Employing Public Key Infrastructure to Encapsulate Messages During Transport Layer Security Handshake Procedure

Khan, Nayeem Ahmad; Khan, Adnan Shahid; Kar, Hushmat Amin; Ahmad, Zeeshan; Tarmizi, Seleviawati; Julaihi, Azlina Ahmadi

doi:10.1109/aiic54368.2022.9914605

Cited by 4 publications

(7 citation statements)

References 20 publications

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“…This indicates that the approach is able to learn and adapt to new types of malware as it is trained on more diverse datasets. Compared to results obtained in studies (4,5,17) , the proposed approach performed better in terms of accuracy, presession and recall…”

Section: Resultscontrasting

confidence: 56%

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Employing Incremental Learning for the Detection of Multiclass New Malware Variants

Alzahrani

2024

IJST

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Background/Objectives: The study aims to achieve two main objectives. The first is to reliably identify and categorize malware variations to maintain the security of computer systems. Malware poses a continuous threat to digital information and system integrity, hence the need for effective detection tools. The second objective is to propose a new incremental learning method. This method is designed to adapt over time, continually incorporating new data, which is crucial for identifying and managing multiclass malware variants. Methods: This study utilised an incremental learning technique as the basis of the approach, a type of machine learning whereby a system retains previous knowledge and builds upon the information from the newly acquired data. Particularly, this method is suitable for tackling mutating character of malware dangers. The researchers used various sets of actual world malwares for evaluating the applicability of these ideas which serves as an accurate test environment. Findings: The findings of the research are significant. We utilizing 6 different datasets, which included 158,101 benign and malicious instances, the method demonstrated a high attack detection accuracy of 99.34%. Moreover, the study was successful in identifying a new category of malware variants and distinguishing between 15 different attack categories. These results underscore the effectiveness of the proposed incremental learning method in a real-world scenario. Novelty: This research is unique because of the novel use of a tailored incremental learning technique for dealing with dynamic threat environment of malwares. However, with a new threat they cannot be so well adapted using traditional machine learning methods. On the other hand, the technique put forward in this paper facilitates continuous learning that can be modified to match different types of malicious software as they develop. The ability to evolve and adapt is an important addition to current cybersecurity practices that include malware identification and classification. Keywords: Cybersecurity, Malware Detection, Incremental learning

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Section: Resultscontrasting

confidence: 56%

“…Nonetheless, these methods have trouble dealing with malware's ongoing evolution (4) . Existing machine learning algorithms may have difficulty correctly detecting and classifying new malware variants as they are developed and released (5) .…”

Section: Introductionmentioning

confidence: 99%

Employing Incremental Learning for the Detection of Multiclass New Malware Variants

Alzahrani

2024

IJST

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“…In [9], it is expand the areas of smart technologies. Such systems typically use the Secure Sockets Layer (SSL)/Transport Level Security (TLS) (SSL/TLS) protocol stack to provide security services, which allows providing authentication, integrity, and confidentiality services [1][2][3][4][5]. This stack is formed on complex symmetric algorithms that simultaneously provide both encryption and generation of MAC codes [1,[6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…At the transport layer in cyber-physical systems, the TLS protocol provides tunnel mode during the authentication process. In addition, at the transport level, the SL/TLS stack is used in public key infrastructure (PKI) technologies, provides transparent data transfer between end users, and also provides reliable data transfer to higher levels [4,6,[9][10][11]. SSL cryptographic protocols and TLS transport layer security provide data encryption and authentication between various homogeneous and heterogeneous devices such as servers, computers and software applications running across the network.…”

