Biblio

In Cloud Computing Environment, using only static security measures didn't mitigate the attack considerably. Hence, deployment of sophisticated methods by the attackers to understand the network topology of complex network makes the task easier. For this reason, the use of dynamic security measure as virtual machine (VM) migration increases uncertainty to locate a virtual machine in a dynamic attack surface. Although this, not all VM's migration enhances security. Indeed, the destination server to host the VM should be selected precisely in order to avoid externality and attack at the same time. In this paper, we model migration in cloud environment by using continuous Markov Chain. Then, we analyze the probability of a VM to be compromised based on the destination server parameters. Finally, we provide some numerical results to show the effectiveness of our approach in term of avoiding intrusion.

Searchable symmetric encryption (SSE) is an important technique for cloud computing. SSE allows encrypted critical data stored on an untrusted cloud server to be searched using keywords, returning correct data, but the keywords and data content are unknown by the server. However, an SSE database is not practical because the data is generally frequently modified even when stored on a remote server, since the server cannot update the encrypted data without decryption. Dynamic searchable symmetric encryption (DSSE) is designed to support this requirement. DSSE allows adding or deleting encrypted data on the server without decryption. Many DSSE systems have been proposed, based on link-list structures or blind storage (a new primitive). Each has advantages and drawbacks regarding function, extensibility, and efficiency. For a real system, the most important aspect is the tradeoff between performance and security. Therefore, we implemented several DSSE systems to compare their efficiency and security, and identify the various disadvantages with a view to developing an improved system.

Point of Sale (POS) systems has become the technology of choice for most businesses and offering number of advantages over traditional cash registers. They manage staffs, customers, transaction, inventory, sale and labor reporting, price adjustment, as well as keeping track of cash flow, expense management, reducing human errors and more. Whether traditional on-premise POS, or Cloud-Bases POS, they help businesses to run more efficiently. However, despite all these advantages, POS systems are becoming targets of a number of cyber-attacks. Security of a POS system is a key requirement of the Payment Card Industry Data Security Standard (PCI DSS). This paper undertakes research into the PCI DSS and its accompanying standards, in an attempt to break or bypass security measures using varying degrees of vulnerability and penetration attacks in a methodological format. The resounding goal of this experimentation is to achieve a basis from which attacks can be made against a realistic networking environment from whence an intruder can bypass security measures thus exposing a vulnerability in the PCI DSS and potentially exposing confidential customer payment information.

Web applications, as a conventional platform for sensitive data and important transactions, are of great significance to human society. But with its open source framework, the existing security vulnerabilities can easily be exploited by malicious users, especially when web developers fail to follow the secure practices. Here we present a distributed scanning system, FalconEye, with great precision and high performance, it will help prevent potential threats to Web applications. Besides, our system is also capable of covering basically all the web vulnerabilities registered in the Common Vulnerabilities and Exposures (CVE). The FalconEye system is consists of three modules, an input source module, a scanner module and a support platform module. The input module is used to improve the coverage of target server, and other modules make the system capable of generic vulnerabilities scanning. We then experimentally demonstrate this system in some of the most common vulnerabilities test environment. The results proved that the FalconEye system can be a strong contender among the various detection systems in existence today.

The main searching functions realized by searchable encryption can be divided into searching using one query and searching using multiple queries. Searchable encryption using one query has been widely studied and researched; however, few methods of searchable encryption can accommodate search using multiple queries. In addition, most of the method proposed thus far utilize the concept of index search. Therefore, a new problem exists, in which an additional process of updating or deleting an index when new documents are added or removed is required. Hence, the overall computation cost increases. Another problem is that a document that is not registered in the index cannot be searched. Therefore, herein, using a secret-sharing scheme that is known to offer a low computational cost, we propose a method that can realize both logical conjunctive (AND) and logical disjunctive (OR) search over multiple conditions, without the construction of any index. Hence, we can realize direct searching over sentences, thus achieving a more efficient search method.

