Biblio

Cyber-attacks continue to pose a major threat to existing critical infrastructure. Although suggestions for defensive strategies abound, Moving Target Defense (MTD) has only recently gained attention as a possible solution for mitigating cyber-attacks. The current work proposes a MTD technique that provides enhanced security through a rotation of multiple operating systems. The MTD solution developed in this research utilizes existing technology to provide a feasible dynamic defense solution that can be deployed easily in a real networking environment. In addition, the system we developed was tested extensively for effectiveness using CORE Impact Pro (CORE), Nmap, and manual penetration tests. The test results showed that platform diversity and rotation offer improved security. In addition, the likelihood of a successful attack decreased proportionally with time between rotations.
 

Moving target defense is an area of network security research in which machines are moved logically around a network in order to avoid detection. This is done by leveraging the immense size of the IPv6 address space and the statistical improbability of two machines selecting the same IPv6 address. This defensive technique forces a malicious actor to focus on the reconnaissance phase of their attack rather than focusing only on finding holes in a machine's static defenses. We have a current implementation of an IPv6 moving target defense entitled MT6D, which works well although is limited to functioning in a peer to peer scenario. As we push our research forward into client server networks, we must discover what the limits are in reference to the client server ratio. In our current implementation of a simple UDP echo server that binds large numbers of IPv6 addresses to the ethernet interface, we discover limits in both the number of addresses that we can successfully bind to an interface and the speed at which UDP requests can be successfully handled across a large number of bound interfaces.
 

Address shuffling is a type of moving target defense that prevents an attacker from reliably contacting a system by periodically remapping network addresses. Although limited testing has demonstrated it to be effective, little research has been conducted to examine the theoretical limits of address shuffling. As a result, it is difficult to understand how effective shuffling is and under what circumstances it is a viable moving target defense. This paper introduces probabilistic models that can provide insight into the performance of address shuffling. These models quantify the probability of attacker success in terms of network size, quantity of addresses scanned, quantity of vulnerable systems, and the frequency of shuffling. Theoretical analysis shows that shuffling is an acceptable defense if there is a small population of vulnerable systems within a large network address space, however shuffling has a cost for legitimate users. These results will also be shown empirically using simulation and actual traffic traces.
 

Datacenter-based Cloud computing has induced new disruptive trends in networking, key among which is network virtualization. Software-Defined Networking overlays aim to improve the efficiency of the next generation multitenant datacenters. While early overlay prototypes are already available, they focus mainly on core functionality, with little being known yet about their impact on the system level performance. Using query completion time as our primary performance metric, we evaluate the overlay network impact on two representative datacenter workloads, Partition/Aggregate and 3-Tier. We measure how much performance is traded for overlay's benefits in manageability, security and policing. Finally, we aim to assist the datacenter architects by providing a detailed evaluation of the key overlay choices, all made possible by our accurate cross-layer hybrid/mesoscale simulation platform.
 

Future networks may change the way how network administrators monitor and account their users. History shows that usually a completely new design (clean slate) is used to propose a new network architecture - e.g. Network Control Protocol to TCP/IP, IPv4 to IPv6 or IP to Recursive Inter Network Architecture. The incompatibility between these architectures changes the user accounting process as network administrators have to use different information to identify a user. The paper presents a methodology how it is possible to gather all necessary information needed for smooth transition between two incompatible architectures. The transition from IPv4 and IPv6 is used as a use case, but it should be able to use the same process with any new networking architecture.
 

The future Internet has been a hot topic during the past decade and many approaches towards this future Internet, ranging from incremental evolution to complete clean slate ones, have been proposed. One of the proposition, LISP, advocates for the separation of the identifier and the locator roles of IP addresses to reduce BGP churn and BGP table size. Up to now, however, most studies concerning LISP have been theoretical and, in fact, little is known about the actual LISP deployment performance. In this paper, we fill this gap through measurement campaigns carried out on the LISP Beta Network. More precisely, we evaluate the performance of the two key components of the infrastructure: the control plane (i.e., the mapping system) and the interworking mechanism (i.e., communication between LISP and non-LISP sites). Our measurements highlight that performance offered by the LISP interworking infrastructure is strongly dependent on BGP routing policies. If we exclude misconfigured nodes, the mapping system typically provides reliable performance and relatively low median mapping resolution delays. Although the bias is not very important, control plane performance favors USA sites as a result of its larger LISP user base but also because European infrastructure appears to be less reliable.
 

