A privacy preserving framework for cyber-physical systems and its integration in real world applications

A cyber-physical system (CPS) comprises of a network of processing and communication capable sensors and actuators that are pervasively embedded in the physical world. These intelligent computing elements achieve the tight combination and coordination between the logic processing and physical resources. It is envisioned that CPS will have great economic and societal impact, and alter the qualify of life like what Internet has done. This dissertation focuses on the privacy issues in current and future CPS applications. as thousands of the intelligent devices are deeply embedded in human societies, the system operations may potentially disclose the sensitive information if no privacy preserving mechanism is designed. This dissertation identifies data privacy and location privacy as the representatives to investigate the privacy problems in CPS. The data content privacy infringement occurs if the adversary can determine or partially determine the meaning of the transmitted data or the data stored in the storage. The location privacy, on the other hand, is the secrecy that a certain sensed object is associated to a specific location, the disclosure of which may endanger the sensed object. The location privacy may be compromised by the adversary through hop-by-hop traceback along the reverse direction of the message routing path. This dissertation proposes a public key based access control scheme to protect the data content privacy. Recent advances in efficient public key schemes, such as ECC, have already shown the feasibility to use public key schemes on low power devices including sensor motes. In this dissertation, an efficient public key security primitives, WM-ECC, has been implemented for TelosB and MICAz, the two major hardware platform in current sensor networks. WM-ECC achieves the best performance among the academic implementations. Based on WM-ECC, this dissertation has designed various security schemes, including pairwise key establishment, user access control and false data filtering mechanism, to protect the data content privacy. The experiments presented in this dissertation have shown that the proposed schemes are practical for real world applications. to protect the location privacy, this dissertation has considered two adversary models. For the first model in which an adversary has limited radio detection capability, the privacy-aware routing schemes are designed to slow down the adversary\u27s traceback progress. Through theoretical analysis, this dissertation shows how to maximize the adversary\u27s traceback time given a power consumption budget for message routing. Based on the theoretical results, this dissertation also proposes a simple and practical weighted random stride (WRS) routing scheme. The second model assumes a more powerful adversary that is able to monitor all radio communications in the network. This dissertation proposes a random schedule scheme in which each node transmits at a certain time slot in a period so that the adversary would not be able to profile the difference in communication patterns among all the nodes. Finally, this dissertation integrates the proposed privacy preserving framework into Snoogle, a sensor nodes based search engine for the physical world. Snoogle allows people to search for the physical objects in their vicinity. The previously proposed privacy preserving schemes are applied in the application to achieve the flexible and resilient privacy preserving capabilities. In addition to security and privacy, Snoogle also incorporates a number of energy saving and communication compression techniques that are carefully designed for systems composed of low-cost, low-power embedded devices. The evaluation study comprises of the real world experiments on a prototype Snoogle system and the scalability simulations

Preventing DDoS using Bloom Filter: A Survey

Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending a DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.Comment: 9 pages, 1 figure. This article is accepted for publication in EAI Endorsed Transactions on Scalable Information System

Provenance-enabled Packet Path Tracing in the RPL-based Internet of Things

The interconnection of resource-constrained and globally accessible things with untrusted and unreliable Internet make them vulnerable to attacks including data forging, false data injection, and packet drop that affects applications with critical decision-making processes. For data trustworthiness, reliance on provenance is considered to be an effective mechanism that tracks both data acquisition and data transmission. However, provenance management for sensor networks introduces several challenges, such as low energy, bandwidth consumption, and efficient storage. This paper attempts to identify packet drop (either maliciously or due to network disruptions) and detect faulty or misbehaving nodes in the Routing Protocol for Low-Power and Lossy Networks (RPL) by following a bi-fold provenance-enabled packed path tracing (PPPT) approach. Firstly, a system-level ordered-provenance information encapsulates the data generating nodes and the forwarding nodes in the data packet. Secondly, to closely monitor the dropped packets, a node-level provenance in the form of the packet sequence number is enclosed as a routing entry in the routing table of each participating node. Lossless in nature, both approaches conserve the provenance size satisfying processing and storage requirements of IoT devices. Finally, we evaluate the efficacy of the proposed scheme with respect to provenance size, provenance generation time, and energy consumption.Comment: 14 pages, 18 Figure

Real-time cross-layer design for large-scale flood detection and attack trace-back mechanism in IEEE 802.11 wireless mesh networks

