Biblio

Software Defined Networking (SDN) is an emerging technology, which provides the flexibility in communicating among network. Software Defined Network features separation of the data forwarding plane from the control plane which includes controller, resulting centralized network. Due to centralized control, the network becomes more dynamic, and resources are managed efficiently and cost-effectively. Network Virtualization is transformation of network from hardware-based to software-based. Network Function Virtualization will permit implementation, adaptable provisioning, and even management of functions virtually. The use of virtualization of SDN networks permits network to strengthen the features of SDN and virtualization of NFV and has for that reason has attracted notable research awareness over the last few years. SDN platform introduces network security challenges. The network becomes vulnerable when a large number of requests is encapsulated inside packet\_in messages and passed to controller from switch for instruction, if it is not recognized by existing flow entry rules. which will limit the resources and become a bottleneck for the entire network leading to DDoS attack. It is necessary to have quick provisional methods to prevent the switches from breaking down. To resolve this problem, the researcher develops a mechanism that detects and mitigates flood attacks. This paper provides a comprehensive survey which includes research relating frameworks which are utilized for detecting attack and later mitigation of flood DDoS attack in Software Defined Network (SDN) with the help of NFV.

DDoS attacks still represent a severe threat to network services. While there are more or less workable solutions to defend against these attacks, there is a significant space for further research regarding automation of reactions and subsequent management. In this paper, we focus on one piece of the whole puzzle. We strive to automatically infer filtering rules which are specific to the current DoS attack to decrease the time to mitigation. We employ a machine learning technique to create a model of the traffic mix based on observing network traffic during the attack and normal period. The model is converted into the filtering rules. We evaluate our approach with various setups of hyperparameters. The results of our experiments show that the proposed approach is feasible in terms of the capability of inferring successful filtering rules.

Internet of Things (IoT) and those protocol CoAP and MQTT has security issues that have entirely changed the security strategy should be utilized and behaved for devices restriction. Several challenges have been observed in multiple domains of security, but Distributed Denial of Service (DDoS) have actually dangerous in IoT that have RT. Thus, the IoT paradigm and those protocols CoAP and MQTT have been investigated to seek whether network services could be efficiently delivered for resources usage, managed, and disseminated to the devices. Internet of Things is justifiably joined with the best practices augmentation to make this task enriched. However, factors behaviors related to traditional networks have not been effectively mitigated until now. In this paper, we present and deep, qualitative, and comprehensive systematic mapping to find the answers to the following research questions, such as, (i) What is the state-of-the-art in IoT security, (ii) How to solve the restriction devices challenges via infrastructure involvement, (iii) What type of technical/protocol/ paradigm needs to be studied, and (iv) Security profile should be taken care of, (v) As the proposals are being evaluated: A. If in simulated/virtualized/emulated environment or; B. On real devices, in which case which devices. After doing a comparative study with other papers dictate that our work presents a timely contribution in terms of novel knowledge toward an understanding of formulating IoT security challenges under the IoT restriction devices take care.

As cyber threats become highly damaging and complex, a new cybersecurity compliance certification model has been developed by the Department of Defense (DoD) to secure its Defense Industrial Base (DIB), and communication with its private partners. These partners or contractors are obligated by the Defense Federal Acquisition Regulations (DFARS) to be compliant with the latest standards in computer and data security. The Cybersecurity Maturity Model Certification (CMMC), and it is built upon existing DFARS 252.204-7012 and the NIST SP 800–171 controls. As of 2020, the DoD has incorporated DFARS and the National Institute of Standards and Technology (NIST) recommended security practices into what is now the CMMC. This paper presents the most commonly identified Security-Control-Deficiencies (SCD) faced, the attacks mitigated by addressing these SCD, and remediations applied to 127 DoD contractors in order to bring them into compliance with the CMMC guidelines. An analysis is done on what vulnerabilities are most prominent in the companies, and remediations applied to ensure these vulnerabilities are better avoided and the DoD supply-chain is more secure from attacks.

