Biblio
Mobile ad hoc network is one of the popular network technology used for rapid deployment in critical situations. Because the nature of network is ad hoc therefore a number of issues exist. In order to investigate the security in mobile ad hoc network a number of research articles are explored and it is observed that most of the attacks are deployed on the basis of poor routing methodology. For providing the security in the ad hoc networks an opinion based trust model is proposed which is working on the basis of the network properties. In this model two techniques are used one is trust calculation that helps in finding most trustworthy node and other is opinion evaluation by which most secure route to the destination is obtained. By the experimental outcomes the results are compared with the traditional approach of trust based security. According to the obtained results the performance of the network becomes efficient in all the evaluated parameters as compared to the traditional technique. Thus proposed model is more adoptable for secure routing in MANET.
Security in cloud environments is always considered an issue, due to the lack of control over leased resources. In this paper, we present a solution that offers security-as-a-service by relying on Security Service Level Agreements (Security SLAs) as a means to represent the security features to be granted. In particular, we focus on a security mechanism that is automatically configured and activated in an as-a-service fashion in order to protect cloud resources against DoS attacks. The activities reported in this paper are part of a wider work carried out in the FP7-ICT programme project SPECS, which aims at building a framework offering Security-as-a-Service using an SLA-based approach. The proposed approach founds on the adoption of SPECS Services to negotiate, to enforce and to monitor suitable security metrics, chosen by cloud customers, negotiated with the provider and included in a signed Security SLA.
Wireless Mesh Networks (WMNs) are being considered as most adequate for deployment in the Neighborhood Area Network (NAN) domain of the smart grid infrastructure because their features such as self-organizing, scalability and cost-efficiency complement the NAN requirements. To enhance the security of the WMNs, the key refreshment strategy for the Simultaneous Authentication of Equals (SAE) or the Efficient Mesh Security Association (EMSA) protocols is an efficient way to make the network more resilient against the cyber-attacks. However, a security vulnerability is discovered in the EMSA protocol when using the key refreshment strategy. The first message of the Mesh Key Holder Security Handshake (MKHSH) can be forged and replayed back in the next cycles of the key refreshment leading to a Denial of Service (DoS) attack. In this paper, a simple one-way hash function based scheme is proposed to prevent the unprotected message from being replayed together with an enhancement to the key refreshment scheme to improve the resilience of the MKHSH. The Protocol Composition Logic (PCL) is used to verify the logical correctness of the proposed scheme, while the Process Analysis Toolkit (PAT) is used to evaluate the security functionality against the malicious attacks.
Rapid advances in wireless ad hoc networks lead to increase their applications in real life. Since wireless ad hoc networks have no centralized infrastructure and management, they are vulnerable to several security threats. Malicious packet dropping is a serious attack against these networks. In this attack, an adversary node tries to drop all or partial received packets instead of forwarding them to the next hop through the path. A dangerous type of this attack is called black hole. In this attack, after absorbing network traffic by the malicious node, it drops all received packets to form a denial of service (DOS) attack. In this paper, a dynamic trust model to defend network against this attack is proposed. In this approach, a node trusts all immediate neighbors initially. Getting feedback from neighbors' behaviors, a node updates the corresponding trust value. The simulation results by NS-2 show that the attack is detected successfully with low false positive probability.
Advanced Metering Infrastructure (AMI) is the core component in a smart grid that exhibits a highly complex network configuration. AMI shares information about consumption, outages, and electricity rates reliably and efficiently by bidirectional communication between smart meters and utilities. However, the numerous smart meters being connected through mesh networks open new opportunities for attackers to interfere with communications and compromise utilities assets or steal customers private information. In this paper, we present a new DoS attack, called puppet attack, which can result in denial of service in AMI network. The intruder can select any normal node as a puppet node and send attack packets to this puppet node. When the puppet node receives these attack packets, this node will be controlled by the attacker and flood more packets so as to exhaust the network communication bandwidth and node energy. Simulation results show that puppet attack is a serious and packet deliver rate goes down to 20%-10%.
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attack, exhausts the resources of server/service and makes it unavailable for legitimate users. With increasing use of online services and attacks on these services, the importance of Intrusion Detection System (IDS) for detection of DoS/DDoS attacks has also grown. Detection accuracy & CPU utilization of Data mining based IDS is directly proportional to the quality of training dataset used to train it. Various preprocessing methods like normalization, discretization, fuzzification are used by researchers to improve the quality of training dataset. This paper evaluates the effect of various data preprocessing methods on the detection accuracy of DoS/DDoS attack detection IDS and proves that numeric to binary preprocessing method performs better compared to other methods. Experimental results obtained using KDD 99 dataset are provided to support the efficiency of proposed combination.
By exploiting the communication infrastructure among the sensors, actuators, and control systems, attackers may compromise the security of smart-grid systems, with techniques such as denial-of-service (DoS) attack, random attack, and data-injection attack. In this paper, we present a mathematical model of the system to study these pitfalls and propose a robust security framework for the smart grid. Our framework adopts the Kalman filter to estimate the variables of a wide range of state processes in the model. The estimates from the Kalman filter and the system readings are then fed into the χ2-detector or the proposed Euclidean detector. The χ2-detector is a proven effective exploratory method used with the Kalman filter for the measurement of the relationship between dependent variables and a series of predictor variables. The χ2-detector can detect system faults/attacks, such as DoS attack, short-term, and long-term random attacks. However, the studies show that the χ2-detector is unable to detect the statistically derived false data-injection attack. To overcome this limitation, we prove that the Euclidean detector can effectively detect such a sophisticated injection attack.