And when we started using gmail, facebook, and google, it seemed like we could upload all kinds of information endlessly, so we could access it at any time, browse it, and so on, which meant that the data in the cloud backend had grown tremendously.
When we return to the basics, we find that 90 percent of all attacks are done over the Internet, and the Internet has become an indispensable medium for attacks. Yes, when an enterprise is attacked by APT, a large amount of information obtained after analyzing the results, the malicious program may use mail, through the network to pass to the internal enterprise, a few days ago, the noisy attack on the network army, and so on, most of them are related to the network attack.
Big Data security challenges are:
1. Complexity of the back-end system
On top of the data, there are often a variety of complex applications to support, and therefore more complex in the security considerations. Users may adopt a single-storage 3-tier architecture, or a more complex Web Service service architecture. Regardless of the architecture, the main goal is to add value to large amounts of data and provide various interfaces or results to the user.
2. Multi-party network access
Despite the complexity of the back-end applications, the simplest way for users to access the services is through the network, which usually contains as many different devices as possible to allow access to the services as opposed to the front-end devices accessing the network. However, for an intruder, this creates a very convenient way to attack, which means that the attacker can also try to attack the whole service through various paths, and then explore the system vulnerability to carry out in-depth attacks.
3. Instant Monitoring and Response
Once big data starts to be provided to various users through services, the system starts to generate various changes, including changes in data and changes in applications. In this case, security scenarios will also follow the changes, such as whether someone is carrying out a dictionary attack on the application, blocking is an attack, and so on. When large amounts of data start to move, and as the amount of usage increases, immediate monitoring becomes more difficult, mainly because it is easier for an attacker to get in between normal users and launch an attack on the system. This can overwhelm system administrators and make it more difficult to detect, let alone respond in a timely manner.
In these circumstances, when we think about security in the context of big data, we can go back to the basics, detecting and strengthening defenses across the system.
It is recommended to consider the security of big data through the following three basic directions:
1. Application security
Data is generally not directly used, but through the application program to display, from the concept of protecting data, the need to strengthen the front-end applications, so companies can be in the application program before the launch of the program, in the middle, after the development of a variety of application program security testing, but also to strengthen the defense measures. Therefore, enterprises can conduct security testing on various developed applications before, during, and after the application is launched, and also can regularly strengthen the testing on relevant web applications that are already online.
Through application security testing, enterprises can provide corresponding basic security testing for applications that use data, and achieve the first step of information security.
2. Network security defense system
The second barrier after the application is in fact the network. Enterprises provide services, relative to the provision of a variety of network access, enterprises can consider by strengthening network security to start, such as in the past, only in the export of the deployment of network security and defense equipment, the idea of expanding to the internal system architecture, that is, in the internal deployment of a new generation of network defense systems, effective defense against a variety of attacks to the network.
3. Intelligent security analysis system
When the big data comes, the enterprise will start to deploy various security measures with the time gradually, intelligent security analysis system can be used as the security brain of the enterprise, through a variety of related analysis, to determine whether it is possible to suffer from the relevant attacks and help enterprises to react in advance. Intelligent security analysis system can make enterprises from the original passive is to detect, improve for active is to dig, and even the use of historical information for threat analysis, so that you can early find a variety of potential security threats.
Big Data security is not a closed problem that can be solved by a single solution, but rather, it is a problem that can be solved by different organizations based on the nature of their data and the context in which it is used. For example, in a variety of hosts, there may still be SSO mechanisms, there may still be host security solutions, anti-virus solutions and so on. Therefore, it is recommended that users start with basic defense, such as basic application security, and basic network security, and then collaborate on various security defense solutions through intelligent security analysis systems.