Biblio

Now-a-days vehicular information network technology is receiving a lot of attention due to its practical as well as safety related applications. By using this technology, participating vehicles can communicate among themselves on the road in order to obtain any interested data or emergency information. In Vehicular Ad-Hoc Network (VANET), due to the fast speed of the vehicles, the traditional host centric approach (i.e. TCP/IP) fails to provide efficient and robust communication between large number of vehicles. Therefore, Named Data Network (NDN) newly proposed Internet architecture is applied in VANET, named as VNDN. In which, the vehicles can communicate with the help of content name rather than vehicle address. In this paper, we explored the concepts and identify the main packet forwarding issues in VNDN. Furthermore, we proposed a protocol, named Control of Useless Interests Flooding (CUIF) in Vehicular Named Data Network. In which, it provides the best and efficient communication environment to users while driving on the highway. CUIF scheme reduces the Interest forwarding storm over the network and control the flooding of useless packets against the direction of a Producer vehicle. Our simulation results show that CUIF scheme decreases the number of outgoing Interest packets as well as data download time in the network.

Due to users' network flow requirement and usage amount nowadays, TCP/IP networks may face various problems. For one, users of video services may access simultaneously the same content, which leads to the host incurring extra costs. Second, although nearby nodes may have the file that a user wants to access, the user cannot directly verify the file itself. This issue will lead the user to connect to a remote host rather than the nearby nodes and causes the network traffic to greatly increase. Therefore, the named data network (NDN), which is based on data itself, was brought about to deal with the aforementioned problems. In NDN, all users can access a file from the nearby nodes, and they can directly verify the file themselves rather than the specific host who holds the file. However, NDN still has no complete standard and secure file transfer protocol to support the ciphertext transmission and the problem of the unknown potential receivers. The straightforward solution is that a sender uses the receiver's public key to encrypt a file before she/he sends the file to NDN nodes. However, it will limit the behavior of users and incur significant storage costs of NDN nodes. This paper presents a complete secure file transfer protocol, which combines the data re-encryption, satisfies the requirement of secure ciphertext transmission, solves the problem of the unknown potential receivers, and saves the significant storage costs of NDN nodes. The proposed protocol is the first one that achieves data confidentiality and solves the problem of the unknown potential receivers in NDN. Finally, we also provide formal security models and proofs for the proposed FTP-NDN.

We consider a cloud based multiserver system consisting of a set of replica application servers behind a set of proxy (indirection) servers which interact directly with clients over the Internet. We study a proactive moving-target defense to thwart a DDoS attacker's reconnaissance phase and consequently reduce the attack's impact. The defense is effectively a moving-target (motag) technique in which the proxies dynamically change. The system is evaluated using an AWS prototype of HTTP redirection and by numerical evaluations of an “adversarial” coupon-collector mathematical model, the latter allowing larger-scale extrapolations.

Moving target defense (MTD) is becoming popular with the advancements in Software Defined Networking (SDN) technologies. With centralized management through SDN, changing the network attributes such as routes to escape from attacks is simple and fast. Yet, the available alternate routes are bounded by the network topology, and a persistent attacker that continuously perform the reconnaissance can extract the whole link-map of the network. To address this issue, we propose to use virtual shadow networks (VSNs) by applying Network Function Virtualization (NFV) abilities to the network in order to deceive attacker with the fake topology information and not reveal the actual network topology and characteristics. We design this approach under a formal framework for Internet Service Provider (ISP) networks and apply it to the recently emerged indirect DDoS attacks, namely Crossfire, for evaluation. The results show that attacker spends more time to figure out the network behavior while the costs on the defender and network operations are negligible until reaching a certain network size.

Traditional address scanning attacks mainly rely on the naive 'brute forcing' approach, where the entire IPv4 address space is exhaustively searched by enumerating different possibilities. However, such an approach is inefficient for IPv6 due to its vast subnet size (i.e., 264). As a result, it is widely assumed that address scanning attacks are less feasible in IPv6 networks. In this paper, we evaluate new IPv6 reconnaissance techniques in real IPv6 networks and expose how to leverage the Domain Name System (DNS) for IPv6 network reconnaissance. We collected IPv6 addresses from 5 regions and 100,000 domains by exploiting DNS reverse zone and DNSSEC records. We propose a DNS Guard (DNSG) to efficiently detect DNS reconnaissance attacks in IPv6 networks. DNSG is a plug and play component that could be added to the existing infrastructure. We implement DNSG using Bro and Suricata. Our results demonstrate that DNSG could effectively block DNS reconnaissance attacks.

