Cyberstalking: Investigating formal intervention and the role of Corporate Social Responsibility

Al-Khateeb, Haider; Epiphaniou, Gregory; Alhaboby, Zhraa A.; Barnes, Jim; Short, Emma

doi:10.1016/j.tele.2016.08.016

Cited by 26 publications

(13 citation statements)

References 26 publications

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“…“Cyber-victimization” is an umbrella term which includes cyberstalking (Dreßing, Bailer, Anders, Wagner, & Gallas, 2014), cyberharassment (Fridh et al, 2015), cyberbullying (Zych, Ortega-Ruiz, & Del Rey, 2015), and other cyber-offences (Mishna, McLuckie, & Saini, 2009). All of these offences cause a considerable impact and leave the victims struggling for support (al-Khateeb, Epiphaniou, Alhaboby, Barnes, & Short, 2017). Cyberharassment is the intimidation of the target using electronic means of communication, while cyberstalking is characterized by fixation, being repetitive, unwanted contact using electronic means that results in fear and distress (Dreßing et al, 2014; Reyns, Henson, & Fisher, 2012).…”

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confidence: 99%

Cyber-Victimization of People With Chronic Conditions and Disabilities: A Systematic Review of Scope and Impact

Alhaboby

Barnes

Evans

et al. 2017

Trauma, Violence, & Abuse

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The victimization of individuals with chronic conditions or disabilities is prevalent with severe impact at psychological and physiological levels. With the increasing use of technology these experiences were further reshaped. This systematic review aimed at scoping the experiences of cyber-victimization of people living with chronic conditions or disabilities and examine the documented impact on them. Following a four-stage search strategy in several databases including MEDLINE, Embase, PsychINFO, CINAHL, Cochrane and snowballing of references, a total of 2,922 studies were scanned and 10 studies were eventually included. Quality assessment was done in two phases using tools specific to observational studies and cyber-victimization research. A narrative synthesis of reported results covered a total of 3,070 people. Sample size ranged between 42 and 823 participants, and the age range was 6-71 years with a majority of White ethnic backgrounds. Most studies (n=9) were cross sectional. The prevalence range of cyber-victimization was 2%-41.7% based on variable definitions, duration and methods. Targeted conditions included physical impairments, intellectual disabilities and specific chronic diseases. The most common documented impact was psychological/psychiatric, mainly depression followed by anxiety and distress. Somatic health complaints and self-harm were also reported. We concluded that people with chronic conditions and disabilities were consistently at higher risk of victimization with devastating health complications. Research gaps were identified such as the need to address more conditions and acknowledge differences between heterogeneous health conditions. Other recommendations include allowing flexibility and accountability to patients/victims in research design, education on victimization and health consequences, and improving primary care.

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confidence: 99%

Cyber-Victimization of People With Chronic Conditions and Disabilities: A Systematic Review of Scope and Impact

Alhaboby

Barnes

Evans

et al. 2017

Trauma, Violence, & Abuse

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“…This approach is suitable as a stand-alone method or triangulated with other qualitative methods to increase confidence in recommendations [29]. The analysis in this paper was underlined by phenomenological philosophy, which looks at official reports as social constructs [33] and it is in-line with previous work carried by the authors in this area [19,27,34]. Hence, thematic analysis was employed in the last stage.…”

Section: Methodsmentioning

confidence: 95%

“…The Police are one of the major instrumental support channels approached by victims of cyber-offences [27]. The "online flag" in police records became mandatory in April 2015 [10].…”

Section: Introductionmentioning

confidence: 99%

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Cyber-Disability Hate Cases in the UK: The Documentation by the Police and Potential Barriers to Reporting

