The Future of Cybercrime Prevention Strategies: Human Factors and A Holistic Approach to Cyber Intelligence

Back, Sinchul; Lee, Jennifer

doi:10.52306/02020119kdhz8339

Cited by 7 publications

(35 citation statements)

References 5 publications

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“…Current cybersecurity strategies, robust in their technical aspects, require combining cybercrime's behavioral dimensions [7][8][9][10]. This gap highlights the limitations of traditional cybersecurity methods, which primarily focus on reactive measures rather than proactive threat prediction and prevention [11][12][13].…”

Section: Problem Overviewmentioning

confidence: 99%

“…The study's approach merges the interdisciplinary CBDFA approach with the introduction of IPM within CFBA. In line with the multidisciplinary nature of cyber behavioral sciences, this approach leverages CBDFA to enhance cybersecurity, particularly in accurately predicting cyber threats from ASNs [9,11]. It represents a significant advancement in CFBA by combining technical analysis with a deep understanding of cybercriminal behavior.…”

Section: Expanding the Cbdfa Approach With Ipmmentioning

confidence: 99%

“…The IPM, incorporating CBS, creates a comprehensive framework for threat prediction, as supported by Connolly et al (2016) [9] and Martineau et al (2023) [2]. This approach signifies a shift in cybersecurity strategies, integrating cyber behavioral science aspects as noted by Ahmad et al (2012) [5] and McAlaney et al (2016) [18], and focuses on refining ASN threat prediction accuracy, as supported by Back and LaPrade (2019) [11] and Pollini et al (2022) [27]. The primary aim of IPM is to improve the precision and accuracy of predictions from ASNs, utilizing ML algorithms and CBDFA [11,27].…”

Section: Expanding the Cbdfa Approach With Ipmmentioning

confidence: 99%

“…This approach signifies a shift in cybersecurity strategies, integrating cyber behavioral science aspects as noted by Ahmad et al (2012) [5] and McAlaney et al (2016) [18], and focuses on refining ASN threat prediction accuracy, as supported by Back and LaPrade (2019) [11] and Pollini et al (2022) [27]. The primary aim of IPM is to improve the precision and accuracy of predictions from ASNs, utilizing ML algorithms and CBDFA [11,27]. This integration of cyberpsychology, digital forensics, and behavioral analysis marks a significant advancement in CFBA [8,12,13,28,30,36], emphasizing the use of diverse expertise to address complex cyber threats.…”

Section: Expanding the Cbdfa Approach With Ipmmentioning

confidence: 99%

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An Interdisciplinary Approach to Enhancing Cyber Threat Prediction Utilizing Forensic Cyberpsychology and Digital Forensics

Rich,

Aiken

2024

Forensic Sciences

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The Cyber Forensics Behavioral Analysis (CFBA) model merges Cyber Behavioral Sciences and Digital Forensics to improve the prediction and effectiveness of cyber threats from Autonomous System Numbers (ASNs). Traditional cybersecurity strategies, focused mainly on technical aspects, must be revised for the complex cyber threat landscape. This research proposes an approach combining technical expertise with cybercriminal behavior insights. The study utilizes a mixed-methods approach and integrates various disciplines, including digital forensics, cybersecurity, computer science, and forensic psychology. Central to the model are four key concepts: forensic cyberpsychology, digital forensics, predictive modeling, and the Cyber Behavioral Analysis Metric (CBAM) and Score (CBS) for evaluating ASNs. The CFBA model addresses initial challenges in traditional cyber defense methods and emphasizes the need for an interdisciplinary, comprehensive approach. This research offers practical tools and frameworks for accurately predicting cyber threats, advocating for ongoing collaboration in the ever-evolving field of cybersecurity.

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Section: Problem Overviewmentioning

confidence: 99%

Section: Expanding the Cbdfa Approach With Ipmmentioning

confidence: 99%

Section: Expanding the Cbdfa Approach With Ipmmentioning

confidence: 99%

Section: Expanding the Cbdfa Approach With Ipmmentioning

confidence: 99%

See 2 more Smart Citations

An Interdisciplinary Approach to Enhancing Cyber Threat Prediction Utilizing Forensic Cyberpsychology and Digital Forensics

Rich,

Aiken

2024

Forensic Sciences

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“…Nguyen (2020) examined what causes cybercrimes originating from Vietnam's social situation and ultimately highlighted the importance of the causes in cyberspaces (Nguyen, 2020). Back and LaPrade (2019) recommended a more holistic approach using technology and a better understanding of the human factors that make cybercrime possible (Back and LaPrade, 2019). Nadir and Bakhshi (2018) reviewed ransomware attacks' history and recent evolution.…”

