Security Symposium Conference Proceedings : 2005

Designing secure blockchain-based access control scheme in IoT-enabled Internet of Drones deployment

The Internet of Medical Things (IoMT) is a kind of connected infrastructure of smart medical devices along with software applications, health systems and services. These medical devices and applications are connected to healthcare systems through the Internet. The Wi-Fi enabled devices facilitate machine-to-machine communication and link to the cloud platforms for data storage. IoMT has the ability to make accurate diagnoses, with fewer mistakes and lower costs of care. IoMT with smartphone applications permits the patients to exchange their health related confidential and private information to the healthcare experts (i.e., doctors) for the better control of diseases, and also for tracking and preventing chronic illnesses. Due to insecure communication among the entities involved in IoMT, an attacker can tamper with the confidential and private health related information for example an attacker can not only intercept the messages, but can also modify, delete or insert malicious messages during communication. To deal this sensitive issue, we design a novel blockchain enabled authentication key agreement protocol for IoMT environment, called BAKMP-IoMT. BAKMP-IoMT provides secure key management between implantable medical devices and personal servers and between personal servers and cloud servers. The legitimate users can also access the healthcare data from the cloud servers in a secure way. The entire healthcare data is stored in a blockchain maintained by the cloud servers. A detailed formal security including the security verification of BAKMP-IoMT using the widely-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool is performed to demonstrate its resilience against the different types of possible attack. The comparison of BAKMP-IoMT with relevant existing schemes is conducted which identifies that the proposed system furnishes better security and functionality, and also needs low communication and computational costs as compared to other schemes. Finally, the simulation of BAKMP-IoMT is conducted to demonstrate its impact on the performance parameters.

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BAKMP-IoMT: Design of Blockchain Enabled Authenticated Key Management Protocol for Internet of Medical Things Deployment

A blockchain-based Roadside Unit-assisted authentication and key agreement protocol for Internet of Vehicles

Internet of Things (IoT) is turning into an undeniably developing point of discussion in both research and industrial fields A key area that is witnessing a quick development in the utilization of IoT devices is the Internet of Vehicles (IoV), which allows information exchange among vehicles and infrastructures Notably, Artificial Intelligence (AI) has been widely adopted for solving challenging vehicular problems and managing the IoV infrastructure Despite the advantages AI carries for IoV, its deployment can be negatively affected by lacking computation resources and processing unreliable data On the other hand, Blockchain is a decentralized and distributed peer-to-peer network architecture that can be employed to empower security and resist against undesirable data modification However, integrating both technologies (ie, AI and Blockchain) exhausts, even more, the IoV infrastructure Therefore, we present in this paper an overview discussing the AI and Blockchain approaches and models for IoV and propose a new Vehicular Edge Computing based architecture embedding both technologies and overcoming the aforementioned limitations We then discuss the main challenges and give notice to the concerned parties and stakeholders about promising directions that arise from enabling the three technologies for providing smart, secure, and efficient IoV

AI, Blockchain, and Vehicular Edge Computing for Smart and Secure IoV: Challenges and Directions

Thanks to the rapid development in mobile vehicles and wireless technologies, the Internet of Vehicles (IoV) has become an attractive application that can provide a large number of mobile services for drivers. Vehicles can be informed of the mobile position, direction, speed, and other real-time information of nearby vehicles to avoid traffic jams and accidents. However, the environments of IoV could be dangerous in the absence of security protections. Due to the openness and self-organization of IoV, there are enormous malicious attackers. To guarantee the safety of mobile services, we propose an effective decentralized authentication mechanism for IoV on the basis of the consensus algorithm of blockchain technology. The simulation under the veins framework is carried out to verify the feasibility of the scheme in reducing the selfish behavior and malicious attacks in IoV.

