Biblio

Software Defined Network (SDN) is a new type of network architecture solution, and its innovation lies in decoupling traditional network system into a control plane, a data plane, and an application plane. It logically implements centralized control and management of the network, and SDN is considered to represent the development trend of the network in the future. However, SDN still faces many security challenges. Currently, the number of insecure devices is huge. Distributed Denial of Service (DDoS) attacks are one of the major network security threats.This paper focuses on the detection and mitigation of DDoS attacks in SDN. Firstly, we explore a solution to detect DDoS using Renyi entropy, and we use exponentially weighted moving average algorithm to set a dynamic threshold to adapt to changes of the network. Second, to mitigate this threat, we analyze the historical behavior of each source IP address and score it to determine the malicious source IP address, and use OpenFlow protocol to block attack source.The experimental results show that the scheme studied in this paper can effectively detect and mitigate DDoS attacks.

Research on the design of data center infrastructure is increasing, both from academia and industry, due to the rapid development of cloud-based applications such as search engines, social networks, and large-scale computing. On a large scale, data centers can consist of hundreds to thousands of servers that require systems with high-performance requirements and low downtime. To meet the network's needs in a dynamic data center, infrastructure of applications and services are growing. It takes a process of designing a network topology so that it can guarantee availability and security. One way to surmount this is by implementing the zero trust security model based on micro-segmentation. Zero trust is a security idea based on the principle of "never trust, always verify" in which no concepts of trust and untrust in network traffic. The zero trust security model implemented network traffic in the form of untrust. Micro-segmentation is a way to achieve zero trust by dividing a network into smaller logical segments to restrict the traffic. In this research, data center network performance based on software-defined networking with zero trust security model using micro-segmentation has been evaluated using a testbed simulation of Cisco Application Centric Infrastructure by measuring the round trip time, jitter, and packet loss during experiments. Performance evaluation results show that micro-segmentation adds an average round trip time of 4 μs and jitter of 11 μs without packet loss so that the security can be improved without significantly affecting network performance on the data center.

Security services and share information is provided by the computer network. The computer network is by default there is not security. The Attackers can use this provision to hack and steal private information. Confidentiality, creation, changes, and truthful of data is will be big problems in the network. Many types of research have given many methods regarding this, from these methods Generating Initial Chromosome Key called Generating Dynamic Chromosome Key (GDCK), which is a novel approach. With the help of the RSA (Rivest Shamir Adleman) algorithm, GICK and GDCK have created an initial key. The proposed method has produced new techniques using genetic fitness function for the sender and receiver. The outcome of GICK and GDCK has been verified by NIST (National Institute of Standards Technology) tools and analyzes randomness of auto-generated keys with various methods. The proposed system has involved three examines; it has been yield better P-Values 6.44, 7.05, and 8.05 while comparing existing methods.

Wireless Sensor Networks (WSNs) are applied in environmental monitoring, military surveillance, etc., whereas these applications focuses on providing security for sensed data and the nodes are available for a long time. Hence, we propose DEAVD protocol for secure data exchange with limited usage of energy. The DEAVD protocol compresses data to reduces the energy consumption and implements an energy efficient encryption and decryption technique using voronoi diagram paradigm. Thus, there is an improvement in the proposed protocol with respect to security due to the concept adapted during data encryption and aggregation.

Substantial empirical evidence, including the success of synthetic graph generation models as well as of analytical methodologies, suggests that large, real graphs have a recursive community structure. The latter results, in part at least, in other important properties of these graphs such as low diameter, high clustering coefficient values, heavy degree distribution tail, and clustered graph spectrum. Notice that this structure need not be official or moderated like Facebook groups, but it can also take an ad hoc and unofficial form depending on the functionality of the social network under study as for instance the follow relationship on Twitter or the connections between news aggregators on Reddit. Community discovery is paramount in numerous applications such as political campaigns, digital marketing, crowdfunding, and fact checking. Here a tensor representation for Twitter subgraphs is proposed which takes into consideration both the followfollower relationships but also the coherency in hashtags. Community structure discovery then reduces to the computation of Tucker tensor decomposition, a higher order counterpart of the well-known unsupervised learning method of singular value decomposition (SVD). Tucker decomposition clearly outperforms the SVD in terms of finding a more compact community size distribution in experiments done in Julia on a Twitter subgraph. This can be attributed to the facts that the proposed methodology combines both structural and functional Twitter elements and that hashtags carry an increased semantic weight in comparison to ordinary tweets.