The OpenFlow architecture is a proposal from the Clean Slate initiative to define a new Internet architecture where the network devices are simple, and the control and management plane is performed by a centralized controller. The simplicity and centralization architecture makes it reliable and inexpensive. However, this architecture does not provide mechanisms to detect conflicting in flows, allowing that unreachable flows can be configured in the network elements, and the network may not behave as expected. This paper proposes an approach to conflict detection using first-order logic to define possible antagonisms and employ an inference engine to detect conflicting flows before the OpenFlow controller implement in the network elements.
 

This paper presents a unified approach for the detection of network anomalies. Current state of the art methods are often able to detect one class of anomalies at the cost of others. Our approach is based on using a Linear Dynamical System (LDS) to model network traffic. An LDS is equivalent to Hidden Markov Model (HMM) for continuous-valued data and can be computed using incremental methods to manage high-throughput (volume) and velocity that characterizes Big Data. Detailed experiments on synthetic and real network traces shows a significant improvement in detection capability over competing approaches. In the process we also address the issue of robustness of network anomaly detection systems in a principled fashion.
 

Network traffic is a rich source of information for security monitoring. However the increasing volume of data to treat raises issues, rendering holistic analysis of network traffic difficult. In this paper we propose a solution to cope with the tremendous amount of data to analyse for security monitoring perspectives. We introduce an architecture dedicated to security monitoring of local enterprise networks. The application domain of such a system is mainly network intrusion detection and prevention, but can be used as well for forensic analysis. This architecture integrates two systems, one dedicated to scalable distributed data storage and management and the other dedicated to data exploitation. DNS data, NetFlow records, HTTP traffic and honeypot data are mined and correlated in a distributed system that leverages state of the art big data solution. Data correlation schemes are proposed and their performance are evaluated against several well-known big data framework including Hadoop and Spark.

Eduroam is a secure WLAN roaming service between academic and research institutions around the globe. It allows users from participating institutions secure Internet access at any other participating visited institution using their home credentials. The authentication credentials are verified by the home institution, while authorization is done by the visited institution. The user receives an IP address in the range of the visited institution, and accesses the Internet through the firewall and proxy servers of the visited institution. However, access granted to services that authorize via an IP address of the visited institution may include access to services that are not allowed at the home institution, due to legal agreements. This paper looks at typical legal agreements with service providers and explores the risks and countermeasures that need to be considered when using eduroam.
 

IP technology for resource-constrained devices enables transparent end-to-end connections between a vast variety of devices and services in the Internet of Things (IoT). To protect these connections, several variants of traditional IP security protocols have recently been proposed for standardization, most notably the DTLS protocol. In this paper, we identify significant resource requirements for the DTLS handshake when employing public-key cryptography for peer authentication and key agreement purposes. These overheads particularly hamper secure communication for memory-constrained devices. To alleviate these limitations, we propose a delegation architecture that offloads the expensive DTLS connection establishment to a delegation server. By handing over the established security context to the constrained device, our delegation architecture significantly reduces the resource requirements of DTLS-protected communication for constrained devices. Additionally, our delegation architecture naturally provides authorization functionality when leveraging the central role of the delegation server in the initial connection establishment. Hence, in this paper, we present a comprehensive, yet compact solution for authentication, authorization, and secure data transmission in the IP-based IoT. The evaluation results show that compared to a public-key-based DTLS handshake our delegation architecture reduces the memory overhead by 64 %, computations by 97 %, network transmissions by 68 %.
 