The digital transformation brought on by 5G is redefining current models of end-to-end (E2E) connectivity and service reliability to include security-by-design principles necessary to enable 5G to achieve its promise. 5G trustworthiness highlights the importance of embedding security capabilities from the very beginning while the 5G architecture is being defined and standardized. Security requirements need to overlay and permeate through the different layers of 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture within a risk-management framework that takes into account the evolving security-threats landscape. 5G presents a typical use-case of wireless communication and computer networking convergence, where 5G fundamental building blocks include components such as Software Defined Networks (SDN), Network Functions Virtualization (NFV) and the edge cloud. This convergence extends many of the security challenges and opportunities applicable to SDN/NFV and cloud to 5G networks. Thus, 5G security needs to consider additional security requirements (compared to previous generations) such as SDN controller security, hypervisor security, orchestrator security, cloud security, edge security, etc. At the same time, 5G networks offer security improvement opportunities that should be considered. Here, 5G architectural flexibility, programmability and complexity can be harnessed to improve resilience and reliability. The working group scope fundamentally addresses the following: •5G security considerations need to overlay and permeate through the different layers of the 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture including a risk management framework that takes into account the evolving security threats landscape. •5G exemplifies a use-case of heterogeneous access and computer networking convergence, which extends a unique set of security challenges and opportunities (e.g., related to SDN/NFV and edge cloud, etc.) to 5G networks. Similarly, 5G networks by design offer potential security benefits and opportunities through harnessing the architecture flexibility, programmability and complexity to improve its resilience and reliability. •The IEEE FNI security WG's roadmap framework follows a taxonomic structure, differentiating the 5G functional pillars and corresponding cybersecurity risks. As part of cross collaboration, the security working group will also look into the security issues associated with other roadmap working groups within the IEEE Future Network Initiative.

Software and firmware vulnerabilities pose security threats to photovoltaic (PV) systems. When patches are not available or cannot be timely applied to fix vulnerabilities, it is important to mitigate vulnerabilities such that they cannot be exploited by attackers or their impacts will be limited when exploited. However, the vulnerability mitigation problem for PV systems has received little attention. This paper analyzes known security vulnerabilities in PV systems, proposes a multi-level mitigation framework and various mitigation strategies including neural network-based attack detection inside inverters, and develops a prototype system as a proof-of-concept for building vulnerability mitigation into PV system design.

The need for cyber resilience is increasingly important in our technology-dependent society, where computing systems, devices and data will continue to be the target of cyber attackers. Hence, we propose a conceptual framework called ‘Human-in-the-Loop Explainable-AI-Enabled Vulnerability Detection, Investigation, and Mitigation’ (HXAI-VDIM). Specifically, instead of resolving complex scenario of security vulnerabilities as an output of an AI/ML model, we integrate the security analyst or forensic investigator into the man-machine loop and leverage explainable AI (XAI) to combine both AI and Intelligence Assistant (IA) to amplify human intelligence in both proactive and reactive processes. Our goal is that HXAI-VDIM integrates human and machine in an interactive and iterative loop with security visualization that utilizes human intelligence to guide the XAI-enabled system and generate refined solutions.

Society heavily relies upon the Internet for global communications. Simultaneously, Internet stability and reliability are continuously subject to deliberate threats. These threats include (Distributed) Denial-of-Service (DDoS) attacks, which can potentially be devastating. As a result of DDoS, businesses lose hundreds of millions of dollars annually. Moreover, when it comes to vital infrastructure, national safety and even lives could be at stake. Effective defenses are therefore an absolute necessity. Prospective users of readily available mitigation solutions find themselves having many shapes and sizes to choose from, the right fit of which may, however, not always be apparent. In addition, the deployment and operation of mitigation solutions may come with hidden hazards that need to be better understood. Policy makers and governments also find themselves facing questions concerning what needs to be done to promote cybersafety on a national level. Developing an optimal course of action to deal with DDoS, therefore, also brings about societal challenges. Even though the DDoS problem is by no means new, the scale of the problem is still unclear. We do not know exactly what it is we are defending against and getting a better understanding of attacks is essential to addressing the problem head-on. To advance situational awareness, many technical and societal challenges need still to be tackled. Given the central importance of better understanding the DDoS problem to improve overall Internet security, the thesis that we summarize in this paper has three main contributions. First, we rigorously characterize attacks and attacked targets at scale. Second, we advance knowledge about the Internet-wide adoption, deployment and operational use of various mitigation solutions. Finally, we investigate hidden hazards that can render mitigation solutions altogether ineffective.