For future Internet, information-centric networking (ICN) is considered a potential solution to many of its current problems, such as content distribution, mobility, and security. Named Data Networking (NDN) is a more popular ICN project. However, concern regarding the protection of user data persists. Information caching in NDN decouples content and content publishers, which leads to content security threats due to lack of secure controls. Therefore, this paper presents a CP-ABE (ciphertext policy attribute based encryption) access control scheme based on hash table and data segmentation (CHTDS). Based on data segmentation, CHTDS uses a method of linearly splitting fixed data blocks, which effectively improves data management. CHTDS also introduces CP-ABE mechanism and hash table data structure to ensure secure access control and privilege revocation does not need to re-encrypt the published content. The analysis results show that CHTDS can effectively realize the security and fine-grained access control in the NDN environment, and reduce communication overhead for content access.

With the development of modern High-Speed Railway (HSR) and mobile communication systems, network operators have a strong demand to provide high-quality on-board Internet services for HSR passengers. Multi-path TCP (MPTCP) provides a potential solution to aggregate available network bandwidth, greatly overcoming throughout degradation and severe jitter using single transmission path during the high-speed train moving. However, the choose of MPTCP algorithms, i.e., Coupled or Uncoupled, has a great impact on the performance. In this paper, we investigate this interesting issue in the practical datasets along multiple HSR lines. Particularly, we collect the first-hand network datasets and analyze the characteristics and category of traffic flows. Based on this statistics, we measure and analyze the transmission performance for both mice flows and elephant ones with different MPTCP congestion control algorithms in HSR scenarios. The simulation results show that, by comparing with the coupled MPTCP algorithms, i.e., Fully Coupled and LIA, the uncoupled EWTCP algorithm provides more stable throughput and balances congestion window distribution, more suitable for the HSR scenario for elephant flows. This work provides significant reference for the development of on-board devices in HSR network systems.

To prevent unauthorized access to adversaries, strong authentication scheme is a vital security requirement in client-server inter-networking systems. These schemes must verify the legitimacy of such users in real-time environments and establish a dynamic session key fur subsequent communication. Of late, T. H. Chen and J. C. Huang proposed a two-factor authentication framework claiming that the scheme is secure against most of the existing attacks. However we have shown that Chen and Huang scheme have many critical weaknesses in real-time environments. The scheme is prone to man in the middle attack and information leakage attack. Furthermore, the scheme does not provide two essential security services such user anonymity and session key establishment. In this paper, we present an enhanced user participating authenticating scheme which overcomes all the weaknesses of Chen et al.'s scheme and provide most of the essential security features.

The battlefield environment differs from the natural environment in terms of irregular communications and the possibility of destroying communication and medical units by enemy forces. Information that can be collected in a war environment by soldiers is important information and must reach top-level commanders in time for timely decisions making. Also, ambulance staff in the battlefield need to enter the data of injured soldiers after the first aid, so that the information is available for the field hospital staff to prepare the needs for incoming injured soldiers.In this research, we propose two transaction techniques to handle these issues and use different concurrency control protocols, depending on the nature of the transaction and not a one concurrency control protocol for all types of transactions. Message transaction technique is used to collect valuable data from the battlefield by soldiers and allows top-level commanders to view it according to their permissions by logging into the system, to help them make timely decisions. In addition, use the capabilities of DBMS tools to organize data and generate reports, as well as for future analysis. Medical service unit transactional workflow technique is used to provides medical information to the medical authorities about the injured soldiers and their status, which helps them to prepare the required needs before the wounded soldiers arrive at the hospitals. Both techniques handle the disconnection problem during transaction processing.In our approach, the transaction consists of four phases, reading, editing, validation, and writing phases, and its processing is based on the optimistic concurrency control protocol, and the rules of actionability that describe how a transaction behaves if a value-change is occurred on one or more of its attributes during its processing time by other transactions.

