Biblio

This article presents results and overview of conducted testing of active optical network devices. The base for the testing is originating in Kali Linux and penetration testing generally. The goal of tests is to either confirm or disprove a vulnerability of devices used in the tested polygon. The first part deals with general overview and topology of testing devices, the next part is dedicated to active and passive exploration and exploits. The last part provides a summary of the results.

Industry 4.0 or the fourth industrial revolution encapsulates future industry development trends to achieve more intelligent manufacturing processes, including reliance on Cyber Physical Systems (CPS). The increase in online access and control given by the incorporation of CPSs introduces a new challenge securing the operations of the CPS in that they are not supported by standard security protocols. This paper describes a process used to effectively protect the operations of an IIoT system by implementing security protocols on the CPS within the IIoT. A series of predefined boundary conditions of the safety critical parameters for which a heating and cooling CPS can safely operate within were established. If the CPS is commended to operate outside of these boundaries, it will disconnect from all external communication network and default to some pre-defined safe-operation mode until the system has been evaluated locally by an administrator and released from the safe-mode. This method was tested and validated by establishing a sample IIoT and CPS testbed setup which monitor and control the temperature of a target environment. An attack was initiated to force the target environment outside of the determined safety-critical parameters. The system responded by disabling all network ports and defaulted to the safe-operation mode established previously.

Peer-to-Peer networks are designed to rely on the resources of their own users. Therefore, resource management plays an important role in P2P protocols. Early P2P networks did not use proper mechanisms to manage fairness. However, after seeing difficulties and rise of freeloaders in networks like Gnutella, the importance of providing fairness for users have become apparent. In this paper, we propose an incentive-based security model which leads to a network infrastructure that lightens the work of Seeders and makes Leechers to contribute more. This method is able to prevent betrayals in Leecher-to-Leecher transactions and helps Seeders to be treated more fairly. This is what other incentive methods such as Bittorrent are incapable of doing. Additionally, by getting help from cryptography and combining it with our method, it is also possible to achieve secure channels, immune to spying, next to a fair network. This is the first protocol designed for P2P networks which has separated Leechers and Seeders without the need to a central server. The simulation results clearly show how our proposed approach can overcome free-riding issue. In addition, our findings revealed that our approach is able to provide an appropriate level of fairness for the users and can decrease the download time.

Wireless Sensor Networks (WSNs) are important and becoming more important as we integrate wireless sensor networks and the internet with different things, which has changed our life, and it is affected everywhere in our life like shopping, storage, live monitoring, smart home etc., called Internet of Things (IoT), as any use of the network physical devices that included in electronics, software, sensors, actuators, and connectivity which makes available these things to connect, collect and exchange data, and the most importantly thing is the accuracy of the data that has been collected in the Internet of Things, detecting sensor data with faulty readings is an important issue of secure communication and power consumption. So, requirement of energy-efficiency and integrity of information is mandatory.

Internet of things is a network formed between two or more devices through internet which helps in sharing data and resources. IoT is present everywhere and lot of applications in our day-to-day life such as smart homes, smart grid system which helps in reducing energy consumption, smart garbage collection to make cities clean, smart cities etc. It has some limitations too such as concerns of security of the network and the cost of installations of the devices. There have been many researches proposed various method in improving the IoT systems. In this paper, we have discussed about the scope and limitations of IoT in various fields and we have also proposed a technique to secure offline architecture of IoT.

The traditional smart-home is designed to integrate the concept of the Internet of Things(IoT) into our home environment, and to improve the comfort of home. It connects electrical products and household goods to the network, and then monitors and controls them. However, this paper takes home safety as the main axis of research. It combines the past concept of smart-home and technology of machine learning to improve the whole system of smart-home. Through systematic self-learning, it automatically figure out whether it is normal or abnormal, and reports to remind building occupants safety. At the same time, it saves the cost of human resources preservation. This paper make a set of rules table as the basic criteria first, and then classify a part of data which collected by traditional Internet of Things of smart-home by manual way, which includes the opening and closing of doors and windows, the starting and stopping of motors, the connection and interruption of the system, and the time of sending each data to label, then use Support Vector Machine(SVM) algorithm to classify and build models, and then train it. The executed model is applied to our smart-home system. Finally, we verify the Accuracy of anomaly reporting in our system.