Section: Introductionmentioning

confidence: 99%

Development of an improved SSL/TLS protocol using post-quantum algorithms

Yevseiev,

Havrylova,

Milevskyi

et al. 2023

EEJET

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The development of Internet technologies together with mobile and computer technologies have formed smart technologies that allow the formation of both cyber-physical and socio-cyber-physical systems. The basis of smart technologies is the integration of wireless channel standards with mobile and computer protocols. 4G/5G technologies are integrated with various web platforms, taking into account the digitalization of services in cyberspace. But the SSL/TLS protocol, based on the hybridization of symmetric encryption algorithms with hashing algorithms (AEAD mode), which is supposed to provide security services, is vulnerable to “Meet in the middle”, POODLE, BEAST, CRIME, BREACH attacks. In addition, with the advent of a full-scale quantum computer, symmetric and asymmetric cryptography algorithms that provide security services can also be hacked. To increase the level of security, an improved protocol based on post-quantum algorithms – crypto-code constructions is proposed, which will ensure not only resistance to current attacks, but also stability in the post-quantum period. To ensure the “hybridity” of services, it is proposed to use the McEliece and Niederreiter crypto-code constructions (confidentiality and integrity are ensured) and the improved UMAC algorithm on the McEliece crypto-code construction. Taking into account the level of “secrecy” of information, it is suggested to use various combinations of crypto-code constructions on different algebraic geometric and/or flawed codes. The use of crypto-code constructions not only provides resistance to attacks, but also simplifies the formation of a connection – the parameters of elliptic curves are used to transmit a common key. This approach significantly reduces the connection time of mobile gadgets and simplifies the procedure of agreement before data transfer

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“…Another existing method to avoid malware injection attacks against hypervisors is the advanced cloud protection system (ACPS) (17) . In ACPS the recorder module warns other multiple recorder module about the security risks and saves all the threats and risks in a warning pool.…”

Section: Introductionmentioning

confidence: 99%

Securing Hypervisors in Cloud Computing Environments against Malware Injection

Qurashi

2023

IJST

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Objectives:The primary objectives of this research are to address the security concerns related to cloud computing, emphasising attacks that target different hypervisor layers. The goal is to propose a revolutionary approach called "hGuard," that provides a thorough protection mechanism against malware attacks across several hypervisor levels. Additionally, the research aims to establish this method's ability to improve cybersecurity in cloud systems and show its efficacy through practical studies. Methods: The study combines theoretical analysis with actual experimentation to accomplish its objectives. The "hGuard" approach that is being proposed was developed to defend against attacks on several hypervisor levels. The strategy produces an output that the data mining algorithm, such as Apriori uses to predict potential attacks. Through this association, it is now possible to simultaneously anticipate and stop malware injection attempts at various hypervisor layers. Empirical tests that simulate attacks and examine real-world situations provide quantitative information on the method's performance. Findings: The "hGuard" approach achieves a 95% detection accuracy for identifying malware injection attacks, with a 3% false positive rate for minimal misclassifications of non-attacks. It also demonstrates an 5% false negative rate, reducing errors in categorizing actual attacks. Additionally, the approach boasts an efficient 20 ms execution time, ensuring rapid processing and prediction of potential attacks. Novelty: The novelty of this research lies in the development of the "hGuard" method, which addresses a crucial gap in existing security approaches. Unlike conventional methods that tackle hypervisor levels individually, the proposed approach offers a holistic defense mechanism capable of countering malware attacks targeting multiple levels simultaneously. The integration of the Apriori technique for attack prediction further enhances its novelty by providing a data-driven approach to proactive cybersecurity. The empirical validation of the method's effectiveness contributes to its novelty, showcasing its potential as a valuable tool for detecting and preventing malware attacks in cloud computing. Furthermore, the research suggests avenues for extending the application of the "hGuard" method to other domains within the realm of cybersecurity.

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Employing Public Key Infrastructure to Encapsulate Messages During Transport Layer Security Handshake Procedure

Cited by 4 publications

References 20 publications

Employing Incremental Learning for the Detection of Multiclass New Malware Variants

Employing Incremental Learning for the Detection of Multiclass New Malware Variants

Development of an improved SSL/TLS protocol using post-quantum algorithms

Securing Hypervisors in Cloud Computing Environments against Malware Injection

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