Federated learning is a novel distributed learning framework, where the deep learning model is trained in a collaborative manner among thousands of participants. The shares between server and participants are only model parameters, which prevent the server from direct access to the private training data. However, we notice that the federated learning architecture is vulnerable to an active attack from insider participants, called poisoning attack, where the attacker can act as a benign participant in federated learning to upload the poisoned update to the server so that he can easily affect the performance of the global model. In this work, we study and evaluate a poisoning attack in federated learning system based on generative adversarial nets (GAN). That is, an attacker first acts as a benign participant and stealthily trains a GAN to mimic prototypical samples of the other participants' training set which does not belong to the attacker. Then these generated samples will be fully controlled by the attacker to generate the poisoning updates, and the global model will be compromised by the attacker with uploading the scaled poisoning updates to the server. In our evaluation, we show that the attacker in our construction can successfully generate samples of other benign participants using GAN and the global model performs more than 80% accuracy on both poisoning tasks and main tasks.

The real-time map updating enables vehicles to obtain accurate and timely traffic information. Especially for driverless cars, real-time map updating can provide high-precision map service to assist the navigation, which requires vehicles to actively upload the latest road conditions. However, due to the untrusted network environment, it is difficult for the real-time map updating server to evaluate the authenticity of the road information from the vehicles. In order to prevent malicious vehicles from deliberately spreading false information and protect the privacy of vehicles from tracking attacks, this paper proposes a trust-based real-time map updating scheme. In this scheme, the public key is used as the identifier of the vehicle for anonymous communication with conditional anonymity. In addition, the blockchain is applied to provide the existence proof for the public key certificate of the vehicle. At the same time, to avoid the spread of false messages, a trust evaluation algorithm is designed. The fog node can validate the received massages from vehicles using Bayesian Inference Model. Based on the verification results, the road condition information is sent to the real-time map updating server so that the server can update the map in time and prevent the secondary traffic accident. In order to calculate the trust value offset for the vehicle, the fog node generates a rating for each message source vehicle, and finally adds the relevant data to the blockchain. According to the result of security analysis, this scheme can guarantee the anonymity and prevent the Sybil attack. Simulation results show that the proposed scheme is effective and accurate in terms of real-time map updating and trust values calculating.

Advanced Persistent Threat (APT) attack has the characteristics of complex attack means, long duration and great harmfulness. Based on the idea of dynamic deception, the paper proposed an APT defense system framework, and analyzed the deception defense process. The paper proposed a hybrid encryption communication mechanism based on socket, a dynamic IP address generation method based on SM4, a dynamic timing selection method based on Viterbi algorithm and a dynamic policy allocation mechanism based on DHCPv6. Tests show that the defense system can dynamically change and effectively defense APT attacks.

Nowadays database outsourcing has become business owners' preferred option and they are benefiting from its flexibility, reliability, and low cost. However, because database service providers cannot always be fully trusted and data owners will no longer have a direct control over their own data, how to make the outsourced data secure becomes a hot research topic. From the data integrity protection aspect, the client wants to make sure the data returned is correct, complete, and up-to-date. Previous research work in literature put more efforts on data correctness, while data completeness is still a challenging problem to solve. There are some existing works that tried to protect the completeness of data. Unfortunately, these solutions were considered not fully solving the problem because of their high communication or computation overhead. The implementations and limitations of existing works will be further discussed in this paper. From the data confidentiality protection aspect, order-preserving encryption (OPE) is a widely used encryption scheme in protecting data confidentiality. It allows the client to perform range queries and some other operations such as GROUP BY and ORDER BY over the OPE encrypted data. Therefore, it is worthy to develop a solution that allows user to verify the query completeness for an OPE encrypted database so that both data confidentiality and completeness are both protected. Inspired by this motivation, we propose a new data completeness protecting scheme by inserting fake tuples into databases. Both the real and fake tuples are OPE encrypted and thus the cloud server cannot distinguish among them. While our new scheme is much more efficient than all existing approaches, the level of security protection remains the same.

Widespread deployment of centralized clouds has changed the way internet services are developed, deployed and operated. Centralized clouds have substantially extended the market opportunities for online services, enabled new entities to create and operate internet-scale services, and changed the way traditional companies run their operations. However, there are types of services that are unsuitable for today's centralized clouds such as highly interactive virtual and augmented reality (VR/AR) applications, high-resolution gaming, virtualized RAN, mass IoT data processing and industrial robot control. They can be broadly categorized as either latency-sensitive network functions, latency-sensitive applications, and/or high-bandwidth services. What these basic functions have in common is the need for a more distributed cloud infrastructure—an infrastructure we call edge clouds. In this paper, we examine the evolution of clouds, and edge clouds especially, and look at the developing market for edge clouds and what developments are required in networking, hardware and software to support them.