IEEE 802.11 WMN is an emerging next generation low-cost multi-hop wireless broadband provisioning technology. It has the capability of integrating wired and wireless networks such as LANs, IEEE 802.11 WLANs, IEEE 802.16 WMANs, and sensor networks. This kind of integration: large-scale coverage, decentralised and multi-hop architecture, multi-radios, multi-channel assignments, ad hoc connectivity support the maximum freedom of users to join or leave the network from anywhere and at anytime has made the situation far more complex. As a result broadband resources are exposed to various kinds of security attacks, particularly DoS attacks

An Approach for Mitigating Denial of Service Attack

Distributed Denial of Service (DDoS) attacks are the most common types of cyber-attack on the internet and are rapidly increasing. Denial of service/distributed denial of service attack is an explicit attempt to make a machine or a network resource unavailable to its intended users. Attackers interrupt/suspend services of the host connected to internet temporarily or indefinitely.It involves saturating the target machine with external communication requests such that it cannot either respond to legitimate traffic or responds so slowly as to be rendered effectively unavailable. Two general form of Dos attacks are - those attacks that crashes services (computer attack) and those that flood services (network attack). Flooding DDoS attacks produce adverse effects for critical infrastructure availability, integrity and confidentiality. Current defense approaches cannot efficiently detect and filter out the attack traffic in real time. Based on the assumption that the attacker flows are very aggressive than the legitimate users the proposed work provides sufficient bandwidth to genuine users during flooding DDoS attack.The aim of the project is to implement an approach for mitigating DDoS based on “The Interface Based Rate Limiting (IBRL) algorithm”, used to mitigate the identified DDoS attacks. The implementation is carried out on a simulation tool Omnett++ installed on linux machine. The results are the plots that show that there is considerable increase in the two important and significant measures, response time and packet drop metrics for legitimate users even under DoS and DDoS attacks

A Defense Framework Against Denial-of-Service in Computer Networks

Denial-of-Service (DoS) is a computer security problem that poses a serious challenge totrustworthiness of services deployed over computer networks. The aim of DoS attacks isto make services unavailable to legitimate users, and current network architectures alloweasy-to-launch, hard-to-stop DoS attacks. Particularly challenging are the service-level DoSattacks, whereby the victim service is flooded with legitimate-like requests, and the jammingattack, in which wireless communication is blocked by malicious radio interference. Theseattacks are overwhelming even for massively-resourced services, and effective and efficientdefenses are highly needed. This work contributes a novel defense framework, which I call dodging, against service-level DoS and wireless jamming. Dodging has two components: (1) the careful assignment ofservers to clients to achieve accurate and quick identification of service-level DoS attackersand (2) the continuous and unpredictable-to-attackers reconfiguration of the client-serverassignment and the radio-channel mapping to withstand service-level and jamming DoSattacks. Dodging creates hard-to-evade baits, or traps, and dilutes the attack "fire power".The traps identify the attackers when they violate the mapping function and even when theyattack while correctly following the mapping function. Moreover, dodging keeps attackers"in the dark", trying to follow the unpredictably changing mapping. They may hit a fewtimes but lose "precious" time before they are identified and stopped. Three dodging-based DoS defense algorithms are developed in this work. They are moreresource-efficient than state-of-the-art DoS detection and mitigation techniques. Honeybees combines channel hopping and error-correcting codes to achieve bandwidth-efficientand energy-efficient mitigation of jamming in multi-radio networks. In roaming honeypots, dodging enables the camouflaging of honeypots, or trap machines, as real servers,making it hard for attackers to locate and avoid the traps. Furthermore, shuffling requestsover servers opens up windows of opportunity, during which legitimate requests are serviced.Live baiting, efficiently identifies service-level DoS attackers by employing results fromthe group-testing theory, discovering defective members in a population using the minimumnumber of tests. The cost and benefit of the dodging algorithms are analyzed theoretically,in simulation, and using prototype experiments

Techniques to Detect DoS and DDoS Attacks and an Introduction of a Mobile Agent System to Enhance it in Cloud Computing

Security in cloud computing is the ultimate question that every potential user studies before adopting it. Among the important points that the provider must ensure is that the Cloud will be available anytime the consumer tries to access it. Generally, the Cloud is accessible via the Internet, what makes it subject to a large variety of attacks. Today, the most striking cyber-attacks are the flooding DoS and its variant DDoS. This type of attacks aims to break down the availability of a service to its legitimate clients. In this paper, we underline the most used techniques to stand up against DoS flooading attacks in the Cloud