Alhaboby

Al-Khateeb

Barnes³

et al. 2021

Cybersecurity, Privacy and Freedom Protection in the Connected World

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Disability hate crime is under-reported in the UK with perceived limited support given to the victims. The use of online communication resulted in cyber-disability hate cases, recognised by the Police with the addition of an 'online-flag' in the documentation. However, the cases remain under-reported, with potential individual, societal and organisational barriers to reporting especially during a pandemic. This paper aims to contextualise the reporting of cyberdisability hate cases, identify potential barriers, and provide recommendations to improve support to victims by the Police. The retrospective examination was carried out on disability-related cyber incidents documented by a police force in the UK for 19 months. Among 3,349 cyber-crimes, 23 cases were included. The analysis covered descriptive statistics and qualitative document analysis (QDA). Only 0.7% of cyber incidents or 6.7% of cyber-hate incidents were disability related. The age of victims ranged between 15 and 61 years, with a mean of 25.8 years. Most of the victims (78%) were from White ethnic background, and the majority were females (61.5%). Three overarching themes emerged from the qualitative data as influencers of reporting or documentation, these were: psychological impact, fear for safety, and the type of disability. Cyber-offences resulted in a serious impact on wellbeing, however, cases that included people with visible disabilities were more documented. Further awareness-raising targeting the police and public is needed to understand the impact of cyber-offences and recognise the different types of disabilities, which might encourage both reporting and documentation.

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“…The annual cost of cyber attacks was $3 trillion in 2015 and it is expected to increase to more than $6 trillion per annum by 5 2021 [4]. This high cost has brought much interest in research and investment towards developing new cyber attacks defence methods and techniques [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Detection of advanced persistent threat using machine-learning correlation analysis

Ghafir

Hammoudeh

Přenosil

et al. 2018

Future Generation Computer Systems

231

107

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Item Type Article Authors Ghafir, Ibrahim; Hammoudeh, M.; Prenosil, V.; Han, L.; Hegarty, R.; Rabie, K.; Aparicio-Navarro, F.J. Citation Ghafir I, Hammoudeh M, Prenosil V (et al) Detection of advanced persistent threat using machine-learning correlation analysis. Future Generation Computer Systems. 89: 349-359. Rights Citation: Ghafir I, Hammoudeh M, Prenosil V (et al) Detection of advanced persistent threat using machine-learning correlation analysis. Future Generation Computer Systems. 89: 349-359. AbstractAs one of the most serious types of cyber attack, Advanced Persistent Threats (APT) have caused major concerns on a global scale. APT refers to a persistent, multi-stage attack with the intention to compromise the system and gain information from the targeted system, which has the potential to cause significant damage and substantial financial loss. The accurate detection and prediction of APT is an ongoing challenge. This work proposes a novel machine learning-based system entitled MLAPT, which can accurately and rapidly detect and predict APT attacks in a systematic way. The MLAPT runs through three main phases: (1) Threat detection, in which eight methods have been developed to detect different techniques used during the various APT steps. The implementation and validation of these methods with real traffic is a significant contribution to the current body of research; (2) Alert correlation, in which a correlation framework is designed to link the outputs of the detection methods, aims to identify alerts that could be related and belong to a single APT scenario; and (3) Attack prediction, in which a machine learning-based prediction module is proposed based on the correlation framework output, to be used by the network security team to determine the probability of the early alerts to develop a complete APT attack. MLAPT is experimentally evaluated and the presented system is able to predict APT in its early steps with a prediction accuracy of 84.8%.to a technical report by Trend Micro [11], this assumption is no longer valid with the rise of targeted attacks, Advanced Persistent Threats (APTs), in which both cyber-criminals and hackers are targeting selected organizations and persisting until they achieve their goals.The APT attack is a persistent, targeted attack on a specific organisation 20 and is performed through several steps [12]. The main aim of APT is espionage and then data exfiltration. Therefore, APT is considered as a new and more complex version of multi-step attack. These APTs present a challenge for current detection methods as they use advanced techniques and make use of unknown vulnerabilities. Moreover, the economic damage due to a successful 25 APT attack significant. The potential cost of attacks is the major motivation for the investments in intrusion detection and prevention systems [13]. APTs are currently one of the most serious threats to companies and governments [14].Most of the research in the area of APT detection, has focused on analysing already identified APTs [15][16][17][...

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Cyberstalking: Investigating formal intervention and the role of Corporate Social Responsibility

Cited by 26 publications

References 26 publications

Cyber-Victimization of People With Chronic Conditions and Disabilities: A Systematic Review of Scope and Impact

Cyber-Victimization of People With Chronic Conditions and Disabilities: A Systematic Review of Scope and Impact

Cyber-Disability Hate Cases in the UK: The Documentation by the Police and Potential Barriers to Reporting

Detection of advanced persistent threat using machine-learning correlation analysis

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