Eddy Current Pulsed Thermography (ECPT) is widely used in Nondestructive Testing (NDT) of metal defects where the defect information is sometimes affected by coil noise and edge noise, therefore, it is necessary to segment the ECPT image sequences to improve the detection effect, that is, segmenting the defect part from the background. At present, the methods widely used in ECPT are mostly based on matrix decomposition theory. In fact, tensor decomposition is a new hotspot in the field of image segmentation and has been widely used in many image segmentation scenes, but it is not a general method in ECPT. This paper analyzes the feasibility of the usage of tensor decomposition in ECPT and designs several experiments on different samples to verify the effects of two popular tensor decomposition algorithms in ECPT. This paper also compares the matrix decomposition methods and the tensor decomposition methods in terms of treatment effect, time cost, detection success rate, etc. Through the experimental results, this paper points out the advantages and disadvantages of tensor decomposition methods in ECPT and analyzes the suitable engineering application scenarios of tensor decomposition in ECPT.

Considering the amount of time we spend on the internet, web pages have evolved over a period of time with rapid progression and momentum. With such advancement, we find ourselves fronting a few hostile ideologies, breaching the security levels of webpages as such. The most hazardous of them all is XSS, known as Cross-Site Scripting, is one of the attacks which frequently occur in website-based applications. Cross-Site Scripting (XSS) attacks happen when malicious data enters a web application through an untrusted source. The spam attacks happen in the form of Wall posts, News feed, Message spam and mostly when a user is open to download content of webpages. This paper investigates the use of machine learning to build classifiers to allow the detection of XSS. Establishing our approach, we target the detection modus operandi of XSS attack via two features: URLs and JavaScript. To predict the level of XSS threat, we will be using four machine learning algorithms (SVM, KNN, Random forest and Logistic Regression). Proposing these classified algorithms, webpages will be branded as malicious or benign. After assessing and calculating the dataset features, we concluded that the Random Forest Classifier performed most accurately with the lowest False Positive Rate of 0.34. This precision will ensure a method much efficient to evaluate threatening XSS for the smooth functioning of the system.

Cross-Site Scripting, also called as XSS, is a type of injection where malicious scripts are injected into trusted websites. When malicious code, usually in the form of browser side script, is injected using a web application to a different end user, an XSS attack is said to have taken place. Flaws which allows success to this attack is remarkably widespread and occurs anywhere a web application handles the user input without validating or encoding it. A study carried out by Symantic states that more than 50% of the websites are vulnerable to the XSS attack. Security engineers of Microsoft coined the term "Cross-Site Scripting" in January of the year 2000. But even if was coined in the year 2000, XSS vulnerabilities have been reported and exploited since the beginning of 1990's, whose prey have been all the (then) tech-giants such as Twitter, Myspace, Orkut, Facebook and YouTube. Hence the name "Cross-Site" Scripting. This attack could be combined with other attacks such as phishing attack to make it more lethal but it usually isn't necessary, since it is already extremely difficult to deal with from a user perspective because in many cases it looks very legitimate as it's leveraging attacks against our banks, our shopping websites and not some fake malicious website.

Cryptocurrencies are the digital currencies designed to replace the regular cash money while taking place in our daily lives especially for the last couple of years. Mining cryptocurrencies are one of the popular ways to have them and make a profit due to unstable values in the market. This attracts attackers to utilize malware on internet users' computer resources, also known as cryptojacking, to mine cryptocurrencies. Cryptojacking started to be a major issue in the internet world. In this case, we developed MiNo, a web browser add-on application to detect these malicious mining activities running without the user's permission or knowledge. This add-on provides security and efficiency for the computer resources of the internet users. MiNo designed and developed with double-layer protection which makes it ahead of its competitors in the market.

