With the cloud changing the way modernizations of big data is done, service providers and security organizations have to work harder to ensure security of Big Data to their consumers. The reason for increased security breaches is because the traditional security technologies have no capacity required to detect and protect against such attacks. In view of this rising issue, let's look at what companies in Silicon Valley are doing to make big data more secure.
IBM and security of Big Data
IBM has launched a security intelligence with Big Data platform to ensure threats and risk are detected. IBM's platform can help business address the ATPs, fraud and insider threats. IBM is helping its clients to answer questions that could never have been answered before. For instance, the new security intelligence with Big Data platform helps clients analyze emails, transactions, social media data, documents and full packet data over years of activity. With these kind of analytic capabilities, organizations can find malicious activities hidden in the big masses of data.
HP's Big Data Security strategy
HP makes use of Knowledge management apps and Autonomy enterprise search and integrate them with Security-event and information management (SIEM) to analyze the massive data. According to Varun Kohli, the director of product market and enterprise security products, it is possible to reveal rogue employee's behavior related to the data leaks of information, and learn in advance plots against the organization by cyber criminals. HP believes autonomy gives meaning to the data to ensure analyst are able to find out what people are saying, both negative and positive.
The Blue Coat (bluecoat.com) security platform is uniquely positioned to ensure secure data for its clients on five advanced solutions areas. They include Advanced Threat Protection, Advanced web and cloud security, Encrypted Traffic management, Incidence Response & Network Forensics and Network Performance & Optimization. The platform aims to deliver cohesive visibility, protection and integration including:
- Providing a management environment to ensure operational teams can manage, enforce policies using a single platform whether in the cloud, on premise or across the platform. The plat
- Intelligence – protection of data is real-time, an effort that requires integrated intelligence to ensure an organization is able to adapt to rapid advancing threats.
Microsoft Big Data Security
To help all its clients move to the cloud and feel more secure, Microsoft launched its new security features of its well-known Azure SQL Database. New security steps include:
- Encryption – referred as "always encrypted", it helps businesses protect sensitive data without "having to relinquish the encryption keys to Azure SQL Database". This means that data remains encrypted on disks, in memory, on transit and during processing.
- Transparent data encryption – helps business comply with requirements using associated backups, encrypting the databases, transaction log files without making changes in the applications.
- Azure SQL database – to support authentication.
- Threat detection – alerts the users on suspicious database activities on logical server or the database itself.
The reasons why companies may not have their Big Data secure is because:
- They fail to view data security in all dimensions.
- Failure to have a cutting-edge comprehensive information security plan.
- Failure for many businesses to see data security as a business problem but instead as an "IT Problem".
- Failure to classify data and trade secrets.
The importance of securing Big Data for the business includes:
- Ensure accuracy – when data in the cloud is secure, every employee has confidence in the values and information.
- Security of confidential information – an organization has to ensure trade secrets and employee personal information are protected among other information to ensure the business does not run in to a crisis.
- Availability – when data is secure, it is accessible as long as internet connection is available. Security of Big Data means information can be accessed at any time regardless of location.
- Prevent opportunistic hacking – when Big Data is not secure, hackers may try to breach the low security level with the aim of destruction and stealing confidential information.
Originally posted on Data Science Central