How to build a vulnerability benchmark to overcome cyber security attacks

Akram, Junaid; Luo, Ping

doi:10.1049/iet-ifs.2018.5647

Cited by 15 publications

(9 citation statements)

References 42 publications

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“…While there are several ways that bad actors obtain this information, prevention strategies all revolve around target hardening. This involves technology measures such as ensuring security systems have the latest patches for vulnerabilities, and staff and customer accounts use adequate security such as multifactor authentication (MFA) and strong password guidelines (Akram and Ping 2019;Lord 2020). It is also important to incorporate staff training in recognising phishing attempts and suspicious emails, awareness of social engineering techniques, and what processes should be followed in these situations (Jampen et al 2020;Lord 2020).…”

Section: Points Of Disruption/preventionmentioning

confidence: 99%

Card-not-present fraud: using crime scripts to inform crime prevention initiatives

Bodker

Connolly²,

Sing³

et al. 2022

Secur J

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Growth in the online retail sector and improvements in card-present authorisation measures have led to substantial increases in card-not-present (CNP) fraud, particularly in the online retail sector. This article uses crime script analysis to understand the commission process of CNP fraud in online retail settings. Drawing upon previous crime script articles and industry reports we outline the steps involved in the three stages of CNP fraud: preparation; doing it; and getting away. From this script, points of disruption are identified and we discuss prevention measures that stakeholders such as businesses and financial institutions could implement to reduce bad actors opportunities for CNP fraud.

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Section: Points Of Disruption/preventionmentioning

confidence: 99%

Card-not-present fraud: using crime scripts to inform crime prevention initiatives

Bodker

Connolly²,

Sing³

et al. 2022

Secur J

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“…Do not open a file from an unknown sender and do not use the same password everywhere and do not keep a copy of plain text login [6]. Try not login into your accounts on a public network and always Enable Multi-Factor Authentication and do not give personal information by phone or email and do not visit a fishy website.…”

Section: Cyber Crime Preventionsmentioning

confidence: 99%

Cyber Security Methodologies and Attack Management

Tomar¹,

Singh²

2021

J. Manage. Serv. Sci.

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Cyber Security refers to the processes of protecting data and systems from cyber-attacks. Any firm without security policies and systematic security systems is at large risk and the important data related to that firm are not safe without security policies like. Payment Card Industry and Data Security Standard framework used to protect payment security credit card, debit card, etc. In maintaining access, the hacker inside the target system is used to exploit vulnerabilities and password cracking. In today’s era, day by day cybercrimes rise so it raised the requirement of system Security or even the entire network. As more business exercises are being mechanized and an expanding number of PCs are being utilized to store important data, the requirement for secure PC frameworks turns out to be more evident. As a result, network safety issues have become public safety issues.

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“…It is a very adaptive process in software development activities. Recently, many clone detection approaches have been developed, which detect code clones in different software systems. However, during the detection of clones, it is difficult to say which code fragment is original and which code fragment is copied.…”

Section: Introductionmentioning

confidence: 99%

IBFET: Index‐based features extraction technique for scalable code clone detection at file level granularity

2019

Self Cite

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Many techniques have been developed over the years to detect code clones in different software systems to maintain security measures. These techniques often require the source code to compare the subject system against a very large data set of big code. This paper presents index-based features extraction technique (IBFET) to detect code clones at a very large-scale level to billions of LOC at file level granularity. We performed preprocessing, indexing, and clone detection for more than 324 billion of LOC using a Hadoop distributed environment, which is quite faster and more efficient as compared to existing distributed indexing and clone detection techniques; meanwhile, it detects all three types of clones efficiently. The MapReduce rule of divide and conquer is used for a count and retrieve the similar features between different systems. We evaluated the execution time, scalability, precision, and recall of IBFET by using a well-known clone detection data set IJaDataset and BigCloneBench; furthermore, we compared the results with other state-of-the-art tools. Our approach is faster, flexible, scalable, and provides accurate results with high authenticity and can be implemented at a large-scale level. KEYWORDSbig code, clone detection, code similarity detection, plagiarism detection, software reuse, software security and maintenance 22

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How to build a vulnerability benchmark to overcome cyber security attacks

Cited by 15 publications

References 42 publications

Card-not-present fraud: using crime scripts to inform crime prevention initiatives

Card-not-present fraud: using crime scripts to inform crime prevention initiatives

Cyber Security Methodologies and Attack Management

IBFET: Index‐based features extraction technique for scalable code clone detection at file level granularity

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