Tag Archives: Security Systems

Competitive Technology, Security Systems

Upgrading Organizations’ Security System through Neural Networks

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For the past decades, there are a number of researches on how to enhance the current technology and methods to defend systems from intrusions. Today, businesses and other organizations utilize ‘anomaly detection’ and misuse or ‘signature-based detection’ to find malicious network activities and identify if these are known or new security threats. Unfortunately, these methods are still subject to progress.

When it comes to cyber security, computer network protection is crucial. This is even compulsory for companies that need to protect their employees’ and clients’ sensitive information. One breach of a company’s data security would destroy its entire structure and reputation.

Security Measures are Important to Every Organization

To ensure the contribution of clients in keeping the classification, morality, and accessibility of all data assets against leakages, an association’s first guard was created which characterized with all-around procedure and administration of frameworks. Security mindfulness training is design for staff to keep vital information that protects a computer from leakages and malware, reduces the dangers against system hacks, and against other emerging threats.

Information Technology (IT) rules and methods can help guard an organization against assaults for the users to be aware, however, when a malicious interruption is attempted, technology is the thing that protects the systems to ensure IT resources. With regards to information security, conventional protection procedures ought to be in layers: firewalls, Intrusion Detection Systems (IDS) and Intrusion Prevention System (IPS) can be utilized.

Dealing with inconsistency and error can work effectively in a possible way, even without the need of human communication/supervision in the procedure demonstrates by in different studies and new improvements in the field of IDPS (Intrusion Detection and Prevention System).

How Do Neural Networks Work?

A neural network method can adjust to specific imperatives, learn framework attributes, perceive examples and contrast late client activities with the standard conduct; this permits settling many issues even without human mediation. Some contextual investigations stress that the utilization of Artificial Neural Networks (ANN) can set up general examples and recognize assault qualities in circumstances where rules are not known. The innovation guarantees to recognize abuse and enhance the acknowledgment of malevolent occasions with more consistency. A neural network can identify any cases of possible abuse, enabling framework overseers to ensure their whole association through advanced protection against dangers.

Developments on IDS and IPS Applications

IT experts have come to depend more on recognition and aversion advances to secure accessibility of business-basic data assets and to defend information secrecy and respectability by computer interruptions, ending up more typical and a developing test to beat.

Intrusion Detection Systems (IDS) can be delegated: Host-based or System based on the previous checking singular machines’ logs and the last breaking down the substance of system parcels; On the web or Disconnected, fit for hailing a risk progressively or sometime later to caution of an issue; Abuse based or Peculiarity based, either particularly checking a deviation from a standard conduct or contrasting exercises and ordinary, known aggressors’ conduct.

While IDS is outlined to detect attacks and ready people to any noxious occasions to research, an IPS is utilized to prevent malicious acts or square suspicious activity on the system. There are four distinct sorts of IPS:

1. Arrange based interruption counteractive action framework (NIPS) that takes a gander at the convention action to spot suspicious activity

2. Remote interruption anticipation framework (WIPS) that examines remote systems administration conventions and is so imperative in the BYOD and versatile driven world

3. Organize conduct examination (NBA) that can spot assaults that make irregular movement, for example, disseminated foreswearing of administration (DDoS) assaults, and it can utilize inconsistency based recognition and stateful convention investigation

4. Host-based interruption aversion framework (HIPS) that can be introduced on single machines and can utilize signature-based and peculiarity based strategies to distinguish issues.

Competitive Technology, Neural Networks

Deep Neural Networks For More Effective Security Systems

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Airports’ security is as important as national security. People, not only within the country but across the globe are going in and out of the country. The US Department of Homeland Security with the help of Google launched a contest in creating computer algorithms that will enable airports to identify hidden items in the images produced by checkpoint body scanner.

Gathering Data Scientists and Their ideas

The government aims to enhance security through advanced screening technology at airports. Kaggle which is already owned by Google and a site that holds over a million data scientists operates the said contests. The government is giving $1.5 million dollars for the contests that will run for 6 months.

Anthony Goldbloom, founder, and chief executive of Kaggle revealed that the said contest is an initiative to develop a technology named ‘deep neural networks’. These are complex mathematical systems with the ability to learn a particular task through huge data analysis. For instance, a neural network can identify what a cat is after analyzing millions of cats’ images.

Utilizing Neural Network Technology

Neural network technology is already used by Google and Facebook in several tasks. These include translation of languages, recognition of verbal commands from smartphones and identifying human faces in online images. While building algorithms were used to identify symptoms of lung cancer in CT scans in the past, neural networks are now developed to work with automated systems and read more precise body scans. This technology will not only enhance security but will also make airports services faster.

When it comes to conducting a contest, several managers and administrators find it a good idea. John W. Halinski, a security consultant considers the said contest as ‘crowdsourcing’ idea that will gather skills from different data scientists. Meanwhile, John Fortune, a program manager working in the Department of Homeland Security believes that the contest will find many people with high problem-solving skills. Moreover, Homeland Security and other agencies are in the process of discovering how neural networks can be used at security checkpoints like in the airport.

Efficiency of Neural Networks

Proponents of neural networks believe that it can upgrade airport security due to its capacity to learn data in a short time. Recently, Homeland Security supplied over a thousand three-dimensional body scans. But the scans are not shared and are not used for the contest. Volunteers from Transportation Security Administration assisted the working team in creating data by walking through a set of test scanners done in New Jersey laboratory.

Data gathered were used for analysis. The result shows that neural networks are efficient in doing security-related tasks like identifying hidden items. On the other hand, experts say that the technology is not perfect. According to some research, law offenders can change items or displaced the system to fool the system run by neural networks. In this case, the image-recognition system powered by neural networks might fail to see some concealed items.

Nevertheless, the government has seen the potential of using this technology to help human screeners in maintain top airport security. In the near future, the government and other organizations hope that neural networks will create breakthroughs in the security system and related tasks.