Although it has been demonstrated in multiple studies that serious data leaks could occur to many-core systems thanks to the existence of the thermal covert channels (TCC), little has been done to produce effective countermeasures that are necessary to fight against such TCC attacks. In this paper, we propose a three-step countermeasure to address this critical defense issue. Specifically, the countermeasure includes detection based on signal frequency scanning, positioning affected cores, and blocking based on Dynamic Voltage Frequency Scaling (DVFS) technique. Our experiments have confirmed that on average 98% of the TCC attacks can be detected, and with the proposed defense, the bit error rate of a TCC attack can soar to 92%, literally shutting down the attack in practical terms. The performance penalty caused by the inclusion of the proposed countermeasures is only 3% for an 8×8 system.

Field-Programmable Gate Arrays (FPGAs) are versatile, reconfigurable integrated circuits that can be used as hardware accelerators to process highly-sensitive data. Leaking this data and associated cryptographic keys, however, can undermine a system's security. To prevent potentially unintentional interactions that could break separation of privilege between different data center tenants, FPGAs in cloud environments are currently dedicated on a per-user basis. Nevertheless, while the FPGAs themselves are not shared among different users, other parts of the data center infrastructure are. This paper specifically shows for the first time that powering FPGAs, CPUs, and GPUs through the same power supply unit (PSU) can be exploited in FPGA-to-FPGA, CPU-to-FPGA, and GPU-to-FPGA covert channels between independent boards. These covert channels can operate remotely, without the need for physical access to, or modifications of, the boards. To demonstrate the attacks, this paper uses a novel combination of "sensing" and "stressing" ring oscillators as receivers on the sink FPGA. Further, ring oscillators are used as transmitters on the source FPGA. The transmitting and receiving circuits are used to determine the presence of the leakage on off-the-shelf Xilinx boards containing Artix 7 and Kintex 7 FPGA chips. Experiments are conducted with PSUs by two vendors, as well as CPUs and GPUs of different generations. Moreover, different sizes and types of ring oscillators are also tested. In addition, this work discusses potential countermeasures to mitigate the impact of the cross-board leakage. The results of this paper highlight the dangers of shared power supply units in local and cloud FPGAs, and therefore a fundamental need to re-think FPGA security for shared infrastructures.

To build the fifth generation (5G) mobile network, the sharing structure in the 5G network adopted in industries has gained great research interesting. However, in this structure data are shared among diversity networks, which introduces the threaten of network security, such as covert timing channels. To eliminate the covert timing channel, we propose to inject noise into the covert timing channel. By analyzing the modulation method of covert timing channels, we design the jamming strategy on the covert channel. According to the strategy, the interference algorithm of the covert timing channel is designed. Since the interference algorithm depends heavily on the memory, we construct a distributing jammer. Experiments results show that these covert time channel can be blocked under the distributing jammer.

One of the emerging methodologies nowadays in the field of cryptography based on human DNA sequences. As the research says that even a limited quantity of DNA can store gigantic measure of information likewise DNA can process and transmit the information, such potential of DNA give rise to the idea of DNA cryptography. A synopsis of the research carried out in DNA based security presented in this paper. Included deliberation contain encryption algorithms based on random DNA, chaotic systems, polymerase chain reaction, coupled map lattices, and other common encryption algorithms. Purpose of algorithms are specific or general as some of them are only designed to encrypt the images or more specific images like medical images or text data and others designed to use it as general for images and text data. We discussed divergent techniques that proposed earlier based on random sample DNA, medical image encryption, image encryption, and cryptanalysis done on various algorithms. With the help of this paper, one can understand the existing algorithms and can design a DNA based encryption algorithm.

Hiding information is a process to hide data or include it in different digital media such as image, audio, video, and text. However, there are many techniques to achieve the process of hiding information in the image processing, in this paper, a new method has been proposed for hidden data mechanism (which is a text file), then a transposition cipher method has been employed for encryption completed. It can be used to build an encrypted text and also to increase security against possible attacks while sending it over the World Wide Web. A genetic algorithm has been affected in the adjustment of the encoded text and DNA in the creation of an encrypted text that is difficult to detect and then include in the image and that affected the image visual quality. The proposed method outperforms the state of arts in terms of efficiently retrieving the embedded messages. Performance evaluation has been recorded high visual quality scores for the (SNR (single to noise ratio), PSNR (peak single to noise ratio) and MSE (mean square error).

