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As consumers, we've grown to enjoy the convenience with online shopping our using our credit cards to make our purchases with numerous retailers. We enjoy the ability to store all of our memories, contacts, messages, and phone backups on iCloud. This has created an unprecedented number of ways bad actors can retrieve your private information, whether it be your credit card information, login credentials to social media or online banking, or even to everything you store on the cloud.
We frequently hear of new breaches occurring on all major news outlets and have almost accepted the fact that our private information can be compromised by numerous organizations without us even knowing. Yet, we still willingly shop online and use our credit cards at the store to make our purchases knowing this information can potentially land into bad actors hands. Telang (2015) describes a framework that will help to allow policymakers to start making organizations more accountable in preventing data breaches.
Through ex-post regulations (such as penalties and liability payments), ex-ante regulations (such as compliance policies), and putting restrictions on information sharing, organizations can take more precautions that consumers sensitive information does not get into the wrong hands of a hacker (Telang, 2015). Cheng, Liu, and Yao (2017) further suggest data leakage detection and prevention technologies, such as intrusion detection systems (IDS), content-based and context-based analysis techniques, can also be deployed to an enterprise system to help further prevent data breaches from within the system itself. As a security professional, our duties are to do our best to stay ahead of the curve to prevent breaches from happening in the first place.
Proactive steps that need further study and focus within the field in the future include a deeper learning for insider threat detection (Cheng, Liu, and Yao, 2017). There is not a great way to detect insider's threats outside of normal security flags and observing the users behavior. As systems migrate to the cloud, better and more improved data leak detection and protection is necessary. Cheng, Liu, and Yao (2017) explain that privacy-preserving data leak detection algorithms are needed to resist strong attacks. Additionally, better training and education solutions are needed to make all users at every level of experience knowledgeable enough to prevent themselves from putting a system at risk.
Sommer & Paxson (2010) explain the lack of training and education is one of the challenges in data leak detection and prevention. As a security professional, I can only hope that the number and severity of data breaches in the future are minimal. However, unless the steps aforementioned are taken, then breaches are going to remain prevalent as more and more systems connect to the internet. Green (2017) discusses that the ever-evolving landscape of online traffic will continue to increase the threat of cyber-attacks and data breaches, and the introduction of "cyber coverage" is imminent to protect people against such attacks.
As security professionals, we must make all contributions to safeguarding systems and promote cybersecurity awareness. We must perform our job functions with the highest integrity and do our due diligence. Proverbs 19:1 (ESV) reads, "Better is a poor person who walks in his integrity than one who is crooked in speech and is a fool." Here we are taught that our wisdom will come shall we walk with integrity and not take shortcuts.
References: Cheng, L., Liu, F., & Yao, D. (. (2017). Enterprise data breach: Causes, challenges, prevention, and future directions. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(5), n/a. doi:10.1002/widm.1211 Green, N. (2017). Standing in the future: The case for a substantial risk theory of "injury in fact" in consumer data breach class actions. Boston College Law Review, 58(1), 287. Sommer, R., & Paxson, V. (2010, May). Outside the closed world: On using machine learning for network intrusion detection. In Security and Privacy (SP), 2010 IEEE Symposium on (pp. 305-316). IEEE. Telang, R. (2015). Policy framework for data breaches. IEEE Security & Privacy, 13(1), 77-79. doi:10.1109/MSP.2015.12