The Meaning of Data Leakage Data leakage is the accidental distribution of sensitive or private data to an unauthorized entity (Wu et al. Russell Wilson Seahawks Jersey , 2011). The sensitive data represents intellectual property, patient information, personal credit data, financial information and any other information that needs to be secured from third parties. Data Leakage poses a critical issue for organizations because the number of incidents and their associated costs continues to increase. How Does Data Leakage Occur in an Organization? Data leakage results from the fact that transmitted data such as emails, file transfers Russell Wilson Kids Jersey , instant messaging and website forms among others are largely unmonitored and unregulated during their transit to the destinations (Papadimitriou & Garcia-Molina, 2011). Also, sensitive data is being shared among several stakeholders like the employees that are working from outside an organization鈥檚 premises, business partners, and clients. Those various users do use various devices like mobile phones Russell Wilson Youth Jersey , PCs, and laptops that may not be having data antimalware protections and other security enhancements. That increases the risk of the sensitive information, hence making it vulnerable to fall into unauthorized hands. Regardless of whether the information leakage is caused by an inadvertent mistake by insiders, malicious Internet or intruders, the exposure of this confidential information can hurt a company (Wu et al. Russell Wilson Womens Jersey , 2011). The Common Causes of the Problem There are many causes of data leakage in any place. A data breach investigation report of 2009 whereby 90 data breaches of that year were analyzed. The report showed a significant number of records that were compromised (285 million), and it also showed other interesting aspects of the issue. The report showed that the common cause of data leakage is ten external parties that accounted for 74 percent. It also showed that the insiders also accounted for 20 percent of data leakage problems in organizations. The common causes of data leakage by insiders are risky behaviors. They included unauthorized application usage on the business networks, misuse of corporate computers, using unsafe devices to access remotely the corporate network, misuse of passwords as well as the logout and login procedures (Shabtai Authentic Russell Wilson Jersey , Elovici & Rokach, 2012). The most common outsider cause is hacking and malware. How to Address the Trend There should be the usage of various methods to address the leakage data trends in organizations. The common mechanisms that should not be lacking in organizations are firewalls, intrusion prevention systems, and antivirus software (Wu et al., 2011). The firewall can be used for preventing outside attacks while the intrusion prevention system is used for detecting and preventing both inside activities and outside incidents. There should also be policies as well as the training ion organizations for the employees and business partners on how to use and secure data. There should be the creation of organization-wide data security policies to regulate the aspects of handling sensitive data (Papadimitriou & Garcia-Molina Russell Wilson Jersey , 2011). Another reliable mechanism for preventing data leakage is the use of intelligent or advanced security measures such as temporal reasoning algorithms and machine learning to detect abnormal access to organizational data. Conclusion Data leakage is becoming a nuisance in many organizations because of the increasing incidents that can result in the challenge. Thus, companies need to make sure that all the stakeholders understand about the challenge since it is a business wide challenge. The reason for that is to help the people understand that the corporate security is critical, and they also need to understand the procedures as well as the policies that are helpful in achieving a secure environment. There should be the usage of technologies that can detect and prevent the data leakage problems. 鈥?br > References Papadimitriou, P., & Garcia-Molina, H. (2011). Data leakage detection. Knowledge and Data Engineering, IEEE Transactions on, 23(1), 51-63. Shabtai, A.#7# Elovici, Y., & Rokach, L. (2012). A survey of data leakage detection and prevention solutions. Springer Science & Business Media. Wu, J.#8# Zhou, J., Ma, J., Mei#9# S., & Ren, J. (2011). An active data leakage prevention model for insider threat. In Intelligence Information Processing and Trusted Computing (IPTC), 2011 2nd International Symposium on (pp. 39-42). IEEE.
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