Moving target defense (MTD) is a proactive defense mechanism of changing the attack surface to increase an attacker's confusion and/or uncertainty, which invalidates its intelligence gained through reconnaissance and/or network scanning attacks. In this work, we propose software-defined networking (SDN)-based MTD technique using the shuffling of IP addresses and port numbers aiming to obfuscate both network and transport layers' real identities of the host and the service for defending against the network reconnaissance and scanning attacks. We call our proposed MTD technique Random Host and Service Multiplexing, namely RHSM. RHSM allows each host to use random, multiple virtual IP addresses to be dynamically and periodically shuffled. In addition, it uses short-lived, multiple virtual port numbers for an active service running on the host. Our proposed RHSM is novel in that we employ multiplexing (or de-multiplexing) to dynamically change and remap from all the virtual IPs of the host to the real IP or the virtual ports of the services to the real port, respectively. Via extensive simulation experiments, we prove how effectively and efficiently RHSM outperforms a baseline counterpart (i.e., a static network without RHSM) in terms of the attack success probability and defense cost.

Now a day, Wireless Sensor Networks are widely used in military applications by its applications, it is extended to healthcare, industrial environments and many more. As we know that, there are some unique features of WSNs such as limited power supply, minimum bandwidth and limited energy. So, to secure traditional network, multiple techniques are available, but we can't use same techniques to secure WSNs. So to increase the overall security of WSNs, we required new ideas as well as new approaches. In general, intrusion prevention is the primary issue in WSNs and intrusion detection already reached to saturation. Thus, we need an efficient solution for proactive intrusion prevention towards WSNs. Thus, formal validation of protocols in WSN is an essential area of research. This research paper aims to formally verify as well as model some protocol used for intrusion detection using AVISPA tool and HLPSL language. In this research paper, the results of authentication and DoS attacks were detected is presented, but there is a need to prevent such type of attacks. In this research paper, a system is proposed in order to avoid intrusion using machine learning for the wireless sensor network. So, the proposed system will be used for intrusion prevention in a wireless sensor network.

The rapid development of the Cloud Computing Technologies (CCTs) has amended the conventional design of resource-constrained Network Control System (NCS) to the powerful and flexible design of Cloud-Based Networked Control System (CB-NCS) by relocating the processing part to the cloud server. This arrangement has produced many internets based exquisite applications. However, this new arrangement has also raised many network security challenges for the cloud-based control system related to cyber-physical part of the system. In the absence of robust verification methodology, an attacker can launch the modification attack in order to destabilize or take control of NCS. It is desirable that there shall be a solution authentication methodology used to verify whether the incoming solutions are coming from the cloud or not. This paper proposes a methodology used for the verification of the receiving solution to the local control system from the cloud using Karush-Kuhn-Tucker (KKT) conditions, which is then applied to actuator after verification and thus ensure the stability in case of modification attack.

Industrial Internet of Things (IIoT) is a fusion of industrial automation systems and IoT systems. It features comprehensive sensing, interconnected transmission, intelligent processing, self-organization and self-maintenance. Its applications span intelligent transportation, smart factories, and intelligence. Many areas such as power grid and intelligent environment detection. With the widespread application of IIoT technology, the cyber security threats to industrial IoT systems are increasing day by day, and information security issues have become a major challenge in the development process. In order to protect the industrial IoT system from network attacks, this paper aims to study the industrial IoT information security protection technology, and the typical architecture of industrial Internet of things system, and analyzes the network security threats faced by industrial Internet of things system according to the different levels of the architecture, and designs the security protection strategies applied to different levels of structures based on the specific means of network attack.

With spatial crowdsourcing (SC), requesters outsource their spatiotemporal tasks (tasks associated with location and time) to a set of workers, who will perform the tasks by physically traveling to the tasks' locations. However, current solutions require the locations of the workers and/or the tasks to be disclosed to untrusted parties (SC server) for effective assignments of tasks to workers. In this paper we propose a framework for assigning tasks to workers in an online manner without compromising the location privacy of workers and tasks. We perturb the locations of both tasks and workers based on geo-indistinguishability and then devise techniques to quantify the probability of reachability between a task and a worker, given their perturbed locations. We investigate both analytical and empirical models for quantifying the worker-task pair reachability and propose task assignment strategies that strike a balance among various metrics such as the number of completed tasks, worker travel distance and system overhead. Extensive experiments on real-world datasets show that our proposed techniques result in minimal disclosure of task locations and no disclosure of worker locations without significantly sacrificing the total number of assigned tasks.

