Deep packet inspection
Introduction
Due to the advancements in technology and its subsequent integration in almost all aspects of life, new technological advances are becoming increasingly necessary. Importantly, the cost, efficiency, and flexibility of computer networks are exceedingly proving to be an essential element of enhancing the usability of computer networks. However, the vulnerability of systems is also increasing with technological advancements. It has, therefore, become a necessity for developers to design improved systems that can overcome vulnerabilities that threaten the integrity of networks to enhance the security of systems and promote the safety of systems. These new network designs overcome the shortcomings and weaknesses of traditional networks like inefficiency in function, vulnerability, and security issues. Deep packet inspection (DPI) is a single application technology, particularly designed to solve some of the problems encountered in the use of traditional networks.
Despite being a controversial technology from a net neutrality perspective, DPI has a reliable internet management capability that helps it to support massive traffic. Moreover, DPI has an enormous computational power that enables service providers to provide different types of traffic and also prioritize traffics. Due to the intrinsic restrictions of the internet protocol in controlling and monitoring a network, DPI serves as a vital instrument for managing internet traffic. DPI integrates the internet capabilities of IPS (intrusion prevention system) and IDS (Intrusion detection system) to reduce network vulnerability and strengthen network security levels by enhancing traffic inspection, monitoring, and management (Ahmed & Kim, 2017). IPS/IDS firewalls in the DPI technology improve its capacity to monitor and detect unknown vulnerabilities, abnormal traffic, unauthorized intrusions, and malicious coding. In this regard, a critical analysis of deep packet inspection in SDN would help to explain its capability overcoming traditional network defects.
Introduction to SDN
Software defined networks (SDN) have been developed to fix the challenges experienced with the use of the traditional networks. In this view, SDN has revolutionized the mode of function of traditional networks. However, SDNs are also evolving at a rapid pace to catch up with new technological advances and as new challenges of computer networks arise. Due to the dynamism of threat and vulnerability perception of systems, network security has become a priority for researchers (Bindra & Sood, 2016). Computer scientists and researchers are increasingly delving in studies aimed at providing an effective security feature that would tackle the ever increasing and rapidly evolving network security threats. The central focus is to develop a security solution that would mitigate various network security threats, if not all.
SDN has successfully demonstrated its capacity in enhancing network security by mitigating most network threats. The fundamental capability of SDN rests in its ability to combine network management and control matrix into a centralized console. In this regard, technology has shaped the network management landscape by improving traffic control and resolving security and vulnerability issues from a centralized point. Similarly, SDN has proved to a reliable technology due to its scalability and flexibility (Yan, Yu, Gong & Li, 2016). It is also highly agile which makes it highly adaptable to changes and more responsive to new security threats as they arise in the network. As a software-based network, SDN’s control is from a centralized point. The centralized controller in SDN plays a critical role in passing instructions, which helps to reduce the disruptions of the network services.
SDN over Traditional Networks
The integration of SDN into networks has been successful in controlling and managing developments that may arise in unexplored areas. Furthermore, network management is currently prone to vulnerabilities associated to security that require a network administrator whose core mandate is to scrutinize and identify the issue without interfering with personal wireless networks and shaping traffic in the right routes. Therefore, the adoption of SDN is due to its agility, the fast response pace to issues detected as well as its flexibility in meeting consumer demands which are unlike traditional networks (Niyaz, Sun & Javaid, 2016). Moreover, SDN offers a higher level of security from threats such as hacking and theft of information, the ability to detect vulnerabilities resulting from software and failure of networks due to the centralization of controllers. The use of SDN offers users efficiency from threats that may originate from malware since it has a detector against the intrusion of the system and can counter it through controller applications.
Also, SDN is more potent than traditional networks as it has a wide range of configuration routers that can be managed to provide better security and wider visibility with reduced time and minimal resources, unlike the traditional networks. Another significance of SDN over the conventional systems is the ability to maneuver against vulnerabilities such as DoS attacks that are easily detectable through filters, and at the controller level, it is easily identified by application of redundant mode (Yu et al., 2018). Therefore, SDN is a better section as compared to traditional networks as it offers the user multiple controllers in take charge of vulnerabilities while creating reliability and secure platforms through the provision of a monitoring service.
SDN vs. Optical Transport Network
Software defined network (SDN) technology has been monumental in transforming how networks function with a higher level of efficiency. As such, SDN is a reliable technology that has been utilized extensively in large data centers and in cloud computing. As its applicability in different frontiers continues to expand, more focus is currently given to the possibility of programming SDN technology to optical transport networks (Scott-Hayward, Natarajan & Sezer, 2016). The optimization of optical transport networks through SDN has already been validated with a significant level of success. However, software engineers and programmers must first understand how to use it in different operator network architectures.