Artificial monitoring is no longer able to match the rapid growth of cybercrime, it is in great need to develop a new spatial analysis technology which allows emergency events to get rapidly and accurately locked in real environment, furthermore, to establish correlative analysis model for cybercrime prevention strategy. On the other hand, Geography information system has been changed virtually in data structure, coordinate system and analysis model due to the “uncertainty and hyper-dimension” characteristics of network object and behavior. In this paper, the spatial rules of typical cybercrime are explored on base of GIS with Internet searching and IP tracking technology: (1) Setup spatial database through IP searching based on criminal evidence. (2)Extend GIS data-structure and spatial models, add network dimension and virtual attribution to realize dynamic connection between cyber and real space. (3)Design cybercrime monitoring and prevention system to discover the cyberspace logics based on spatial analysis.
 

The growth of the Internet has made IPv4 addresses a scarce resource. Due to slow IPv6 deployment, IANA-level IPv4 address exhaustion was reached before the world could transition to an IPv6-only Internet. The continuing need for IPv4 reachability will only be supported by IPv4 address sharing. This paper reviews ISP-level address sharing mechanisms, which allow Internet service providers to connect multiple customers who share a single IPv4 address. Some mechanisms come with severe and unpredicted consequences, and all of them come with tradeoffs. We propose a novel classification, which we apply to existing mechanisms such as NAT444 and DS-Lite and proposals such as 4rd, MAP, etc. Our tradeoff analysis reveals insights into many problems including: abuse attribution, performance degradation, address and port usage efficiency, direct intercustomer communication, and availability.
 

Smartphones are a new type of mobile devices that users can install additional mobile software easily. In the almost all smartphone applications, client-server model is used because end-to-end communication is prevented by NAT routers. Recently, some smartphone applications provide real time services such as voice and video communication, online games etc. In these applications, end-to-end communication is suitable to reduce transmission delay and achieve efficient network usage. Also, IP mobility and security are important matters. However, the conventional IP mobility mechanisms are not suitable for these applications because most mechanisms are assumed to be installed in OS kernel. We have developed a novel IP mobility mechanism called NTMobile (Network Traversal with Mobility). NTMobile supports end-to-end IP mobility in IPv4 and IPv6 networks, however, it is assumed to be installed in Linux kernel as with other technologies. In this paper, we propose a new type of end-to-end mobility platform that provides end-to-end communication, mobility, and also secure data exchange functions in the application layer for smartphone applications. In the platform, we use NTMobile, which is ported as the application program. Then, we extend NTMobile to be suitable for smartphone devices and to provide secure data exchange. Client applications can achieve secure end-to-end communication and secure data exchange by sharing an encryption key between clients. Users also enjoy IP mobility which is the main function of NTMobile in each application. Finally, we confirmed that the developed module can work on Android system and iOS system.
 

The paper presents a secure solution that provides VoIP service for mobile users, handling both pre-call and mid-call mobility. Pre-call mobility is implemented using a presence server that acts as a DNS for the moving users. Our approach also detects any change in the attachment point of the moving users and transmits it to the peer entity by in band signaling using socket communications. For true mid-call mobility we also employ buffering techniques that store packets for the duration of the signaling procedure. The solution was implemented for Android devices and it uses ASP technology for the server part.
 

Smartphones are a new type of mobile devices that users can install additional mobile software easily. In the almost all smartphone applications, client-server model is used because end-to-end communication is prevented by NAT routers. Recently, some smartphone applications provide real time services such as voice and video communication, online games etc. In these applications, end-to-end communication is suitable to reduce transmission delay and achieve efficient network usage. Also, IP mobility and security are important matters. However, the conventional IP mobility mechanisms are not suitable for these applications because most mechanisms are assumed to be installed in OS kernel. We have developed a novel IP mobility mechanism called NTMobile (Network Traversal with Mobility). NTMobile supports end-to-end IP mobility in IPv4 and IPv6 networks, however, it is assumed to be installed in Linux kernel as with other technologies. In this paper, we propose a new type of end-to-end mobility platform that provides end-to-end communication, mobility, and also secure data exchange functions in the application layer for smartphone applications. In the platform, we use NTMobile, which is ported as the application program. Then, we extend NTMobile to be suitable for smartphone devices and to provide secure data exchange. Client applications can achieve secure end-to-end communication and secure data exchange by sharing an encryption key between clients. Users also enjoy IP mobility which is the main function of NTMobile in each application. Finally, we confirmed that the developed module can work on Android system and iOS system.