With spatial crowdsourcing (SC), requesters outsource their spatiotemporal tasks (tasks associated with location and time) to a set of workers, who will perform the tasks by physically traveling to the tasks' locations. However, current solutions require the locations of the workers and/or the tasks to be disclosed to untrusted parties (SC server) for effective assignments of tasks to workers. In this paper we propose a framework for assigning tasks to workers in an online manner without compromising the location privacy of workers and tasks. We perturb the locations of both tasks and workers based on geo-indistinguishability and then devise techniques to quantify the probability of reachability between a task and a worker, given their perturbed locations. We investigate both analytical and empirical models for quantifying the worker-task pair reachability and propose task assignment strategies that strike a balance among various metrics such as the number of completed tasks, worker travel distance and system overhead. Extensive experiments on real-world datasets show that our proposed techniques result in minimal disclosure of task locations and no disclosure of worker locations without significantly sacrificing the total number of assigned tasks.

Geo-social applications deal with constantly sharing user's current geographic information in terms of location (Latitude and Longitude). Such application can be used by many people to get information about their surrounding with the help of their friend's locations and their recommendations. But without any privacy protection, these systems can be easily misused by tracking the users. We are proposing Error Based Transformation (ERB) approach for location transformation which provides significantly improved location privacy without adding uncertainty in to query results or relying on strong assumptions about server security. The key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. Only the friends of a user can get exact co-ordinates by applying inverse transformation with secret key shared with them. Servers can evaluate all location queries correctly on transformed data. ERB privacy mechanism guarantee that servers are unable to see or infer actual location data from the transformed data. ERB privacy mechanism is successful against a powerful adversary model where prototype measurements used to show that it provides with very little performance overhead making it suitable for today's mobile device.

Geo-social applications deal with constantly sharing user's current geographic information in terms of location (Latitude and Longitude). Such application can be used by many people to get information about their surrounding with the help of their friend's locations and their recommendations. But without any privacy protection, these systems can be easily misused by tracking the users. We are proposing Error Based Transformation (ERB) approach for location transformation which provides significantly improved location privacy without adding uncertainty in to query results or relying on strong assumptions about server security. The key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. Only the friends of a user can get exact co-ordinates by applying inverse transformation with secret key shared with them. Servers can evaluate all location queries correctly on transformed data. ERB privacy mechanism guarantee that servers are unable to see or infer actual location data from the transformed data. ERB privacy mechanism is successful against a powerful adversary model where prototype measurements used to show that it provides with very little performance overhead making it suitable for today's mobile device.

All popular browsers support browser extensions. They are small software module for customizing web browsers. It provides extra features like user interface modifications, ad blocking, cookie management and so on. As features increase, security becomes more difficult. The impact of malicious browser extensions is also enormous. More than 1 million Chrome users got affected by extensions from Chrome store itself. [1] The risk further increases with offline extension installations. The privileges browser extensions have, pave the path for many kinds of attacks. Replay attack and session hijacking are two of these attacks we are dealing here. Here we propose a defence system based on dynamic encrypted cookies to defend these attacks. We use cookies as token for continuous authentication, which protects entire communication. Static cookies are prone for session hijacking, and therefore we use dynamic cookies which are sealed with encryption. It also protects from replay attack by changing itself, making previous message obsolete. This essentially solves both of the problems.

Certificate Transparency (CT) is an emerging system for enabling the rapid discovery of malicious or misissued certificates. Initially standardized in 2013, CT is now finally beginning to see widespread support. Although CT provides desirable security benefits, web browsers cannot begin requiring all websites to support CT at once, due to the risk of breaking large numbers of websites. We discuss challenges for deployment, analyze the adoption of CT on the web, and measure the error rates experienced by users of the Google Chrome web browser. We find that CT has so far been widely adopted with minimal breakage and warnings. Security researchers often struggle with the tradeoff between security and user frustration: rolling out new security requirements often causes breakage. We view CT as a case study for deploying ecosystem-wide change while trying to minimize end user impact. We discuss the design properties of CT that made its success possible, as well as draw lessons from its risks and pitfalls that could be avoided in future large-scale security deployments.

