Telecom operators are currently using Artificial Intelligence (AI) technologies to improve their services. Cloud providers are beginning to provide AI as a service, making the technology available to all customers. Compromising an operator is valuable to the attacker, and using AI to increase their success rate is considered a technique to do so. Telecommunications providers are also under attack from two directions: direct attacks from cybercriminals attempting to compromise their organization and network operations, and indirect attacks from those attempting to steal their subscribers’ data. Many classic attack vectors are present among the top threats now attacking each of these frontlines, but with new twists in terms of complexity or size that place new demands on telecoms businesses. The following are some of the threats:
- Distributed Denial of Service (DDoS) attacks
- The exploitation of vulnerabilities in network and consumer devices
- Compromising subscribers with social engineering, phishing or malware
- Insider threat
To neutralize these hazards, we must first detect them, after which only appropriate preventive steps may be considered. As a result, an intrusion detection system is used to detect the intrusion. In addition, a machine learning technique is employed to improve intrusion detection. In fact, a model is generated when a machine learns from a collection of training data. Test data is compared or evaluated using that model to identify attacks. Intrusion detection is carried out in the proposed system utilizing a machine learning algorithm that learns from a training dataset before testing the network traffic dataset. The number of attacks detected by a model, which are then categorized based on a likelihood, is the end outcome. Either of the following will be the final classification: Denial of Service (DoS), Remote to Local (R2L), User to Root (U2R), PROBE, and NORMAL.
Introduction
Telecommunications networks have evolved from circuit-switched to packet-switched to all-IP-based networks in this era of Information and Communication Technology (ICT). Both cable and wireless communication networks have seen significant increases in transmission speeds. With the increase in transmission speeds, communications networks are on the verge of a massive increase in the number of attacks on them. The telecommunications industry is constantly fighting to keep on top of information security threats. The recent trend in telecom companies is that they are expanding their reach and converting into full-fledged technological firms. As a result, the telecom ecosystem has become sophisticated for commercial purposes, and it continues to face unceasing IT challenges to balance a variety of compliance requirements. Due to its engagement with millions of customers who subscribe to services such as cable, the Internet, home and mobile phone service, and even data centers, the industry is operating in a high-risk environment.
Because of the range and depth of services provided by telecom businesses, there is a considerable increase in the danger of security risks. While the telecom industry is better able to safeguard its networks due to its nature, there are a number of progressive dangers that must be addressed. If telecom networks are breached, the potential consequences include phone service interruptions affecting millions of subscribers, internet outages affecting millions of users, and the possibility for enterprises to be irreparably harmed. Overall IT security incidents in the telecommunications business grew to 45 percent in 2015, according to PwC’s Global State of Information Security, 2016.
Telecommunication service providers have a sizable consumer base, which serves as a strong incentive for bad actors to break into the network. Furthermore, security dangers to computer networks have also increased. The computer and its networking have served as the backbone for essential industries and all of the world’s leading multinational corporations.
In general, the telecom industry is at risk from two aspects. They are:
- Direct attacks by cyber criminals aimed directly at their business, and
- Indirect attacks targeting subscribers.
Unauthorized action on a network or system is referred to as intrusion. It is, in reality, an effective attack with a definite goal. Denial of Service (DoS) attacks, packet sniffing, and remote login are just a few common instances of network intrusions. Trojans and spyware are some of the methods used to get access to a computer’s system.
In network security, intrusion detection is a key operation. The standard method of detecting network intrusions is based on a saved pattern of previously detected attacks. They identify intrusions by matching network connection characteristics to attack patterns reported by humans. Traditional approaches have the major flaw of being unable to detect unknown attacks or intrusions. Even for a new attack pattern, the system would have to be manually updated to incorporate it.
Intrusion Detection System (IDS)
Intrusion Detection Systems (IDS) is software or hardware systems that identify hostile activity in a computer network by automating the process of monitoring and analyzing events. It enables businesses to safeguard their systems against the dangers that come with increased network connectivity and reliance on information technology. In today’s environment, an intrusion detection system with specific characteristics and capabilities is essential. Intrusions are typically triggered by: attackers gaining access to systems, Authorized system users who try to get additional rights for which they are not authorized, and authorized users who abuse the powers that have been granted to them. Data security has become a critical component of every information system within a business. Internet threats have evolved to the point where they can fool even the most basic security measures, such as firewalls and antivirus scanners. An additional security layer, such as an intrusion detection system (IDS), must be implemented to improve the network’s overall security. Anomaly detection IDS is a sort of IDS that can detect normal and anomalous data in the monitored data.
Thank you Ramesh KC Sir, Senior Engineer, Nepal Telecom