The intensity of DNA figuring will reinforce the current security on frameworks by opening up another probability of a half and half cryptographic framework. Here, we are exhibiting the DNA S-box for actualizing cryptographic algorithm. The DNA based S-Box is designed using vivado software and implemented using Artix-7 device. The main aim is to design the DNA based S-box to increase the security. Also pipelining and parallelism techniques are to be implement in future to increase the speed.

Cryptography is the method of transforming the original texted message into an unknown form and in reverse also. It is the process of hiding and forwarding the data in an appropriate form so that only authorized persons can know and can process it. Cryptographic process secures the data from hijacking or transmutation, it is mainly used for users data security. This paper justifies the encryption and decryption using DNA(Deoxyribo Nucleic Acid) sequence. This process includes several intermediate steps, the perception of binary-coded form and generating of arbitrary keys is used to encrypt the message. A common key should be established between the sender and receiver for encryption and decryption process. The common key provides more security to the sequence. In this paper, both the process of binary-coded form and generating of arbitrary keys are used to encrypt the message. It is widely used in an institution and by every individual to hide their data from the muggers and hijackers and provides the data securely, and confidentially over the transmission of information.

This paper presents an overhead analysis of the use of digital signature mechanisms in the Message Queue Telemetry Transport (MQTT) protocol for three classes of constrained-device. Because the resources provided by constrained-devices are very limited, the purpose of this overhead analysis is to help find out the advantages and disadvantages of each class of constrained-devices after a security mechanism has been applied, namely by applying a digital signature mechanism. The objective of using this digital signature mechanism is for providing integrity, that if the payload sent and received in its destination is still original and not changed during the transmission process. The overhead analysis aspects performed are including analyzing decryption time, signature verification performance, message delivery time, memory and flash usage in the three classes of constrained-device. Based on the overhead analysis result, it can be seen that for decryption time and signature verification performance, the Class-2 device is the fastest one. For message delivery time, the smallest time needed for receiving the payload is Class-l device. For memory usage, the Class-2 device is providing the biggest available memory and flash.

The exchange of data has expanded utilizing the web nowadays, but it is not dependable because, during communication on the cloud, any malicious client can alter or steal the information or misuse it. To provide security to the data during transmission is becoming hot research and quite challenging topic. In this work, our proposed algorithm enhances the security of the keys by increasing its complexity, so that it can't be guessed, breached or stolen by the third party and hence by this, the data will be concealed while sending between the users. The proposed algorithm also provides more security and authentication to the users during cloud communication, as compared to the previously existing algorithm.

We all are living in the digital era, where the maximum of the information is available online. The digital world has made the transfer of information easy and provides the basic needs of security like authentication, integrity, nonrepudiation, etc. But, with the improvement in security, cyber-attacks have also increased. Security researchers have provided many techniques to prevent these cyber-attacks; one is a Digital Signature (DS). The digital signature uses cryptographic key pairs (public and private) to provide the message's integrity and verify the sender's identity. The private key used in the digital signature is confidential; if attackers find it by using various techniques, then this can result in an attack. This paper presents a brief introduction about the digital signature and how it is vulnerable to a man-in-the-middle attack. Further, it discusses a technique to prevent this attack in the digital signature.

the purpose of this paper is investigation of existing approaches to formation of electronic digital signatures, as well as the possibility of software developing for electronic signature generation at electronic document circulation of institution. The article considers and analyzes the existing algorithms for generating and processing electronic signatures. Authors propose the model for documented information exchanging in institution, including cryptographic module and secure key storage, blockchain storage of electronic signatures, central web-server and web-interface. Examples of the developed software are demonstrated, and recommendations are given for its implementation, integration and using in different institutions.