Section: Existing Cybersecurity Frameworkmentioning

confidence: 99%

Mitigating cybercrimes in an evolving organizational landscape

Yeboah-Ofori

Opoku-Boateng

2023

CRR

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PurposeVarious organizational landscapes have evolved to improve their business processes, increase production speed and reduce the cost of distribution and have integrated their Internet with small and medium scale enterprises (SMEs) and third-party vendors to improve business growth and increase global market share, including changing organizational requirements and business process collaborations. Benefits include a reduction in the cost of production, online services, online payments, product distribution channels and delivery in a supply chain environment. However, the integration has led to an exponential increase in cybercrimes, with adversaries using various attack methods to penetrate and exploit the organizational network. Thus, identifying the attack vectors in the event of cyberattacks is very important in mitigating cybercrimes effectively and has become inevitable. However, the invincibility nature of cybercrimes makes it challenging to detect and predict the threat probabilities and the cascading impact in an evolving organization landscape leading to malware, ransomware, data theft and denial of service attacks, among others. The paper explores the cybercrime threat landscape, considers the impact of the attacks and identifies mitigating circumstances to improve security controls in an evolving organizational landscape.Design/methodology/approachThe approach follows two main cybercrime framework design principles that focus on existing attack detection phases and proposes a cybercrime mitigation framework (CCMF) that uses detect, assess, analyze, evaluate and respond phases and subphases to reduce the attack surface. The methods and implementation processes were derived by identifying an organizational goal, attack vectors, threat landscape, identification of attacks and models and validation of framework standards to improve security. The novelty contribution of this paper is threefold: first, the authors explore the existing threat landscapes, various cybercrimes, models and the methods that adversaries are deploying on organizations. Second, the authors propose a threat model required for mitigating the risk factors. Finally, the authors recommend control mechanisms in line with security standards to improve security.FindingsThe results show that cybercrimes can be mitigated using a CCMF to detect, assess, analyze, evaluate and respond to cybercrimes to improve security in an evolving organizational threat landscape.Research limitations/implicationsThe paper does not consider the organizational size between large organizations and SMEs. The challenges facing the evolving organizational threat landscape include vulnerabilities brought about by the integrations of various network nodes. Factor influencing these vulnerabilities includes inadequate threat intelligence gathering, a lack of third-party auditing and inadequate control mechanisms leading to various manipulations, exploitations, exfiltration and obfuscations.Practical implicationsAttack methods are applied to a case study for the implementation to evaluate the model based on the design principles. Inadequate cyber threat intelligence (CTI) gathering, inadequate attack modeling and security misconfigurations are some of the key factors leading to practical implications in mitigating cybercrimes.Social implicationsThere are no social implications; however, cybercrimes have severe consequences for organizations and third-party vendors that integrate their network systems, leading to legal and reputational damage.Originality/valueThe paper’s originality considers mitigating cybercrimes in an evolving organization landscape that requires strategic, tactical and operational management imperative using the proposed framework phases, including detect, assess, analyze, evaluate and respond phases and subphases to reduce the attack surface, which is currently inadequate.

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An anti‐phishing enterprise environ model using feed‐forward backpropagation and Levenberg‐Marquardt method

Sankhwar

Pandey

Khan

et al. 2020

Security and Privacy

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Phishing in an enterprise is serious issue rising in wide scale and complexity, as phishers use email phishing via obfuscated, malicious or phished URLs and continuously adapt or innovate their strategies to lure victims for identity theft for financial benefits. To gain victim's trust and confidence phishers have started using visceral factors and familiarity cues. Phishing is not always money centric; phisher defame the user's goodwill and character. Defamation in enterprise could be much more traumatic than being embarrassed at a social networking site. It is a challenging task to address this issue. It is evident through literature review that single phishing detection filter approaches are insufficient to detect phishing in enterprise environ. Therefore, a novel anti-phishing model for enterprise using artificial neural network is proposed. In addition, this model effectively identifies whether the phishing email is known phishing or unknown phishing to reduce the trust and familiarity-based email phishing enterprise environ. The feed-forward backpropagation and Levenberg-Marquart methods of ANN are adopted to enhance the URL classification process and with Fuzzy Inference System to get result with imprecise data of social features. The proposed model can accurately classify the known and unknown email phishing via URLs. K E Y W O R D S authentication, E-mail phishing, enterprise cyber threat, machine learning techniques, privacy models for communication systems communication security, security and privacy in mobile communication services, social engineering 1 INTRODUCTION In digital era, email phishing is a critical issue causing loss of finance during online transactions. At present, different anti-phishing approaches are being proposed to detect email phishing attacks. Despite the various developed anti-phishing approaches are profoundly incompetent to tackle the real-time hassles. In literature review, a group of researchers argued upon about URLs blacklisting, which are mostly used in industry or organizations but not well off to

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The Future of Cybercrime Prevention Strategies: Human Factors and A Holistic Approach to Cyber Intelligence

Cited by 7 publications

References 5 publications

An Interdisciplinary Approach to Enhancing Cyber Threat Prediction Utilizing Forensic Cyberpsychology and Digital Forensics

An Interdisciplinary Approach to Enhancing Cyber Threat Prediction Utilizing Forensic Cyberpsychology and Digital Forensics

Mitigating cybercrimes in an evolving organizational landscape

An anti‐phishing enterprise environ model using feed‐forward backpropagation and Levenberg‐Marquardt method

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