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IoT Security Frameworks and Countermeasures
Published in Stavros Shiaeles, Nicholas Kolokotronis, Internet of Things, Threats, Landscape, and Countermeasures, 2021
G. Bendiab, B. Saridou, L. Barlow, N. Savage, S. Shiaeles
A Next-Generation Firewall (NGFW) is the more advanced and effective solution for network security as NGFWs combine knowledge of both rulesets and policies, with an understanding of threats relating to the application-level protocols and applications used in the network [33]. This enriched knowledge base makes it able to detect and block packets that are deemed to be malicious, along with a variety of attacks. This type of firewall can implement a range of additional security controls on a network. This includes deep packet inspection, where not only basic packet data is inspected, but the identification of what applications are being used for the data stream. When paired with relevant and easily updated intelligence, this allows it to detect possible exploits and attacks at a greater level of accuracy [33].
Microsegmentation
Published in Dijiang Huang, Ankur Chowdhary, Sandeep Pisharody, Software-Defined Networking and Security, 2018
Dijiang Huang, Ankur Chowdhary, Sandeep Pisharody
Around the late 1990s, firewall inspecting traffic at the application protocol layer started; it is called application-level firewall. The key benefit of application layer firewall is to understand particular applications and protocols such as File Transfer Protocol (FTP), Domain Name System (DNS), or Hypertext Transfer Protocol (HTTP). This is useful as it is able to detect if an unwanted application or service is attempting to bypass the firewall using a protocol on an allowed port, or detect if a protocol is being abused in any harmful way. Time forwards to 2011 and 2012, when SDN and NFV came into the picture, where firewall technologies had faced a huge challenge as well as opportunities. Microsegmentation was brought up in the SDN community to provide fine-grained level of packet inspection at any network segment and push the inspection into a more refined level. As of 2012, the so-called Next-Generation Firewall (NGFW)Next-Generation Firewall (NGFW) is nothing more than the “wider” or “deeper” inspection at application stack. For example, the existing deep packet inspection functionality of modern firewalls can be extended to include Intrusion prevention systems (IPS).
Picture Fuzzy N-Soft Sets and Their Applications in Decision-Making Problems
Published in Fuzzy Information and Engineering, 2021
Ubaid Ur Rehman, Tahir Mahmood
It is observed that one of the essential concept of neutral grade is missing in the IFN-SS theory. Concept of neutrality grade can be observed in the situation when we encounter human views including more answers of type: yes, abstain, no, refusal. To overcome this issue, we interpreted the idea of PFN-SS by merging PFSs and N-SSs in this manuscript. We defined some relevant properties of PFN-SS such as a compliment, restricted intersection and union, extended intersection, and union, M-subset, and F-subset of PFN-SS. We also linked PFSSs with PFN-SS by using a threshold. Further, we gave numerical examples to explain these notions. We described an algorithm to deal with PFN-SS data. To show the advantage and usefulness of the defined technique, we used two examples which are Selection of corona vaccineSelection of next generation firewall from real life by utilising PFN-SS data. In the selection of the corona vaccine we have seen that the corona vaccine was the best vaccine to purchase according to the health expert. Similarly in the selection of a company for a job, we have seen that the company was the best company for a job according to the expert. After this, we did a comparison of our work with IFN-SS by using Example 16 given in Section 5 in which we have seen that how PFN-SS change the result which an expert got by using IFN-SS data. From that example, we got the results that our defined algorithm in Section 4 is more general than the algorithm defined by Akram et al. [46]. One can solve IFN-SS data by our proposed algorithm by taking the neutral membership zero. By our proposed algorithm one can also solve the FN-SS by taking neutral membership and non-membership zero. This showed that our initiated method is more general and suitable than the intuitionistic fuzzy N-SS (IFN-SS), fuzzy N-SS (FN-SS), and N-SS.