Advancing a Machine Learning Mitigation Approach - Computer Science Assignment Help

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Assignment Task

 

AIM

Seven years ago, the federal government of Nigeria introduced a cashless policy, the aim was to reduce the amount of physical cash in the economy and encourage electronic transactions. Central Bank of Nigeria (CBN) reported that N15.5 billion ($333 million) was lost to bank fraud in 2019 of which 60% of it was due to social engineering (CBN, 2020). This policy is being threatened by the growing perpetration of social engineering attacks. This paper will investigate these attacks and produce an algorithm which will help in an effective detection of attacks which could jeopardise the social engineering confidentiality, this will create a safer and more reliable computing environment in Nigeria and around the world.

 

PROBLEM STATEMENT

The act of tricking employees and consumers into disclosing their credentials which they will now use to access their accounts or networks is known as social engineering. This can also be classified as human hacking. (Conteh et al, 2019)

Providing protection and countering cyberattacks whilst keeping up-to-date with growing challenges is one of the major problems face by today businesses.

The importance of cyber security differs according to business needs, budget, business prerequisites, market pressures and investment into emerging markets. Despite the fact that financial institutions have invested billions of dollars to counter cyber-attacks, cybercriminals have made and are continuously making various efforts to find advanced methods for hacking the banking system in a dynamic way. ( Mangala, 2018)

One of the attacks that plague financial institutions is social engineering attack, the management of banking institutions are really worried about social engineering, since most of their customers have been the victims of this kind of attack (Di Pinto, 2019)

 

SCOPE OF THE RESEARCH

  • The research question will be used to unearth social engineering attack on banks’ customers, its prevention and detection
  • Secondary data will be collected from a UCI Repository
  • The study will show detail evaluation of social engineering attack detection and prevention which will enable me to provide appropriate answers to the research question
  • English language simulations will be developed and used as a training tool

 

OBJECTIVES

  • To assess underlying concept of social engineering attack and their influence on bank account holders in Nigeria
  • To identify attack stages and provide Machine Learning algorithms that can be used to intercept emails related to social engineering attacks.
  • To propose a model that will aid users and financial institutions in Nigeria to re-think their anti-social engineering strategies

 

 

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