Matrix-based pairwise key establishment with pre and post deployment knowledge for wireless mesh networks

The nature of wireless transmission leads to vulnerabilities to many malicious activities, and communication in wireless mesh networks (WMNs) must be protected by proper security measures. This paper focuses on symmetric pair wise key establishment and presents a new matrix-based pair wise key establishment scheme for mesh clients. In WMNs, mesh routers are much more powerful than mesh clients, both in communication and computation. By taking advantage of this heterogeneity, our new scheme delegates energy-consuming operations to mesh routers when establishing pair wise keys for mesh clients. Additionally, neighbor mesh clients in our scheme can directly establish pair wise keys with significantly reduced communication and storage costs, due to the use of both pre and post deployment knowledge.

Catabolism attack and anabolism defense: a novel attack and traceback mechanism in opportunistic networks

Security is a major challenge in Opportunistic Networks (OppNets) because of its characteristics, such as open medium, dynamic topology, no centralized management and absent clear lines of defense.A packet dropping attack is one of the major security threats in OppNets since neither source nodes nor destination nodes have the knowledge of where or when the packet will be dropped. In this paper, we present a novel attack and traceback mechanism against a special type of packet dropping where the malicious node drops one or more packets and then injects new fake packets instead. We call this novel attack a Catabolism Attack and we call our novel traceback mechanism against this attack Anabolism Defense. Our novel detection and traceback mechanism is very powerful and has very high accuracy. Each node can detect and then traceback the malicious nodes based on a solid and powerful idea that is, hash chain techniques. In our defense techniques we have two stages. The first stage is to detect the attack, and the second stage is to find the malicious nodes. Simulation results show this robust mechanism achieves a very high accuracy and detection rate.

Transmission network expansion planning in full open market considering security constraints

This paper presents a mathematical model and a methodology to solve the transmission network expansion planning problem with security constraints in full competitive market, assuming that all generation programming plans present in the system operation are known. The methodology let us find an optimal transmission network expansion plan that allows the power system to operate adequately in each one of the generation programming plans specified in the full competitive market case, including a single contingency situation with generation rescheduling using the security (n-1) criterion. In this context, the centralized expansion planning with security constraints and the expansion planning in full competitive market are subsets of the proposal presented in this paper. The model provides a solution using a genetic algorithm designed to efficiently solve the reliable expansion planning in full competitive market. The results obtained for several known systems from the literature show the excellent performance of the proposed methodology.

L3-arpsec - módulo seguro para controle e proteção do protocolo de resolução de endereços em redes definidas por software

Pós-graduação em Engenharia Elétrica - FEIS

Persistent Caching in Information-Centric Networks

Information-centric networking (ICN) is a new communication paradigm that aims at increasing security and efficiency of content delivery in communication networks. In recent years, many research efforts in ICN have focused on caching strategies to reduce traffic and increase overall performance by decreasing download times. Since caches need to operate at line speed, they have only a limited size and content can only be stored for a short time. However, if content needs to be available for a longer time, e.g., for delay-tolerant networking or to provide high content availability similar to content delivery networks (CDNs), persistent caching is required. We base our work on the Content-Centric Networking (CCN) architecture and investigate persistent caching by extending the current repository implementation in CCNx. We show by extensive evaluations in a YouTube and webserver traffic scenario that repositories can be efficiently used to increase content availability by significantly increasing cache hit rates.

Defense against node compromise in sensor network security

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

Defense Against Node Compromise in Sensor Network Security

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

Security Evaluation of Substation Network Architectures

In recent years, security of industrial control systems has been the main research focus due to the potential cyber-attacks that can impact the physical operations. As a result of these risks, there has been an urgent need to establish a stronger security protection against these threats. Conventional firewalls with stateful rules can be implemented in the critical cyberinfrastructure environment which might require constant updates. Despite the ongoing effort to maintain the rules, the protection mechanism does not restrict malicious data flows and it poses the greater risk of potential intrusion occurrence. The contributions of this thesis are motivated by the aforementioned issues which include a systematic investigation of attack-related scenarios within a substation network in a reliable sense. The proposed work is two-fold: (i) system architecture evaluation and (ii) construction of attack tree for a substation network. Cyber-system reliability remains one of the important factors in determining the system bottleneck for investment planning and maintenance. It determines the longevity of the system operational period with or without any disruption. First, a complete enumeration of existing implementation is exhaustively identified with existing communication architectures (bidirectional) and new ones with strictly unidirectional. A detailed modeling of the extended 10 system architectures has been evaluated. Next, attack tree modeling for potential substation threats is formulated. This quantifies the potential risks for possible attack scenarios within a network or from the external networks. The analytical models proposed in this thesis can serve as a fundamental development that can be further researched.

Characterising anomalous events using change point correlation on unsolicited network traffic

Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.

Reconstruction of falsified computer logs for digital forensics investigations

Digital forensics investigations aim to find evidence that helps confirm or disprove a hypothesis about an alleged computer-based crime. However, the ease with which computer-literate criminals can falsify computer event logs makes the prosecutor's job highly challenging. Given a log which is suspected to have been falsified or tampered with, a prosecutor is obliged to provide a convincing explanation for how the log may have been created. Here we focus on showing how a suspect computer event log can be transformed into a hypothesised actual sequence of events, consistent with independent, trusted sources of event orderings. We present two algorithms which allow the effort involved in falsifying logs to be quantified, as a function of the number of `moves' required to transform the suspect log into the hypothesised one, thus allowing a prosecutor to assess the likelihood of a particular falsification scenario. The first algorithm always produces an optimal solution but, for reasons of efficiency, is suitable for short event logs only. To deal with the massive amount of data typically found in computer event logs, we also present a second heuristic algorithm which is considerably more efficient but may not always generate an optimal outcome.