Distributed large-scale cyber attacks targeting the availability of computing and network resources still remain a serious threat. To limit the effects caused by those attacks and to provide a proactive defense, mitigation should move to the networks of Internet Service Providers (ISPs). In this context, this thesis focuses on a development of a collaborative, automated approach to mitigate the effects of Distributed Denial of Service (DDoS) attacks at Internet Scale. This thesis has the following contributions: i) a systematic and multifaceted study on mitigation of large-scale cyber attacks at ISPs. ii) A detailed guidance selecting an exchange format and protocol suitable to use to disseminate threat information. iii) To overcome the shortcomings of missing flow-based interoperability of current exchange formats, a development of the exchange format Flow-based Event Exchange Format (FLEX). iv) A communication process to facilitate the automated defense in response to ongoing network-based attacks, v) a model to select and perform a semi-automatic deployment of suitable response actions. vi) An investigation of the effectiveness of the defense techniques moving-target using Software Defined Networking (SDN) and their applicability in context of large-scale cyber attacks and the networks of ISPs. Finally, a trust model that determines a trust and a knowledge level of a security event to deploy semi-automated remediations and facilitate the dissemination of security event information using the exchange format FLEX in context of ISP networks.

In accordance to the annual report by the Cisco 2018, web applications are exposed to several security vulnerabilities that are exploited by hackers in various ways. It is becoming more and more frequent, specific and sophisticated. Of all the vulnerabilities, more than 40% of attempts are performed via cross-site scripting (XSS). A number of methods have been postulated to examine such vulnerabilities. Therefore, this paper attempted to address an overview of one such vulnerability: the cookies in the XSS. The objective is to present an overview of the cookies, it's type, vulnerability, policies, discovering, protecting and their mitigation via different tools/methods and via cryptography, artificial intelligence techniques etc. While some future issues, directions, challenges and future research challenges were also being discussed.

Cryptojacking (also called malicious cryptocurrency mining or cryptomining) is a new threat model using CPU resources covertly “mining” a cryptocurrency in the browser. The impact is a surge in CPU Usage and slows the system performance. In this research, in-browsercryptojacking mitigation has been built as an extension in Google Chrome using Taint analysis method. The method used in this research is attack modeling with abuse case using the Man-In-The-Middle (MITM) attack as a testing for mitigation. The proposed model is designed so that users will be notified if a cryptojacking attack occurs. Hence, the user is able to check the script characteristics that run on the website background. The results of this research show that the taint analysis is a promising method to mitigate cryptojacking attacks. From 100 random sample websites, the taint analysis method can detect 19 websites that are infcted by cryptojacking.

Content Delivery Networks(CDN) is a standout amongst the most encouraging innovations that upgrade performance for its clients' websites by diverting web demands from browsers to topographically dispersed CDN surrogate nodes. However, due to the variable nature of CDN, it suffers from various security and resource allocation issues. The most common attack which is used to bring down a whole network as well as CDN without even finding a loophole in the security is DDoS. In this proposal, we proposed a distributed virtual honeypot model for diminishing DDoS attacks and prevent intrusion in securing CDN. Honeypots are specially utilized to imitate the primary server with the goal that the attack is alleviated to the fake rather than the main server. Our proposed layer based model utilizes honeypot to be more effective reducing the cost of the system as well as maintaining the smooth delivery in geographically dispersed servers without performance degradation.

