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Detection and Minimization of Malware by Implementing AI in SMEs

Nisha Rawindaran, Liqaa Niwaf*, Vibhushinie Bentotahewa, Edmond Prakash, Ambikesh Jayal, Chaminda Hewage, Daniyal Alghazzawi

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddPennodadolygiad gan gymheiriaid

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The malware can threaten personal privacy by opening backdoors for attackers to access user passwords, IP addresses, banking information, and other personal data, whilst some malware extracts personal data and sends them to people unknown to the users. In this chapter, the authors will present recent case studies and discuss the privacy and security threats associated with different types of malwares. The small medium enterprises (SMEs) have a unique working model forming the backbone of the UK economy and malware affects SMEs’ organizations. Also, the use of Artificial Intelligence (AI) as both an offense and defense mechanism, for the hacker, and the end user will be investigated further. In conclusion, finding a balance between IT expertise and the costs of products that are able to help SMEs protect and secure their data will benefit the SMEs by using a more intelligent controlled environment with applied machine learning techniques and not compromising on costs will be discussed.

Iaith wreiddiolSaesneg
TeitlMalware - Detection and Defense
GolygyddionEduard Babulak
Man cyhoeddiLondon, United Kingdom
CyhoeddwrInTech
Pennod3
ISBN (Electronig)978-1-83768-446-5
ISBN (Argraffiad)978-1-83768-445-8 , 978-1-83768-444-1
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 2022
Cyhoeddwyd yn allanolIe

NDC y CU

Mae’r allbwn hwn yn cyfrannu at y Nod(au) Datblygu Cynaliadwy canlynol

  1. NDC 8 - Gwaith Teilwng a Thwf Economaidd
    NDC 8 Gwaith Teilwng a Thwf Economaidd
  2. NDC 9 - Diwydiant, Arloesi a Seilwaith
    NDC 9 Diwydiant, Arloesi a Seilwaith

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