Infrastructure-based Vehicular Networks can be applied in different social contexts, such as health care, transportation and entertainment. They can easily take advantage of the benefices provided by wireless mesh networks (WMNs) to mobility, since WMNs essentially support technological convergence and resilience, required for the effective operation of services and applications. However, infrastructure-based vehicular networks are prone to attacks such as ARP packets flooding that compromise mobility management and users' network access. Hence, this work proposes MIRF, a secure mobility scheme based on reputation and filtering to mitigate flooding attacks on mobility management. The efficiency of the MIRF scheme has been evaluated by simulations considering urban scenarios with and without attacks. Analyses show that it significantly improves the packet delivery ratio in scenarios with attacks, mitigating their intentional negative effects, as the reduction of malicious ARP requests. Furthermore, improvements have been observed in the number of handoffs on scenarios under attacks, being faster than scenarios without the scheme.

There is an increasing need for wireless sensor networks (WSNs) to be more tightly integrated with the Internet. Several real world deployment of stand-alone wireless sensor networks exists. A number of solutions have been proposed to address the security threats in these WSNs. However, integrating WSNs with the Internet in such a way as to ensure a secure End-to-End (E2E) communication path between IPv6 enabled sensor networks and the Internet remains an open research issue. In this paper, the 6LoWPAN adaptation layer was extended to support both IPsec's Authentication Header (AH) and Encapsulation Security Payload (ESP). Thus, the communication endpoints in WSNs are able to communicate securely using encryption and authentication. The proposed AH and ESP compressed headers performance are evaluated via test-bed implementation in 6LoWPAN for IPv6 communications on IEEE 802.15.4 networks. The results confirm the possibility of implementing E2E security in IPv6 enabled WSNs to create a smooth transition between WSNs and the Internet. This can potentially play a big role in the emerging "Internet of Things" paradigm.

The emerging paradigm of cloud computing, e.g., Amazon Elastic Compute Cloud (EC2), promises a highly flexible yet robust environment for large-scale applications. Ideally, while multiple virtual machines (VM) share the same physical resources (e.g., CPUs, caches, DRAM, and I/O devices), each application should be allocated to an independently managed VM and isolated from one another. Unfortunately, the absence of physical isolation inevitably opens doors to a number of security threats. In this paper, we demonstrate in EC2 a new type of security vulnerability caused by competition between virtual I/O workloads-i.e., by leveraging the competition for shared resources, an adversary could intentionally slow down the execution of a targeted application in a VM that shares the same hardware. In particular, we focus on I/O resources such as hard-drive throughput and/or network bandwidth-which are critical for data-intensive applications. We design and implement Swiper, a framework which uses a carefully designed workload to incur significant delays on the targeted application and VM with minimum cost (i.e., resource consumption). We conduct a comprehensive set of experiments in EC2, which clearly demonstrates that Swiper is capable of significantly slowing down various server applications while consuming a small amount of resources.

With the rapid increase in cloud services collecting and using user data to offer personalized experiences, ensuring that these services comply with their privacy policies has become a business imperative for building user trust. However, most compliance efforts in industry today rely on manual review processes and audits designed to safeguard user data, and therefore are resource intensive and lack coverage. In this paper, we present our experience building and operating a system to automate privacy policy compliance checking in Bing. Central to the design of the system are (a) Legal ease-a language that allows specification of privacy policies that impose restrictions on how user data is handled, and (b) Grok-a data inventory for Map-Reduce-like big data systems that tracks how user data flows among programs. Grok maps code-level schema elements to data types in Legal ease, in essence, annotating existing programs with information flow types with minimal human input. Compliance checking is thus reduced to information flow analysis of Big Data systems. The system, bootstrapped by a small team, checks compliance daily of millions of lines of ever-changing source code written by several thousand developers.