The massive growth of the global routing tables is one of the biggest problems that still face internet nowadays. This problem is mainly caused by the random distribution of IPv4 addresses. With the immigration to IPv6 and the large ranges of addresses provided by this protocol, it is crucial to wisely manage the assignment of IPv6 prefixes. In this paper, we propose a process to generate a logical topology of IPv6 networks. This topology uses perfectly the summarization technique and consists in representing the summary routes in hierarchical manner such that large range of addresses represents several smaller ranges. The proposed aggregation process optimizes and divides up the routing tables which may help resolve the problem of the explosive growth of internet routing tables. Furthermore, the logical topology can be easly customized to fit the features of the routers that are used in the network.

Protection from DDoS-attacks is one of the most urgent problems in the world of network technologies. And while protect systems has algorithms for detection and preventing DDoS attacks, there are still some unresolved problems. This article is devoted to the DDoS-attack called Pulse Wave. Providing a brief introduction to the world of network technologies and DDoS-attacks, in particular, aims at the algorithm for protecting against DDoS-attack Pulse Wave. The main goal of this article is the implementation of traffic classifier that adds rules for infected computers to put them into a separate queue with limited bandwidth. This approach reduces their load on the service and, thus, firewall neutralises the attack.

This paper provides a Common Vulnerability Scoring System (CVSS) metric-based technique for classifying and analysing the prevailing Computer Network Security Vulnerabilities and Threats (CNSVT). The problem that is addressed in this paper, is that, at the time of writing this paper, there existed no effective approaches for analysing and classifying CNSVT for purposes of assessments based on CVSS metrics. The authors of this paper have achieved this by generating a CVSS metric-based dynamic Vulnerability Analysis Classification Countermeasure (VACC) criterion that is able to rank vulnerabilities. The CVSS metric-based VACC has allowed the computation of vulnerability Similarity Measure (VSM) using the Hamming and Euclidean distance metric functions. Nevertheless, the CVSS-metric based on VACC also enabled the random measuring of the VSM for a selected number of vulnerabilities based on the [Ma-Ma], [Ma-Mi], [Mi-Ci], [Ma-Ci] ranking score. This is a technique that is aimed at allowing security experts to be able to conduct proper vulnerability detection and assessments across computer-based networks based on the perceived occurrence by checking the probability that given threats will occur or not. The authors have also proposed high-level countermeasures of the vulnerabilities that have been listed. The authors have evaluated the CVSS-metric based VACC and the results are promising. Based on this technique, it is worth noting that these propositions can help in the development of stronger computer and network security tools.

An air-gapped network is a type of IT network that is separated from the Internet - physically - due to the sensitive information it stores. Even if such a network is compromised with a malware, the hermetic isolation from the Internet prevents an attacker from leaking out any data - thanks to the lack of connectivity. In this paper we show how attackers can covertly leak sensitive data from air-gapped networks via the row of status LEDs on networking equipment such as LAN switches and routers. Although it is known that some network equipment emanates optical signals correlated with the information being processed by the device (‘side-channel'), malware controlling the status LEDs to carry any type of data (‘covert-channel') has never studied before. Sensitive data can be covertly encoded over the blinking of the LEDs and received by remote cameras and optical sensors. A malicious code is executed in a compromised LAN switch or router allowing the attacker direct, low-level control of the LEDs. We provide the technical background on the internal architecture of switches and routers at both the hardware and software level which enables these attacks. We present different modulation and encoding schemas, along with a transmission protocol. We implement prototypes of the malware and discuss its design and implementation. We tested various receivers including remote cameras, security cameras, smartphone cameras, and optical sensors, and discuss detection and prevention countermeasures. Our experiments show that sensitive data can be covertly leaked via the status LEDs of switches and routers at bit rates of 1 bit/sec to more than 2000 bit/sec per LED.

We introduce a new cybersecurity project named RIVALS. RIVALS will assist in developing network defense strategies through modeling adversarial network attack and defense dynamics. RIVALS will focus on peer-to-peer networks and use coevolutionary algorithms. In this contribution, we describe RIVALS' current suite of coevolutionary algorithms that use archiving to maintain progressive exploration and that support different solution concepts as fitness metrics. We compare and contrast their effectiveness by executing a standard coevolutionary benchmark (Compare-on-one) and RIVALS simulations on 3 different network topologies. Currently, we model denial of service (DOS) attack strategies by the attacker selecting one or more network servers to disable for some duration. Defenders can choose one of three different network routing protocols: shortest path, flooding and a peer-to-peer ring overlay to try to maintain their performance. Attack completion and resource cost minimization serve as attacker objectives. Mission completion and resource cost minimization are the reciprocal defender objectives. Our experiments show that existing algorithms either sacrifice execution speed or forgo the assurance of consistent results. rIPCA, our adaptation of a known coevolutionary algorithm named IPC A, is able to more consistently produce high quality results, albeit without IPCA's guarantees for results with monotonically increasing performance, without sacrificing speed.