Expanding the programmability of software-based networks to optical transport networks has various advantages. Some of the benefits of SDN are that it enables the specification of resource requirements by the applications and also simplifies and accelerates service creation in the network. Similarly, SDN helps to optimize the usage of network resource, which is also applicable in optical transport networks. However, optical networks have intensely diverse architectures that often uses complex Ethernet infrastructure (Baktir, Ozgovde & Ersoy, 2017). As such, SDN should be extended beyond its rudimentary infrastructure to improve its ability to work with the complex optical network architectures. Transport networks have high reliability standards which help them to support and control traffic in the network. However, traffic in a network is highly predictable at different times. Despite having a high reliability standard, transport networks lack the aptitude to handle dynamic capacity requirements.
Due to the advancements of cloud computing technologies and the Internet of Things (IoT), it has become possible for providers to store resources remotely and distribute them virtually around the world. Cloud computing provides a more reliable resource for facilitating network security, thus protecting the integrity of data and confidentiality of information shared along the network (Shone, Ngoc, Phai & Shi, 2018).. Similarly, it supports huge traffic in the network by shifting the compute load to remote facilities when the demand rises beyond the capacity of local resources. Due to the reliability and efficacy of cloud computing in protecting networks and data against cataclysmic loss, it has reduced the demand for optical transport networks. Conversely, it has improved the preference of SDN technology as a more reliable substitute for network management.
As a software-based network, SDN applies cloud computing capabilities to enhance the storage, computing, and distribution of resources. In this light, SDN uses one network technology comprising of only Ethernet infrastructure and IP packets to handle traffic through data centers and clouds. Therefore, SDN has limited hardware constituents that only consist of routers and switches, which combine the functions of the network in a single unit (Elgendi, Munasinghe, Jamalipour & Sharma, 2017). Although the configuration and management of units from different manufacturers may vary considerably, they all rely on the use of well-understood protocols and IP packets. Primarily, this makes SDN more cost-effective and easy to manage. However, transport networks differ substantially in their basic network architectures and have complex infrastructures. As a result, transport networks have diverse network architectures that make them hard to manage and optimize resources.
Although SDN technology and optical transport networks have some similarities, they also vary in various domains. For instance, both SDN and optical transport networks have a separation of control and data planes. They also have a centralized system of network control and management. Similarly, both networks utilize circuit-oriented data planes. However, SDN technology has network programmability, which is absent in optical network (Benzekki, El Fergougui & Elbelrhiti Elalaoui, 2016). Likewise, SDN facilitates optical layer virtualization but optical transport lacks this capability. In this view, SDN provides a broad array of advantages enhanced by its agility and flexibility, as well as the separation of data and control planes. Its automation and programmability also helps to reduce the operational cost of the software-based network technology.
Cutting-Down Costs
As a network technology that decouples packet forwarding, and traffic management of a network, SDN has the capacity of slashing operational costs as well as hardware costs. On the other hand, it reduces the time of making changes in the network and creating new provisions for services. These benefits are attributable to its flexibility and agility. It is critical to note that as a software-based network, SDN stores all the intelligence of the network in software, thus, eliminating the significance of monolithic specialty hardware. As opposed to the traditional networks which used multiple switches that increase capital costs, the software-based network technology uses commodity devices, thus saving costs. The use of SDN creates an interface between applications and the network through APIs; hence, improving the performance of the application and security of the network (Zhang et al., 2018). Unlike the traditional networks that comprise of hardware gadgets consisting of independently managed data forwarding and separately configured control boxes, SDN system is highly integrated. Essentially, the architecture of the SDN network has reduces the operational and hardware costs. Similarly, its configuration makes it easier to manage and improves its scalability, and as a result, it becomes possible to make changes in the network without interfering with the entire system. With the current development in cloud computing and IoT, it has become possible for networks to be fast and agile. Cloud computing has also enabled SDN to separate data and control planes, which has also centralized network controller.
Countering Zero-day Attacks
Unlike the traditional networks, SDN employs the principles of intrusion detection system to identify threats before they attack the network. In this view, SDNs use IDS as controller applications to advance network monitoring and intrusion detection. As opposed to the traditional networks which use individual configuring of the network, IDS implements network wide objectives thus providing security from inductions in configuration (Molina & Jacob, 2018). As a result, using SDN is more effective in enhancing the security of networks and countering zero-day attacks because it has increased uptime, and uses fewer resources. On the other hand, SDN is a more preferable technology due to its enhanced network-wide visibility, better network management, improved security capability, and easy management. These factors reduce the management, operational, and maintenance costs of the technology.
On the other hand, the capability of the SDN system in managing the security and controlling the traffic of a network comes from its ability to analyze the network traffic in real-time. In this way, the system detects threats and vulnerability on the network in real-time and adjusts its configurations to mitigate attacks. SDN achieves these capabilities due to the incorporation of the intrusion detection and intrusion prevention system within its network. The combination of these capabilities helps SDN to detect possible zero-day attacks on the network and counters them by adjusting its configurations (Li, Meng & Kwok, 2016). The system then resumes its normal states after thwarting the intrusion or attack. Similarly, SDN improves the effectiveness of the intrusion detection system by making IDS function as a controller application to promote network monitoring and controlling in SDN. As a result, there is vast cost savings by ensuring real-time monitoring and mitigation of attacks, as well as increased security of the network.