SDN is new networking concept which has revolutionized the network architecture in recent years. It decouples control plane from data plane. Architectural change provides re-programmability and centralized control management of the network. At the same time it also increases the complexity of underlying physical infrastructure of the network. Unfortunately, the centralized control of the network introduces new vulnerabilities and attacks. Attackers can exploit the limitation of centralized control by DDoS attack on control plane. The entire network can be compromised by DDoS attack. Based on packet entropy, a solution for mitigation of DDoS attack provided in the proposed scheme.

Software-defined networking (SDN) is a relatively new technology that promotes network revolution. The most distinct characteristic of SDN is the transformation of control logic from the basic packet forwarding equipment to a centralized management unit called controller. However, the centralized control of the network resources is like a double-edged sword, for it not only brings beneficial features but also introduces single point of failure if the controller is under distributed denial of service (DDoS) attacks. In this paper, we introduce a light-weight approach based on conditional entropy to improve the SDN security with an aim of defending DDoS at the early stage. The experimental results show that the proposed method has a high average detection rate of 99.372%.

Transient execution attacks like Spectre, Meltdown and Foreshadow have shown that combinations of microarchitectural side-channels can be synergistically exploited to create side-channel leaks that are greater than the sum of their parts. While both hardware and software mitigations have been proposed against these attacks, provable security has remained elusive. This paper introduces a formal methodology for enabling secure speculative execution on modern processors. We propose a new class of information flow security properties called trace property-dependent observational determinism (TPOD). We use this class to formulate a secure speculation property. Our formulation precisely characterises all transient execution vulnerabilities. We demonstrate its applicability by verifying secure speculation for several illustrative programs.

With the rapid development of radio detection and wireless communication, narrowband radio-frequency interference (NB-RFI) is a serious threat for GNSS-R (global navigation satellite systems - reflectometry) receivers. However, interferometric GNSS-R (iGNSS-R) is more prone to the NB-RFIs than conventional GNSS-R (cGNSS-R), due to wider bandwidth and unclean replica. Therefore, there is strong demand of detecting and mitigating NB-RFIs for GNSS-R receivers, especially iGNSS-R receivers. Hence, focusing on working with high sampling rate and simplifying the fixed-point implementation on FPGA, this paper proposes a system design exploiting cascading IIR band-stop filters (BSFs) to suppress NB-RFIs. Furthermore, IIR BSF compared with IIR notch filter (NF) and IIR band-pass filter (BPF) is the merely choice that is able to mitigate both white narrowband interference (WNBI) and continuous wave interference (CWI) well. Finally, validation and evaluation are conducted, and then it is indicated that the system design can detect NB-RFIs and suppress WNBI and CWI effectively, which improves the signal-to-noise ratio (SNR) of the Delay-Doppler map (DDM).

Cloud computing is an assured progression inside the future of facts generation. It's far a sub-domain of network security. These days, many huge or small organizations are switching to cloud which will shop and arrange their facts. As a result, protection of cloud networks is the want of the hour. DDoS is a killer software for cloud computing environments on net today. It is a distributed denial of carrier. we will beat the ddos attacks if we have the enough assets. ddos attacks can be countered by means of dynamic allocation of the assets. In this paper the attack is detected as early as possible and prevention methods is done and also mitigation method is also implemented thus attack can be avoided before it may occur.

Bitcoin exchanges rely heavily on traditional intrusion detection system to secure their system. However, this reliance has proven to be high risk, since Bitcoin and other blockchain-based transactions are not easily reversible. Many of the attacks have shown that the traditional intrusion detection system is not enough to safeguard against all possible attacks, and most importantly, in some cases, it takes a long time to assess the damage. In this paper, we first describe three types of intrusion models in Bitcoin exchanges and propose a detection and mitigation system using blockchain analysis for each. The proposed detection and mitigation system exploit the decentralized and public nature of Bitcoin blockchain to complement the existing traditional intrusion detection system as a fail-safe. The proposed method provides real-time intrusion detection capability that the existing work cannot provide. Although the proposed method is specifically for Bitcoin blockchain, similar ideas can be extended to other proof-of-work based blockchain cryptocurrencies.