The widespread adoption of social networking and cloud computing has transformed today's Internet to a trove of personal information. As a consequence, data breaches are expected to increase in gravity and occurrence. To counteract unintended data disclosure, a great deal of effort has been dedicated in devising methods for uncovering privacy leaks. Existing solutions, however, have not addressed the time- and data-intensive nature of leak detection. The shift from hardware-specific implementation to software-based solutions is the core idea behind the concept of Network Function Virtualization (NFV). On the other hand, the Software Defined Networking (SDN) paradigm is characterized by the decoupling of the forwarding and control planes. In this paper, an SDN/NFV-enabled architecture is proposed for improving the efficiency of leak detection systems. Employing a previously developed identification strategy, Personally Identifiable Information detector (PIID) and load balancer VNFs are packaged and deployed in OpenStack through an NFV MANO. Meanwhile, SDN controllers permit the load balancer to dynamically redistribute traffic among the PIID instances. In a physical testbed, tests are conducted to evaluate the proposed architecture. Experimental results indicate that the proportions of forwarding and parsing on total overhead is influenced by the traffic intensity. Furthermore, an NFV-enabled system with scalability features was found to outperform a non-virtualized implementation in terms of latency (85.1%), packet loss (98.3%) and throughput (8.41%).

In this paper we propose ROS-Defender, a holistic approach to secure robotics systems, which integrates a Security Event Management System (SIEM), an intrusion prevention system (IPS) and a firewall for a robotic system. ROS-Defender combines anomaly detection systems at application (ROS) level and network level, with dynamic policy enforcement points using software defined networking (SDN) to provide protection against a large class of attacks. Although SIEMs, IPS, and firewall have been previously used to secure computer networks, ROSDefender is applying them for the specific use case of robotic systems, where security is in many cases an afterthought.

Open-source honeypots are a vital component in the protection of networks and the observation of trends in the threat landscape. Their open nature also enables adversaries to identify the characteristics of these honeypots in order to detect and avoid them. In this study, we investigate the prevalence of 14 open- source honeypots running more or less default configurations, making them easily detectable by attackers. We deploy 20 simple signatures and test them for false positives against servers for domains in the Alexa top 10,000, official FTP mirrors, mail servers in real operation, and real IoT devices running telnet. We find no matches, suggesting good accuracy. We then measure the Internet-wide prevalence of default open-source honeypots by matching the signatures with Censys scan data and our own scans. We discovered 19,208 honeypots across 637 Autonomous Systems that are trivially easy to identify. Concentrations are found in research networks, but also in enterprise, cloud and hosting networks. While some of these honeypots probably have no operational relevance, e.g., they are student projects, this explanation does not fit the wider population. One cluster of honeypots was confirmed to belong to a well-known security center and was in use for ongoing attack monitoring. Concentrations in an another cluster appear to be the result of government incentives. We contacted 11 honeypot operators and received response from 4 operators, suggesting the problem of lack of network hygiene. Finally, we find that some honeypots are actively abused by attackers for hosting malicious binaries. We notified the owners of the detected honeypots via their network operators and provided recommendations for customization to avoid simple signature-based detection. We also shared our results with the honeypot developers.

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.

With the rapid development of the contemporary society, wide use of smart phone and vehicle sensing devices brings a huge influence on the extensive data collection. Network coding can only provide weak security privacy protection. Aiming at weak secure feature of network coding, this paper proposes an information transfer mechanism, Weak Security Network Coding with Homomorphic Encryption (HE-WSNC), and it is integrated into routing policy. In this mechanism, a movement model is designed, which allows information transmission process under Wi-Fi and Bluetooth environment rather than consuming 4G data flow. Not only does this application reduce the cost, but also improve reliability of data transmission. Moreover, it attracts more users to participate.

Authentication is the fundamental security service used in almost all remote applications. All such sensitive applications over an open network need authentication mechanism that should be delivered in a trusted way. In this paper, we design an RSA based authentication system for smart IoT environment over the air network using state-of-the-art industry standards. Our system provide security services including X.509 certificate, RSA based Public Key Infrastructure (PKI), challenge/response protocols with the help of proxy induced security service provider. We describe an innovative system model, protocol design, system architecture and evaluation against known threats. Also the implemented solution designed as an add on service for multiple other sensitive applications (smart city apps, cyber physical systems etc.) which needs the support of X.509 certificate based on hard tokens to populate other security services including confidentiality, integrity, non-repudiation, privacy and anonymity of the identities. The proposed scheme is evaluated against known vulnerabilities and given detail comparisons with popular known authentication schemes. The result shows that our proposed scheme mitigate all the known security risks and provide highest level assurance to smart gadgets.