Combining SDN control functions and network monitoring increases the security of the system by ensuring there is maximal control of traffic on the network and real-time inspection of possible attacks. Intrusion mitigation and security threat detection algorithms help SDN to effectively improve the security of the network (Jeong et al., 2017). However, this only works as the second line of defense after fine permission system, which applies minimum privileges on application. Nonetheless, the use of deep packet inspection (DPI) in SDN can help to improve the real-time monitoring of the network, thus enhancing its security.
Vulnerabilities and Mitigation Measures
Although SDN is the most preferred network due to its efficiency due to its security features and ease of maneuvering threats, it is equally vulnerable to interference from malware and infected files that cripple the use of wireless networks. However, SDN is highly effective in countering such attacks by having a monitoring service that checks the flow of information. Also, conducting a physical performance on networks allows the detection of vulnerabilities that may hinder its operations by identifying the controller system and distributing the load (da Silva, Wickboldt, Granville & Schaeffer-Filho, 2016). Also, the creation of IP packets in a bid to conceal the identity of the threat is a major form of eliminating suspicion as DoS attacks are rarely seen under filters. The major vulnerabilities related to SDN include the DDos and DoS as well as forged traffic flows that constantly cause disruption of the networks through the interference of rogue elements. As a result of DDoS or DoS attack, there can be corruption of networks to the point that the operating system is controlled and managed through the same network.
Following the identification of vulnerabilities that both the traditional networks and SDN face, the best form of mitigation would be to adopt an automatic trust model that verifies credentials and prevents the replication of vulnerabilities. Moreover, the use of flexible sampling to counter network packets that conceal into undetectable packets would assist in preventing its vulnerabilities. In most cases, the use of public network poses a greater risk as compared to a home network (Joshi, Joshi & Joshi, 2018). Hence, the use of SDN network would increase security when loading onto public wireless platforms and eliminate possible threats. Regarding the failure of components that may interfere with the functioning of controllers and increase their vulnerabilities, SDN acts in an arbitrary manner to counter any form of threat through a self-healing mechanism. Ultimately, the use of sampling algorithm allows the detection of malware.
Computational Power
A bloom filter is an efficient data structure that is randomized and offer supportive responses to queries through provision of functions. The filters can have a false positive element that allows the returning low false drawback of probability within a widespread database. Moreover, bloom filters act as a prime significance to securing millions of data through development of solutions to strong, and updating queries in data structures through the representation of various elements and reducing the storage requirements (Sood, Yu & Xiang, 2016). The data structures give probability representation that represents networking that allows the filtering of unwanted information. In most cases, bloom filters apply the hashing technique to gives the positive performance in an element as well as create a constant factor that is part p the computational power as opposed to memory access which has the power to slow down the computation time. Also, perfect hashing is an alternative to bloom filters as it sets the platform for harsh computation and gives the storage functionality in each location through use of finger printing and creates a dynamic environment.
Fundamentally, the choice of computation power depends on the improvement of bloom filters and the use of hashing technique that results in reduced performance and mapping of a specific location with the use of universally acceptable reporting mechanisms. The purpose for use of the predicting ideals for computation of elements is as a result of the choice of bloom filters chosen to study the gap between the theory and practice. Furthermore, the formulation of the computation elements through insertion and deletion of elements that would otherwise not contribute to the probability of items applicable to the process (Yang, Ng & Seah, 2016). The analysis of the most viable computation method relies on the size of the bloom filter, the hash elements, and the counters. In most cases, the flow of element and their count is a determination of the probability of the structures set in place to the target positions of operation increments that approximate the counting items. When there is an overlap of the inserted elements to the function, it tends to minimize the counts of the locations that are subject to the bloom filter, and creates space for overflowing of elements that are either deleted or inserted into the operations.
Regarding the implementation of hardware, SDN is highly promising on flexibility and management of networks that require programming of data and accommodating various changes. As such, SDN easily shifts from a programmable commodity into a low cost software that is operational in terms of security and reconfigures towards FPGA platform to ensure the switch ha deployment of security models such as packet detectors and filters. For instance, the choice of FPGA that has acceleration from SDN results in a switch process that allows offloading of content that is not aligned to the performance of the induced software (Niyaz, Sun & Javaid, 2016). In line with network hardware, the device that is chosen by the programmer has to be simple and support the protocol’s underlying technologies through the relevant hardware. In a broad perspective, the hardware is responsible for transmitting data in and out of a device through the transmission and management of data in a physical layer. In most cases, the supporting capabilities of communication of a hardware is through the type of data it is carrying and it combination with the local units which offer control, management of data, and processing of components.
Conclusion