Preventive Policy Enforcement with Minimum User Intervention Against SMS Malware in Android Devices

Derhab, Abdelouahid; Saleem, Kashif; Youssef, Ahmed E.; Gabsi, Mohamed

doi:10.1007/s13369-015-1665-2

Cited by 2 publications

(2 citation statements)

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“…According to the authors, most anti-virus applications couldn't recognize the malware, even when deployed with other spells. This indicates that anti-malware systems need to be up to date to stumble on better this new kind of malware (Derhab et al, 2016a). The look at "Performance Evaluation of CNN and Pre-educated Models for Malware Classification" assesses how well convolutional neural networks (CNNs) and pre-skilled models carry out in classifying malware.…”

Section: Discussionmentioning

confidence: 99%

“…The counseled approach has yet to be made into a commercial product and is best examined on a dataset of Android packages. The examine notably contributes to malware detection normal (Derhab et al, 2016b). Vinod et al Advise an empirical assessment of a machine name-based totally Android malware detector, which uses a dataset of malicious and benign Android packages to extract gadget calls and use a gadget learning classifier to become aware of malicious programs.…”

Section: Discussionmentioning

confidence: 99%

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Unmasking the Threat: Exploring Effective Techniques for Investigating ATM Malware Through Digital Forensic Analyses

Kiranbhai R Dodiya

2024

IJRITCC

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Hackers have developed new techniques to directly breach a system or device, responding to the surge in numerous cybercrimes. Criminals frequently attack automated teller machines (ATMs) because of the vulnerabilities they present. ATM security must monitor and investigate these attacks because ATMs may contain and manage enormous sums of cash, making them good targets for hackers. Because of this, ATM security needs to monitor and investigate these assaults. Because automated teller machines may hold and handle significant quantities of money, the security at ATMs needs to monitor and analyze assaults of this kind. In the present study, using Studio to analyze ATM malware is essential to identifying malware signatures and behaviours that can improve ATM security. Banks and ATM manufacturers must implement specific measures to prevent ATM malware attacks. Based on present research on ATM malware analysis, researchers have uncovered critical insights that are highly beneficial for those seeking to investigate Malware aimed at breaching automated teller machines (ATMs). It is an invaluable tool for conducting such investigations. This paper will serve as a means of sharing insightful findings and aiding others in deepening their understanding of this crucial topic.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%