Due to practical constraints in preventing phishing through public network or insecure communication channels, simple physical unclonable function (PDF)-based authentication protocol with unrestricted queries and transparent responses is vulnerable to modeling and replay attacks. In this paper, we present a PUF-based authentication method to mitigate the practical limitations in applications where a resource-rich server authenticates a device with no strong restriction imposed on the type of PUF designs or any additional protection on the binary channel used for the authentication. Our scheme uses an active deception protocol to prevent machine learning (ML) attacks on a device. The monolithic system makes collection of challenge response pairs (CRPs) easy for model building during enrollment but prohibitively time consuming upon device deployment. A genuine server can perform a mutual authentication with the device at any time with a combined fresh challenge contributed by both the server and the device. The message exchanged in clear does not expose the authentic CRPs. The false PUF multiplexing is fortified against prediction of waiting time by doubling the time penalty for every unsuccessful authentication.

A semi-quantum key distribution (SQKD) protocol allows two users A and B to establish a shared secret key that is secure against an all-powerful adversary E even when one of the users (e.g., B) is semi-quantum or classical in nature while the other is fully-quantum. A mediated SQKD protocol allows two semi-quantum users to establish a key with the help of an adversarial quantum server. We introduce the concept of a multi-mediated SQKD protocol where two (or more) adversarial quantum servers are used. We construct a new protocol in this model and show how it can withstand high levels of quantum noise, though at a cost to efficiency. We perform an information theoretic security analysis and, along the way, prove a general security result applicable to arbitrary MM-SQKD protocols. Finally, a comparison is made to previous (S)QKD protocols.

We present a security analysis of several gesture CAPTCHA challenges designed to operate on mobiles. Mobile gesture CAPTCHA challenges utilize the accelerometer and the gyroscope inputs from a mobile to allow a human to solve a simple test by physically manipulating the device. We have evaluated the security of gesture CAPTCHA in mobile devices and found them resistant to a range of common automated attacks. Our study has shown that using an accelerometer and the gyroscope readings as an input to solve the CAPTCHA is difficult for malware, but easy for a real user. Gesture CAPTCHA is effective in differentiating between humans and machines.

This paper reports the definition, setup and obtained results of the Fed4FIRE + medium experiment ERASER, aimed to evaluate the actual Quality of Service (QoS) guarantees that the clean-slate Recursive InterNetwork Architecture (RINA) can deliver to heterogeneous applications at large-scale. To this goal, a 37-Node 5G metro/regional RINA network scenario, spanning from the end-user to the server where applications run in a datacenter has been configured in the Virtual Wall experimentation facility. This scenario has initially been loaded with synthetic application traffic flows, with diverse QoS requirements, thus reproducing different network load conditions. Next,their experienced QoS metrics end-to-end have been measured with two different QTA-Mux (i.e., the most accepted candidate scheduling policy for providing RINA with its QoS support) deployment scenarios. Moreover, on this RINA network scenario loaded with synthetic application traffic flows, a real HD (1080p) video streaming demonstration has also been conducted, setting up video streaming sessions to end-users at different network locations, illustrating the perceived Quality of Experience (QoE). Obtained results in ERASER disclose that, by appropriately deploying and configuring QTA-Mux, RINA can yield effective QoS support, which has provided perfect QoE in almost all locations in our demo when assigning video traffic flows the highest (i.e., Gold) QoS Cube.

This paper provides hardware-independent authentication named as Intelligent Authentication Scheme, which rectifies the design weaknesses that may be exploited by various security attacks. The Intelligent Authentication Scheme protects against various types of security attacks such as password-guessing attack, replay attack, streaming bots attack (denial of service), keylogger, screenlogger and phishing attack. Besides reducing the overall cost, it also balances both security and usability. It is a unique authentication scheme.

