Why Enterprise Application Security is Getting More Attention Than Ever?
Cyber assaults are a common occurrence, regardless of the size of the firm. As a result of the advent of digital transformation and the Internet of Things, discussions on Enterprise Application Security have grown increasingly significant, as the risks become more serious, sophisticated, and difficult to defend against. Despite the fact that technology firms have been working tirelessly to strengthen cybersecurity systems, the truth remains that they have not been entirely effective in their efforts. As a result, businesses that rely on online and mobile apps to execute internal and external operations, as well as those that store their data in the cloud or in a conventional data centre, are putting themselves at great danger.
It is not the case that the susceptible state of corporate applications and cyber security was previously unknown. The web development firms as well as the businesses themselves have lately begun to pay more attention to this issue, which is encouraging. This is due to the rising rate of big data analytics services technology adoption among businesses, as well as the entry of new technologies such as the Internet of Things (IoT) into the market.
Getting Started with Application Security 101
When you think about software security breaches, it’s easy to envisage shadowy hackers hammering away on a keyboard in a dark room, attempting to break your security safeguards in order to get access to your system and steal data. According to a security breach survey, while it is true that 50 per cent of security breaches are classified as malicious (malware infections, criminal insiders, phishing or social engineering, and SQL injections), the other 50 per cent are caused by software “glitches” and human error.
Large corporations, including Microsoft, Facebook, and Intel, have bug bounty programmes in place to assist them in discovering and resolving issues in their software before their consumers become aware of them. It is possible for white hat hackers to make millions of dollars by discovering and exposing security flaws in software. In addition to bug bounty programmes, there are cybersecurity organisations that provide bug rewards in exchange for vulnerabilities that they may utilise for more sinister reasons.
What role does Big Data analytics play in the fight against cyber threats?
To identify security events, traditional security technology relied on two basic analytical techniques: heuristics and classification.
- Correlation rules are manually defined rules that specify a sequence of events that indicates an anomaly, which could indicate a security threat, vulnerability, or active security incident. Correlation rules are used to identify anomalies in data that could indicate a security threat, vulnerability, or active security incident.
- Vulnerabilities and risk assessment in networks scanning networks for known attack patterns and known vulnerabilities, such as open ports and unsecured protocols are two important aspects of network security.
- The one thing that all of these earlier strategies have in common is that they are effective in detecting known bad conduct. They do, however, suffer from two significant drawbacks:
- As a result of the rigorous, established criteria and signatures that are used, there is a high rate of false positives, which results in increased alert fatigue.
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How Do You Put Big Data Security Into Practice?
It is possible for enterprises to apply security measures to secure their big data analytics tools in a number of different ways. One of the most often used security technologies is encryption, which is a very basic technology that may be quite effective. External factors, such as hackers, will be unable to access encrypted data if they do not have the key to decrypt the data. Furthermore, encrypting data ensures that information is totally safeguarded at both the input and output points.
Another important element for large data security is the establishment of a robust firewall. Firewalls are excellent at filtering traffic that enters and exits servers, and they are becoming more popular. The creation of powerful filters that block out any third parties or unknown data sources may help organisations avert attacks before they occur.
Finally, managing who gets root access to your business intelligence (BI) tools and analytics platforms is another important step in data security. By implementing a tiered access strategy, you may limit the likelihood of an attack occurring on your network.
There are a number of difficulties with safeguarding large amounts of data. In order to avoid taking anything for granted while hosting your Big Data platform in the cloud, strive not to do so. Working closely with the big data analytics services provider is essential to overcoming these obstacles while maintaining high levels of security.
In addition, it provides an overview of the many possibilities, rewards, and problems associated with big data security analytics programmes across several industries. In addition, it provides an overview of the various technologies now in use to solve these issues.