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Author

Meghan E. Hunt

Bio: Meghan E. Hunt is an academic researcher from University of Vermont. The author has contributed to research in topics: Emerging technologies & Cyberspace. The author has an hindex of 1, co-authored 1 publications receiving 9 citations.

Papers
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Journal ArticleDOI
19 May 2019
TL;DR: A review of relevant research in cybersecurity tools and technologies is performed, organized according to both active and passive Defensive Cyberspace Operations, which accounts for the bulk of the cyber research literature over the last two decades.
Abstract: The realm of cybersecurity is perhaps one of the most quickly evolving areas within today’s research space. New and emerging technologies, as well as the growth of cybersecurity environment...

17 citations


Cited by
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01 Jan 2013
TL;DR: The authors have introduced a new advanced symmetric key cryptographic method called NJJSAA which can be applied to encrypt data in sensor network or in mobile network and one can apply this method on top of any other standard algorithm such as DES, AES or RSA.
Abstract: In the present work the authors have introduced a new advanced symmetric key cryptographic method called NJJSAA. The authors introduced new bit manipulation method for data encryption and decryption of any file. Nath et al already developed some symmetric key methods [1, 2, 3, 4] where they have used some randomized key matrix for encryption and decryption methods. In the present work the authors have used a bit manipulation method which include bit exchange, right shift and XOR operation on the incoming bits. To exchange bits the authors used a randomized key matrix of size (16x16) using the method developed by Nath et al (1). The present method allows the multiple encryption and multiple decryption. To initiate the encryption process a user has to enter a text-key which may be maximum of 16 characters long. From the text-key the authors have calculated randomization number and the encryption number. The method used was developed by Nath et al (1). A slight change in the text-key will change the randomization number and the encryption number quite a lot. Multiple encryption using bit exchange, bit right shift and XOR operations makes the system very secured. The present method is a block cipher method and it can be applied to encrypt data in sensor network or in mobile network. The advantage of the present method is that one can apply this method on top of any other standard algorithm such as DES, AES or RSA. The method is suitable to encrypt any large or small file. There is a scope to further enhance the present method of encryption.

14 citations

Journal ArticleDOI
01 Mar 2022-Sensors
TL;DR: This survey focuses on Defensive Deception tactics deployed using the help of deep learning and machine learning algorithms, and culminates with a discussion about future directions, which helps address the important gaps in present Defensive Deceptions research.
Abstract: With information systems worldwide being attacked daily, analogies from traditional warfare are apt, and deception tactics have historically proven effective as both a strategy and a technique for Defense. Defensive Deception includes thinking like an attacker and determining the best strategy to counter common attack strategies. Defensive Deception tactics are beneficial at introducing uncertainty for adversaries, increasing their learning costs, and, as a result, lowering the likelihood of successful attacks. In cybersecurity, honeypots and honeytokens and camouflaging and moving target defense commonly employ Defensive Deception tactics. For a variety of purposes, deceptive and anti-deceptive technologies have been created. However, there is a critical need for a broad, comprehensive and quantitative framework that can help us deploy advanced deception technologies. Computational intelligence provides an appropriate set of tools for creating advanced deception frameworks. Computational intelligence comprises two significant families of artificial intelligence technologies: deep learning and machine learning. These strategies can be used in various situations in Defensive Deception technologies. This survey focuses on Defensive Deception tactics deployed using the help of deep learning and machine learning algorithms. Prior work has yielded insights, lessons, and limitations presented in this study. It culminates with a discussion about future directions, which helps address the important gaps in present Defensive Deception research.

9 citations

Proceedings ArticleDOI
01 Dec 2019
TL;DR: This paper proposes proactive antifragility as a new paradigm for the next generation of cyber defence approaches capable of taking into account the aforementioned system characteristics and environmental challenges.
Abstract: Recent advances in the Internet of Things (IoT) and, more generally, distributed computing research have given rise to various edge-oriented computing paradigms including Edge-, Fog-, and Mobile Cloud-Computing. Systems adhering to these paradigms exhibit a number of characteristics such as high levels of heterogeneity and dynamicity, leading to high complexity, that exacerbate the problems associated with traditional cyber defence. These problems are further exacerbated when edge-oriented systems operate in adversarial environments, e.g. the Internet of Battle Things (IoBT). Current generations of cyber defence approaches straddling attack prevention, detection, response and tolerance are arguably insufficient for edge-oriented systems operating in IoBT environments, especially given the constant increase in cyber attack sophistication. In this paper, we propose proactive antifragility as a new paradigm for the next generation of cyber defence approaches capable of taking into account the aforementioned system characteristics and environmental challenges. We propose a conceptualization of proactive antifragility, and then outline associated challenges and research directions indicating which existing approaches can be re-used or advanced/developed further in order for proactive antifragility to be achieved "at the edge".

8 citations

Journal ArticleDOI
01 Apr 2021
TL;DR: The research of active defense technology under the background of power information network security is put forward, the defects of firewall technology and intrusion trap technology in passive network security defense technology are expounded, and the pitfalls of activedefense new technology are introduced.
Abstract: With the rapid development of the national power industry, the security of power information network has been widely concerned by the society, and the related impact has also been prominent. At this stage, the development of power information technology is more and more inseparable from the network, so network security has become more and more important, if the network has a serious threat in practical application, the loss caused will be unbearable. In the process of controlling the network security of power information industry, one of the most important and effective methods is active defense. Based on this, this paper puts forward the research of active defense technology under the background of power information network security, expounds the defects of firewall technology and intrusion trap technology in passive network security defense technology, and introduces the pitfalls of active defense new technology In addition, the paper discusses the new active defense technology and its application in power information network security, and puts forward reasonable suggestions. Therefore, the use of information technology to solve the hidden danger of power network security is important.

5 citations