Nowadays one-time passwords are used in a lot of areas of information technologies including e-commerce. A few vulnerabilities in authentication protocols based on one-time passwords are widely known. In current work, we analyze authentication protocols based on one-time passwords and their vulnerabilities. Both simple and complicated protocols which are implementing cryptographic algorithms are reviewed. For example, an analysis of relatively old Lamport's hash-chain protocol is provided. At the same time, we examine HOTP and TOTP protocols which are actively used nowadays. The main result of the work are conclusions about the security of reviewed protocols based on one-time passwords.

We propose an efficient and secure two-server password-only remote user authentication protocol for consumer electronic devices, such as smartphones and laptops. Our protocol works on-top of any existing trust model, like Secure Sockets Layer protocol (SSL). The proposed protocol is secure against dictionary and impersonation attacks.

Denial-of-Service attack (DoS attack) is an attack on network in which an attacker tries to disrupt the availability of network resources by overwhelming the target network with attack packets. In DoS attack it is typically done using a single source, and in a Distributed Denial-of-Service attack (DDoS attack), like the name suggests, multiple sources are used to flood the incoming traffic of victim. Typically, such attacks use vulnerabilities of Domain Name System (DNS) protocol and IP spoofing to disrupt the normal functioning of service provider or Internet user. The attacks involving DNS, or attacks exploiting vulnerabilities of DNS are known as DNS based DDOS attacks. Many of the proposed DNS based DDoS solutions try to prevent/mitigate such attacks using some intelligent non-``network layer'' (typically application layer) protocols. Utilizing the flexibility and programmability aspects of Software Defined Networks (SDN), via this proposed doctoral research it is intended to make underlying network intelligent enough so as to prevent DNS based DDoS attacks.

The greatest threat towards securing the organization and its assets are no longer the attackers attacking beyond the network walls of the organization but the insiders present within the organization with malicious intent. Existing approaches helps to monitor, detect and prevent any malicious activities within an organization's network while ignoring the human behavior impact on security. In this paper we have focused on user behavior profiling approach to monitor and analyze user behavior action sequence to detect insider threats. We present an ensemble hybrid machine learning approach using Multi State Long Short Term Memory (MSLSTM) and Convolution Neural Networks (CNN) based time series anomaly detection to detect the additive outliers in the behavior patterns based on their spatial-temporal behavior features. We find that using Multistate LSTM is better than basic single state LSTM. The proposed method with Multistate LSTM can successfully detect the insider threats providing the AUC of 0.9042 on train data and AUC of 0.9047 on test data when trained with publically available dataset for insider threats.

Recently, the novel networking technology Software-Defined Networking(SDN) and Service Function Chaining(SFC) are rapidly growing, and security issues are also emerging for SDN and SFC. However, the research about security and safety on a novel networking environment is still unsatisfactory, and the vulnerabilities have been revealed continuously. Among these security issues, this paper addresses the ARP Poisoning attack to exploit SFC vulnerability, and proposes a method to defend the attack. The proposed method recognizes the repetitive ARP reply which is a feature of ARP Poisoning attack, and detects ARP Poisoning attack. The proposed method overcomes the limitations of the existing detection methods. The proposed method also detects the presence of an attack more accurately.

With the growing use of the Robot Operating System (ROS), it can be argued that it has become a de-facto framework for developing robotic solutions. ROS is used to build robotic applications for industrial automation, home automation, medical and even automatic robotic surveillance. However, whenever ROS is utilized, security is one of the main concerns that needs to be addressed in order to ensure a secure network communication of robots. Cyber-attacks may hinder evolution and adaptation of most ROS-enabled robotic systems for real-world use over the Internet. Thus, it is important to address and prevent security threats associated with the use of ROS-enabled applications. In this paper, we propose a novel approach for securing ROS-enabled robotic system by integrating ROS with the Message Queuing Telemetry Transport (MQTT) protocol. We manage to secure robots' network communications by providing authentication and data encryption, therefore preventing man-in-the-middle and hijacking attacks. We also perform real-world experiments to assess how the performance of a ROS-enabled robotic surveillance system is affected by the proposed approach.