This research aims to identify some vulnerabilities of advanced persistent threat (APT) attacks using multiple simulated attacks in a virtualized environment. Our experimental study shows that while updating the antivirus software and the operating system with the latest patches may help in mitigating APTs, APT threat vectors could still infiltrate the strongest defenses. Accordingly, we highlight some critical areas of security concern that need to be addressed.

There has been a growing spate of Cyber attacks targeted at different corporate enterprises and systems across the globe. The scope of these attacks spans from small scale (grid and control system manipulation, domestic meter cyber hacking etc) to large scale distributed denial of service attacks (DDoSA) in enterprise networks. The effect of hacking on control systems through distributed control systems (DCS) using communication protocols on vulnerable home area networks (HANs) and neighborhood area networks (NANs) is terrifying. To meet the current security requirements, a new security network is proposed called Smart grid convoluted network (SGCN). With SGCN, the basic activities of data processing, monitoring and query requests are implemented outside the grid using Fog computing layer-3 devices (gatekeepers). A cyber monitor agent that leverages a reliable end-to end-communication network to secure the systems components on the grid is employed. Cyber attacks which affects the computational requirements of SG applications is mitigated by using a Fourier predictive cyber monitor (FPCM). The network uses flexible resources with loopback services shared across the network. Serial parallelism and efficient bandwidth provisioning are used by the locally supported Fog nodes within the SG cloud space. For services differentiation, SGCN employed secure communication between its various micro-grids as well as its metering front-ends. With the simulated traffic payload extraction trend (STPET), SGCN promises hard time for hackers and malicious malwares. While the work guarantees security for SGs, reliability is still an open issue due to the complexity of SG architecture. In conclusion, the future of the Cyber security in SGs must employ the concept of Internet of Everything (IoE), Malware predictive analytics and Fog layers on existing SG prototypes for optimal security benefits.

Cybercrimes today are focused over returns, especially in the form of monetary returns. In this paper - through a literature study and conducting interviews for the people victimized by ransomware and a survey with random set of victimized and non-victimized by ransomware - conclusions about the dependence of ransomware on demographics like age and education areshown. Increasing threats due to ease of transfer of ransomware through internet arealso discussed. Finally, low level awarenessamong company professionals is confirmed and reluctance to payment on being a victim is found as a common trait.

In cyberspace, availability of the resources is the key component of cyber security along with confidentiality and integrity. Distributed Denial of Service (DDoS) attack has become one of the major threats to the availability of resources in computer networks. It is a challenging problem in the Internet. In this paper, we present a detailed study of DDoS attacks on the Internet specifically the attacks due to protocols vulnerabilities in the TCP/IP model, their countermeasures and various DDoS attack mechanisms. We thoroughly review DDoS attacks defense and analyze the strengths and weaknesses of different proposed mechanisms.

The need to keep an attacker oblivious of an attack mitigation effort is a very important component of a defense against denial of services (DoS) and distributed denial of services (DDoS) attacks because it helps to dissuade attackers from changing their attack patterns. Conceptually, DDoS mitigation can be achieved by two components. The first is a decoy server that provides a service function or receives attack traffic as a substitute for a legitimate server. The second is a decoy network that restricts attack traffic to the peripheries of a network, or which reroutes attack traffic to decoy servers. In this paper, we propose the use of a two-stage map table extension Locator/ID Separation Protocol (LISP) to realize a decoy network. We also describe and demonstrate how LISP can be used to implement an oblivious DDoS mitigation mechanism by adding a simple extension on the LISP MapServer. Together with decoy servers, this method can terminate DDoS traffic on the ingress end of an LISP-enabled network. We verified the effectiveness of our proposed mechanism through simulated DDoS attacks on a simple network topology. Our evaluation results indicate that the mechanism could be activated within a few seconds, and that the attack traffic can be terminated without incurring overhead on the MapServer.