Our cybersecurity tool, RIVALS, develops adaptive network defense strategies by modeling adversarial network attack and defense behavior in peer-to-peer networks via coevolutionary algorithms. Currently RIVALS DOS attacks are modestly modeled by the selection of a node that is completely disabled for a resource-limited duration. Defenders have three different network routing protocols. Attack or mission completion and resource cost metrics serve as attacker and defender objectives. This work also includes a description of RIVALS' suite of coevolutionary algorithms that explore archiving as a means of maintaining progressive exploration and support the evaluation of different solution concepts. To compare and contrast the effectiveness of each algorithm, we execute simulations on 3 different network topologies. Our experiments show that it is possible to forgo the assurance of monotonically increasing results and still retain high quality results.

The Controller Area Network (CAN) is a broadcast communications network invented by Robert Bosch GmbH in 1986. CAN is the standard communication network found in automobiles, industry equipment, and many space applications. To be used in these environments, CAN is designed for efficiency and reliability, rather than security. This research paper closely examines the security risks within the CAN protocol and proposes a feasible solution. In this research, we investigate the problems with implementing certain security features in the CAN protocol, such as message authentication and protections against replay and denial-of-service (DoS) attacks. We identify the restrictions of the CAN bus, and we demonstrate how our proposed implementation meets these restrictions. Many previously proposed solutions lack security, feasibility, and/or efficiency; however, a solution must not drastically hinder the real-time operation speed of the network. The solution proposed in this research is tested with a simulative CAN environment. This paper proposes an alteration to the standard CAN bus nodes and the CAN protocol to better protect automobiles and other CAN-related systems from attacks.

Thanks to the occurrence of the Internet of Things (IoT), the devices are able to collect and transmit data via the Internet and contributing to our big data world. It will permit devices to exchange monitoring data content in real time. Real-time communication (RTC) with these devices was analyzed in respect to the Network delay. Network coding (NC) combines data packets and the output packet which is a mixture of the input packets. This technique can provide many potential gains to the network, including reducing Round-Trip Time (RTT), decreasing latency and improving Network delay (ND). In the present paper, the authors improve network delay metrics in the context of the remote management of renewable energy using a random NC with an efficient strategy technique.

Due to the increasing threat of network attacks, Firewall has become crucial elements in network security, and have been widely deployed in most businesses and institutions for securing private networks. The function of a firewall is to examine each packet that passes through it and decide whether to letting them pass or halting them based on preconfigured rules and policies, so firewall now is the first defense line against cyber attacks. However most of people doesn't know how firewall works, and the most users of windows operating system doesn't know how to use the windows embedded firewall. This paper explains how firewall works, firewalls types, and all you need to know about firewall policies, then presents a novel application (QudsWall) developed by authors that manages windows embedded firewall and make it easy to use.

In-vehicle networks like Controller Area Network, FlexRay, Ethernet are now subjected to huge security threats where unauthorized entities can take control of the whole vehicle. This can pose very serious threats including accidents. Security features like encryption, message authentication are getting implemented in vehicle networks to counteract these issues. This paper is proposing a set of novel validation techniques to ensure that vehicle network security is fool proof. Security validation against requirements, security validation using white box approach, black box approach and grey box approaches are put forward. Test system architecture, validation of message authentication, decoding the patterns from vehicle network data, using diagnostics as a security loophole, V2V V2X loopholes, gateway module security testing are considered in detail. Aim of this research paper is to put forward a set of tools and methods for finding and reporting any security loopholes in the in-vehicle network security implementation.

The article issue is the enterprise information protection within the internet of things concept. The aim of research is to develop arrangements set to ensure secure enterprise IPv6 network operating. The object of research is the enterprise IPv6 network. The subject of research is modern switching equipment as a tool to ensure network protection. The research task is to prioritize functioning of switches in production and corporation enterprise networks, to develop a network host protection algorithm, to test the developed algorithm on the Cisco Packet Tracer 7 software emulator. The result of research is the proposed approach to IPv6-network security based on analysis of modern switches functionality, developed and tested enterprise network host protection algorithm under IPv6-protocol with an automated network SLAAC-configuration control, a set of arrangements for resisting default enterprise gateway attacks, using ACL, VLAN, SEND, RA Guard security technology, which allows creating sufficiently high level of networks security.