Cryptographically-Curated File System (CCFS) proposed in this work supports the adoption of Information-Centric Networking. CCFS utilizes content names that span trust boundaries, verify integrity, tolerate disruption, authenticate content, and provide non-repudiation. Irrespective of the ability to reach an authoritative host, CCFS provides secure access by binding a chain of trust into the content name itself. Curators cryptographically bind content to a name, which is a path through a series of objects that map human meaningful names to cryptographically strong content identifiers. CCFS serves as a network layer for storage systems unifying currently disparate storage technologies. The power of CCFS derives from file hashes and public keys used as a name with which to retrieve content and as a method of verifying that content. We present results from our prototype implementation. Our results show that the overhead associated with CCFS is not negligible, but also is not prohibitive.

Intrusion Detection Systems (IDS) have become a necessity in computer security systems because of the increase in unauthorized accesses and attacks. Intrusion Detection is a major component in computer security systems that can be classified as Host-based Intrusion Detection System (HIDS), which protects a certain host or system and Network-based Intrusion detection system (NIDS), which protects a network of hosts and systems. This paper addresses Probes attacks or reconnaissance attacks, which try to collect any possible relevant information in the network. Network probe attacks have two types: Host Sweep and Port Scan attacks. Host Sweep attacks determine the hosts that exist in the network, while port scan attacks determine the available services that exist in the network. This paper uses an intelligent system to maximize the recognition rate of network attacks by embedding the temporal behavior of the attacks into a TDNN neural network structure. The proposed system consists of five modules: packet capture engine, preprocessor, pattern recognition, classification, and monitoring and alert module. We have tested the system in a real environment where it has shown good capability in detecting attacks. In addition, the system has been tested using DARPA 1998 dataset with 100% recognition rate. In fact, our system can recognize attacks in a constant time.

IP spoofing based DDoS attack that relies on multiple compromised hosts in the network to attack the victim. In IP spoofing, IP addresses can be forged easily, thus, makes it difficult to filter illegitimate packets from legitimate one out of aggregated traffic. A number of mitigation techniques have been proposed in the literature by various researchers. The conventional Hop Count Filtering or probabilistic Hop Count Filtering based research work indicates the problems related to higher computational time and low detection rate of illegitimate packets. In this paper, DPHCF-RTT technique has been implemented and analysed for variable number of hops. Goal is to improve the limitations of Conventional HCF or Probabilistic HCF techniques by maximizing the detection rate of illegitimate packets and reducing the computation time. It is based on distributed probabilistic HCF using RTT. It has been used in an intermediate system. It has the advantage for resolving the problems of network bandwidth jam and host resources exhaustion. MATLAB 7 has been used for simulations. Mitigation of DDoS attacks have been done through DPHCF-RTT technique. It has been shown a maximum detection rate up to 99% of malicious packets.

This work proposes a novel approach to infer and characterize Internet-scale DNS amplification DDoS attacks by leveraging the darknet space. Complementary to the pioneer work on inferring Distributed Denial of Service (DDoS) using darknet, this work shows that we can extract DDoS activities without relying on backscattered analysis. The aim of this work is to extract cyber security intelligence related to DNS Amplification DDoS activities such as detection period, attack duration, intensity, packet size, rate and geo- location in addition to various network-layer and flow-based insights. To achieve this task, the proposed approach exploits certain DDoS parameters to detect the attacks. We empirically evaluate the proposed approach using 720 GB of real darknet data collected from a /13 address space during a recent three months period. Our analysis reveals that the approach was successful in inferring significant DNS amplification DDoS activities including the recent prominent attack that targeted one of the largest anti-spam organizations. Moreover, the analysis disclosed the mechanism of such DNS amplification DDoS attacks. Further, the results uncover high-speed and stealthy attempts that were never previously documented. The case study of the largest DDoS attack in history lead to a better understanding of the nature and scale of this threat and can generate inferences that could contribute in detecting, preventing, assessing, mitigating and even attributing of DNS amplification DDoS activities.

The Internet is vulnerable to bandwidth distributed denial-of-service (BW-DDoS) attacks, wherein many hosts send a huge number of packets to cause congestion and disrupt legitimate traffic. So far, BW-DDoS attacks have employed relatively crude, inefficient, brute force mechanisms; future attacks might be significantly more effective and harmful. To meet the increasing threats, we must deploy more advanced defenses.