There exist different pillars that define security management goals which include confidentiality, integrity, and availability. The main section of concern in this study is Integrity where its purpose is to guarantee consistency and accuracy of data. Thus the function of integrity is to ensure accurate and reliable data by preventing unauthorized hackers accessing the system containing sensitive data (Zhuang et al. 2017). Also, integrity ensures transmission of data arrives at the destination same as it originates from the sender without any changes. Security is a major issue among small and medium-sized organizations as they fail to invest in security measures thus creating a vulnerability of attack by unanimous persons or hackers. Thus, the hacker may gain access to the organization system, and the system administrator fails to notice the attack if the hacker manages to cover the tracks well. In such situation, the integrity ensures there is no manipulation of data either intentionally or accidentally thereby retaining purity and trustworthy of data.
Implementation of integrity model helps in achieving three different types of goals. First, the unauthorized person will not manage to modify any data or programs installed in the organization (Zhuang et al. 2017). Second, there will be no improper or unauthorized changes done by an unauthorized hacker. Third, integrity guarantees internal and external data or programs consistency.
Factors Undermining Integrity and their Solution
The first thing to consider while achieving integrity is data completeness. Data completeness refers to a situation of evaluating gaps in data by examining the actual data and the expected data to be collected. Solving the issue with incomplete data can only occur by preventing submission of data which is not complete until the expected data is available (Singh et al. 2016). The paper format will comprise the integrity of data due to human errors. Paperless data collection will require assigning of mandatory fields while collecting the data. Hence achieving data completeness will be easier and time-saving as there will be no need to revisit to check mistakes resulting to incomplete data. Another factor undermining integrity is data consistency. By consistency means there is a match in different data types with the expected data types flowing in the system. Achieving data consistency will require designing the system with menus where the user can easily select without entering the data in an empty text box. Thus there will be consistency in all data which simplifies other activities within the system such as searching for results.
Another factor undermining integrity is data accuracy which ensures the data collected is correct and it represents what it should accurately. Solving issues with data accuracy follow a different strategy as it often depends on the knowledge and training of the user interacting with the system (Singh et al. 2016). However, overcoming human errors requires implementation of extra measures to all employees despite the position of the employee. Also, another strategy may include the use of additional steps such as collection of GPS location and capturing of the picture which will help in reducing inaccurate data. Data validity is another factor which affects the integrity of data. The issue with validity usually arises with paper forms as once data is collected it becomes hard to change such data. Solving issue with data validity requires the use of paperless data collection method like the use of Smartphone where changes to data can occur easily (Singh et al. 2016). Lastly, there is data timeliness which refers to the expected time for the data to be effective for use. Solving such issue will require integration of timely analytics or implement real-time data collection method. Therefore, achieving integrity through considering the above factors will help in achieving a high quality of data.
Zhuang, C., Chengyin, Y., & Feng, Q. (2017). Scheme of Encrypted Cloud Data Transmission and Achieve the Data Integrity Valid.
Singh, S., Jeong, Y. S., & Park, J. H. (2016). A survey on cloud computing security: Issues, threats, and solutions. Journal of Network and Computer Applications, 75, 200-222.