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An Improved Authentication Scheme for Internet of Vehicles Based on Blockchain Technology

https://researchbank.swinburne.edu.au/file/8ad11282-95ea-4445-93ab-2130db4cb82e/1/2017-ruan-visualization_of_big.pdf

Visualization of big data security: a case study on the KDD99 cup data set

Aim/Purpose: This paper presents an exploratory case study into using 360° videos to present small segments of lecture content for IT students in an Australian University. The aim of this study was to understand; what is the impact of incorporating 360° videos into class content for students and teaching staff? In this study the 360° videos are described as “learning atoms”. Learning atoms are short duration videos (1 to 5 minutes) captured in 360°.Background: Within this paper we conducted experiments in the classroom using 360° videos to determine if they have an impact on student's feeling of presence with class content. Additionally, to follow up, how does the inclusion of 360° impact on the teaching experience.Methodology: The methodology used in this study focused on both quantitative and qualita-tive aspects. Data was captured at the same time during the teaching period to address the research questions. In order to gauge the feeling of presence within the classroom a short survey was administered to students in the undergraduate IT class at the start (pre) and end (post) of the semester using the same questions to measure any change.Contribution: The main contributions from this study were that we demonstrated there is a potential for providing an alternative ‘immersive’ content presentation for students. This alternative content took the form of 360° learning atoms, whereas further showed our nuance process for creating and publishing of these atoms.Findings: The results show that for students, learning atoms can help improve the sense of presence, particularly for remote students, however the interactive experience can take student’s attention away from the lecturer. The results present potential for providing an alternative ‘immersive’ content presentation for students, however problems for uptake are present for both students and teachers, such as image capture quality and file sizeImpact on Society: We foresee this approach as being a new approach to teaching students in higher education within online spaces to increase engagement and move towards having a richer virtual experience no matter the location.Future Research: Future research will be conducted to resolve whether presence and engagement is supported by the inclusion of 360° videos in the classroom.

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Virtually There: The Potential, Process and Problems of Using 360° Video in the Classroom

Virtual property theft is a serious problem that exists in virtual worlds. Legitimate users of these worlds invest considerable amounts of time, effort and real-world money into obtaining virtual property, but unfortunately, are becoming victims of theft in high numbers. It is reported that there are over 1 billion registered users of virtual worlds containing virtual property items worth an estimated US$50 billion dollars. The problem of virtual property theft is complex, involving many legal, social and technological issues. The software used to access virtual worlds is of great importance as they form the primary interface to these worlds and as such the primary interface to conduct virtual property theft. The security vulnerabilities of virtual world applications have not, to date, been examined. This study aims to use the process of software inspection to discover security vulnerabilities that may exist within virtual world software – vulnerabilities that enable virtual property theft to occur. Analyzing three well know virtual world applications World of Warcraft, Guild Wars and Entropia Universe, this research utilized security analysis tools and scenario testing with focus on authentication, trading, intruder detection and virtual property recovery. It was discovered that all three examples were susceptible to keylogging, mail and direct trade methods were the most likely method for transferring stolen items, intrusion detection is of critical concern to all VWEs tested, stolen items were unable to be recovered in all cases and lastly occurrences of theft were undetectable in all cases. The results gained in this study present the key problem areas which need to be addressed to improve security and reduce the occurrence of virtual property theft.

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Virtual World Security Inspection

With the development of information technology, thousands of devices are connected to the Internet, various types of data are accessed and transmitted through the network, which pose huge security threats while bringing convenience to people. In order to deal with security issues, many effective solutions have been given based on traditional machine learning. However, due to the characteristics of big data in cyber security, there exists a bottleneck for methods of traditional machine learning in improving security. Owning to the advantages of processing big data and high-dimensional data, new solutions for cyber security are provided based on deep learning. In this paper, the applications of deep learning are classified, analyzed and summarized in the field of cyber security, and the applications are compared between deep learning and traditional machine learning in the security field. The challenges and problems faced by deep learning in cyber security are analyzed and presented. The findings illustrate that deep learning has a better effect on some aspects of cyber security and should be considered as the first option.

Nicholas Patterson

Papers

An Improved Authentication Scheme for Internet of Vehicles Based on Blockchain Technology

Visualization of big data security: a case study on the KDD99 cup data set

Virtually There: The Potential, Process and Problems of Using 360° Video in the Classroom

Virtual World Security Inspection

Deep learning algorithms for cyber security applications: A survey