With the progressive development of network applications and software dependency, we need to discover more advanced methods for protecting our systems. Each industry is equally affected, and regardless of whether we consider the vulnerability of the government or each individual household or company, we have to find a sophisticated and secure way to defend our systems. The starting point is to create a reliable intrusion detection mechanism that will help us to identify the attack at a very early stage; otherwise in the cyber security space the intrusion can affect the system negatively, which can cause enormous consequences and damage the system's privacy, security or financial stability. This paper proposes a concise, and easy to use statistical learning procedure, abbreviated NASCA, which is a four-stage intrusion detection method that can successfully detect unwanted intrusion to our systems. The model is static, but it can be adapted to a dynamic set up.

As one of the security components in cyber situational awareness systems, Intrusion Detection System (IDS) is implemented by many organizations in their networks to address the impact of network attacks. Regardless of the tools and technologies used to generate security alarms, IDS can provide a situation overview of network traffic. With the security alarm data generated, most organizations do not have the right techniques and further analysis to make this alarm data more valuable for the security team to handle attacks and reduce risk to the organization. This paper proposes the IDS Metrics Framework for cyber situational awareness system that includes the latest technologies and techniques that can be used to create valuable metrics for security advisors in making the right decisions. This metrics framework consists of the various tools and techniques used to evaluate the data. The evaluation of the data is then used as a measurement against one or more reference points to produce an outcome that can be very useful for the decision making process of cyber situational awareness system. This metric offers an additional Graphical User Interface (GUI) tools that produces graphical displays and provides a great platform for analysis and decision-making by security teams.

The Distributed Denial of Service (DDoS) attack is a main concern in network security. Since the attackers have developed different techniques and methods, preventing DDoS attacks has become more difficult. Traditional firewall is ineffective in preventing DDoS attacks. In this paper, we propose a new type of firewall named XFirewall to defend against DDoS attacks. XFirewall is a temporary firewall and is created when an attack occurs. Also, XFirewall will be configured with dynamic rules based on real-time traffic analysis. We will discuss in detail the design and algorithm for generating an XFirewall.

Attacks of Ransomware are increasing, this form of malware bypasses many technical solutions by leveraging social engineering methods. This means established methods of perimeter defence need to be supplemented with additional systems. Honeypots are bogus computer resources deployed by network administrators to act as decoy computers and detect any illicit access. This study investigated whether a honeypot folder could be created and monitored for changes. The investigations determined a suitable method to detect changes to this area. This research investigated methods to implement a honeypot to detect ransomware activity, and selected two options, the File Screening service of the Microsoft File Server Resource Manager feature and EventSentry to manipulate the Windows Security logs. The research developed a staged response to attacks to the system along with thresholds when there were triggered. The research ascertained that witness tripwire files offer limited value as there is no way to influence the malware to access the area containing the monitored files.

Security situational awareness is an essential building block in order to estimate security level of systems and to decide how to protect networked systems from cyber attacks. In this extended abstract we envision a model that combines results from security metrics to 3d network visualisation. The purpose is to apply security metrics to gather data from individual hosts. Simultaneously, the whole network is visualised in a 3d format, including network hosts and their connections. The proposed model makes it possible to offer enriched situational awareness for security administrators. This can be achieved by adding information pertaining to individual host into the network level 3d visualisation. Thus, administrator can see connected hosts and how the security of these hosts differs at one glance.

Security is concerned with protecting assets. The aspects of security can be applied to any situation- defense, detection and deterrence. Network security plays important role of protecting information, hardware and software on a computer network. Denial of service (DOS) attacks causes great impacts on the internet world. These attacks attempt to disrupt legitimate user's access to services. By exploiting computer's vulnerabilities, attackers easily consume victim's resources. Many special techniques have been developed to protest against DOS attacks. Some organizations constitute several defense mechanism tools to tackle the security problems. This paper has proposed various types of attacks and solutions associated with each layers of OSI model. These attacks and solutions have different impacts on the different environment. Thus the rapid growth of new technologies may constitute still worse impacts of attacks in the future.

Design-time analysis and verification of distributed real-time embedded systems necessitates the modeling of the time-varying performance of the network and comparing that to application requirements. Earlier work has shown how to build a system network model that abstracted away the network's physical medium and protocols which govern its access and multiplexing. In this work we show how to apply a network medium channel access protocol, such as Time-Division Multiple Access (TDMA), to our network analysis methods and use the results to show that the abstracted model without the explicit model of the protocol is valid.