Developing mission-centric impact assessment techniques to address cyber resiliency in the cyber-physical systems (CPSs) requires integrating system inter-dependencies to the risk and resilience analysis process. Generally, network administrators utilize attack graphs to estimate possible consequences in a networked environment. Attack graphs lack to incorporate the operations-specific dependencies. Localizing the dependencies among operational missions, tasks, and the hosting devices in a large-scale CPS is also challenging. In this work, we offer a graphical modeling technique to integrate the mission-centric impact assessment of cyberattacks by relating the effect to the operational resiliency by utilizing a combination of the logical attack graph and mission impact propagation graph. We propose formal techniques to compute cyberattacks’ impact on the operational mission and offer an optimization process to minimize the same, having budgetary restrictions. We also relate the effect to the system functional operability. We illustrate our modeling techniques using a SCADA (supervisory control and data acquisition) case study for the cyber-physical power systems. We believe our proposed method would help evaluate and minimize the impact of cyber attacks on CPS’s operational missions and, thus, enhance cyber resiliency.

In 2018, several malware campaigns targeted and succeed to infect millions of low-cost routers (malwares e.g., VPN-Filter, Navidade, and SonarDNS). These routers were used, then, for all sort of cybercrimes: from DDoS attacks to ransomware. MikroTik routers are a peculiar example of low-cost routers. These routers are used to provide both last mile access to home users and are used in core network infrastructure. Half of the core routers used in one of the biggest Internet exchanges in the world are MikroTik devices. The problem is that vulnerable firmwares (RouterOS) used in homeusers houses are also used in core networks. In this paper, we are the first to quantify the problem that infecting MikroTik devices would pose to the Internet. Based on more than 4 TB of data, we reveal more than 4 million MikroTik devices in the world. Then, we propose an easy-to-deploy MikroTik honeypot and collect more than 17 millions packets, in 45 days, from sensors deployed in Australia, Brazil, China, India, Netherlands, and the United States. Finally, we use the collected data from our honeypots to automatically classify and assess attacks tailored to MikroTik devices. All our source-codes and analysis are publicly available. We believe that our honeypots and our findings in this paper foster security improvements in MikroTik devices worldwide.

Cloud computing provides so many groundbreaking advantages over native computing servers like to improve capacity and decrease costs, but meanwhile, it carries many security issues also. In this paper, we find the feasible security attacks made about cloud computing, including Wrapping, Browser Malware-Injection and Flooding attacks, and also problems caused by accountability checking. We have also analyzed the honey pot attack and its procedural intrusion way into the system. This paper on overall deals with the most common security breaches in cloud computing and finally honey pot, in particular, to analyze its intrusion way. Our major scope is to do overall security, analyze in the cloud and then to take up with a particular attack to deal with granular level. Honey pot is the one such attack that is taken into account and its intrusion policies are analyzed. The specific honey pot algorithm is in the queue as the extension of this project in the future.

Unilateral spatial neglect (USN) is a higher cognitive dysfunction that can occur after a stroke. It is defined as an impairment in finding, reporting, reacting to, and directing stimuli opposite the damaged side of the brain. We have proposed a system to identify neglected regions in USN patients in three dimensions using three-dimensional virtual reality. The objectives of this study are twofold: first, to propose a system for numerically identifying the neglected regions using an object detection task in a virtual space, and second, to compare the neglected regions during object detection when the patient's neck is immobilized (‘fixed-neck’ condition) versus when the neck can be freely moved to search (‘free-neck’ condition). We performed the test using an immersive virtual reality system, once with the patient's neck fixed and once with the patient's neck free to move. Comparing the results of the study in two patients, we found that the neglected areas were similar in the fixed-neck condition. However, in the free-neck condition, one patient's neglect improved while the other patient’s neglect worsened. These results suggest that exploratory ability affects the symptoms of USN and is crucial for clinical evaluation of USN patients.

This paper investigates the effects of real time visual biofeedback for improving sports performance using a large scale immersive mixed reality system in which users are able to play a simulated game of curling. The users slide custom curling stones across the floor onto a projected target whose size is dictated by the user’s stress-related physiological measure; heart rate (HR). The higher HR the player has, the smaller the target will be, and vice-versa. In the experiment participants were asked to compete in three different conditions: baseline, with and without the proposed biofeedback. The results show that when providing a visual representation of the player’s HR or "choking" in competition, it helped the player understand their condition and improve competition performance (P-value of 0.0391).