Denial of Service (DoS) attacks have been a serious security concern, as no service is, in principle, protected against them. Although a Dolev-Yao intruder with unlimited resources can trivially render any service unavailable, DoS attacks do not necessarily have to be carried out by such (extremely) powerful intruders. It is useful in practice and more challenging for formal protocol verification to determine whether a service is vulnerable even to resource-bounded intruders that cannot generate or intercept arbitrary large volumes of traffic. This paper proposes a novel, more refined intruder model where the intruder can only consume at most some specified amount of resources in any given time window. Additionally, we propose protocol theories that may contain timeouts and specify service resource usage during protocol execution. In contrast to the existing resource-conscious protocol verification models, our model allows finer and more subtle analysis of DoS problems. We illustrate the power of our approach by representing a number of classes of DoS attacks, such as, Slow, Asymmetric and Amplification DoS attacks, exhausting different types of resources of the target, such as, number of workers, processing power, memory, and network bandwidth. We show that the proposed DoS problem is undecidable in general and is PSPACE-complete for the class of resource-bounded, balanced systems. Finally, we implemented our formal verification model in the rewriting logic tool Maude and analyzed a number of DoS attacks in Maude using Rewriting Modulo SMT in an automated fashion.

Rapid evolution of cyber threats and recent trends in the increasing number of cyber-attacks call for adopting robust and agile cybersecurity techniques. Cybersecurity information sharing is expected to play an effective role in detecting and defending against new attacks. However, reservations and or-ganizational policies centering the privacy of shared data have become major setbacks in large-scale collaboration in cyber defense. The situation is worsened by the fact that the benefits of cyber-information exchange are not realized unless many actors participate. In this paper, we argue that privacy preservation of shared threat data will motivate entities to share threat data. Accordingly, we propose a framework called CYBersecurity information EXchange with Privacy (CYBEX-P) to achieve this. CYBEX-P is a structured information sharing platform with integrating privacy-preserving mechanisms. We propose a complete system architecture for CYBEX-P that guarantees maximum security and privacy of data. CYBEX-P outlines the details of a cybersecurity information sharing platform. The adoption of blind processing, privacy preservation, and trusted computing paradigms make CYBEX-P a versatile and secure information exchange platform.

Load balancing and IP anycast are traffic routing algorithms used to speed up delivery of the Domain Name System. In case of a DDoS attack or an overload condition, the value of these protocols is critical, as they can provide intrinsic DDoS mitigation with the failover alternatives. In this paper, we present a methodology for predicting the next DNS response in the light of a potential redirection to less busy servers, in order to mitigate the size of the attack. Our experiments were conducted using data from the Nov. 2015 attack of the Root DNS servers and Logistic Regression, k-Nearest Neighbors, Support Vector Machines and Random Forest as our primary classifiers. The models were able to successfully predict up to 83% of responses for Root Letters that operated on a small number of sites and consequently suffered the most during the attacks. On the other hand, regarding DNS requests coming from more distributed Root servers, the models demonstrated lower accuracy. Our analysis showed a correlation between the True Positive Rate metric and the number of sites, as well as a clear need for intelligent management of traffic in load balancing practices.

Since cyber-physical systems are inherently vulnerable to information leaks, software architects need to reason about security policies to define desired and undesired information flow through a system. The microservice architectural style requires the architects to refine a macro-level security policy into micro-level policies for individual microservices. However, when policies are refined in an ill-formed way, information leaks can emerge on composition of microservices. Related approaches to prevent such leaks do not take into account characteristics of cyber-physical systems like real-time behavior or message passing communication. In this paper, we enable the refinement and verification of information-flow security policies for cyber-physical microservice architectures. We provide architects with a set of well-formedness rules for refining a macro-level policy in a way that enforces its security restrictions. Based on the resulting micro-level policies, we present a verification technique to check if the real-time message passing of microservices is secure. In combination, our contributions prevent information leaks from emerging on composition. We evaluate the accuracy of our approach using an extension of the CoCoME case study.