Biblio

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 %.
 

Mobile ad hoc networks have the features of open medium, dynamic topology, cooperative algorithms, lack of centralized monitoring etc. Due to these, mobile ad hoc networks are much vulnerable to security attacks when compared to wired networks. There are various routing protocols that have been developed to cope up with the limitations imposed by the ad hoc networks. But none of these routing schemes provide complete unlinkability and unobservability. In this paper we have done a survey about anonymous routing and secure communications in mobile ad hoc networks. Different routing protocols are analyzed based on public/private key pairs and cryptosystems, within that USOR can well protect user privacy against both inside and outside attackers. It is a combination of group signature scheme and ID based encryption scheme. These are run during the route discovery process. We implement USOR on ns2, and then its performance is compared with AODV.

The innovations in communication and computing technologies are changing the way we carry-out the tasks in our daily lives. These revolutionary and disrupting technologies are available to the users in various hardware form-factors like Smart Phones, Embedded Appliances, Configurable or Customizable add-on devices, etc. One such technology is Bluetooth [1], which enables the users to communicate and exchange various kinds of information like messages, audio, streaming music and file transfer in a Personal Area Network (PAN). Though it enables the user to carry-out these kinds of tasks without much effort and infrastructure requirements, they inherently bring with them the security and privacy concerns, which need to be addressed at different levels. In this paper, we present an application-layer framework, which provides strong mutual authentication of applications, data confidentiality and data integrity independent of underlying operating system. It can make use of the services of different Cryptographic Service Providers (CSP) on different operating systems and in different programming languages. This framework has been successfully implemented and tested on Android Operating System on one end (using Java language) and MS-Windows 7 Operating System on the other end (using ANSI C language), to prove the framework's reliability/compatibility across OS, Programming Language and CSP. This framework also satisfies the three essential requirements of Security, i.e. Confidentiality, Integrity and Availability, as per the NIST Guide to Bluetooth Security specification and enables the developers to suitably adapt it for different kinds of applications based on Bluetooth Technology.

Theft or loss of a mobile device could be an information security risk as it can result in loss of con fidential personal data. Traditional cryptographic algorithms are not suitable for resource constrained and handheld devices. In this paper, we have developed an efficient and user friendly tool called “NCRYPT” on Android platform. “NCRYPT” application is used to secure the data at rest on Android thus making it inaccessible to unauthorized users. It is based on lightweight encryption scheme i.e. Hummingbird-2. The application provides secure storage by making use of password based authentication so that an adversary cannot access the confidential data stored on the mobile device. The cryptographic key is derived through the password based key generation method PBKDF2 from the standard SUN JCE cryptographic provider. Various tools for encryption are available in the market which are based on AES or DES encryption schemes. Ihe reported tool is based on Hummingbird-2 and is faster than most of the other existing schemes. It is also resistant to most of attacks applicable to Block and Stream Ciphers. Hummingbird-2 has been coded in C language and embedded in Android platform with the help of JNI (Java Native Interface) for faster execution. This application provides choice for en crypting the entire data on SD card or selective files on the smart phone and protect p ersonal or confidential information available in such devices.

Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user's channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique's effectiveness.

Cloud computing technologies are receiving a great deal of attention. Furthermore most of the hardware devices such as the PCs and mobile phones are increasingly having a trusted component called Trusted Platform Module embedded in them, which helps to measure the state of the platform and hence reason about its trust. Recently attestation techniques such as binary attestation and property based attestation techniques have been proposed based on the TPM. In this paper, we propose a novel trust enhanced security model for cloud services that helps to detect and prevent security attacks in cloud infrastructures using trusted attestation techniques. We consider a cloud architecture where different services are hosted on virtualized systems on the cloud by multiple cloud customers (multi-tenants). We consider attacker model and various attack scenarios for such hosted services in the cloud. Our trust enhanced security model enables the cloud service provider to certify certain security properties of the tenant virtual machines and services running on them. These properties are then used to detect and minimise attacks between the cloud tenants running virtual machines on the infrastructure and its customers as well as increase the assurance of the tenant virtual machine transactions. If there is a variation in the behaviour of the tenant virtual machine from the certified properties, the model allows us to dynamically isolate the tenant virtual machine or even terminate the malicious services on a fine granular basis. The paper describes the design and implementation of the proposed model and discusses how it deals with the different attack scenarios. We also show that our model is beneficial for the cloud service providers, cloud customers running tenant virtual machines as well as the customers using the services provided by these tenant virtual machines.

Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user's channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique's effectiveness.

We characterize the secrecy level of communication under Uncoordinated Frequency Hopping, a spread spectrum scheme where a transmitter and a receiver randomly hop through a set of frequencies with the goal of deceiving an adversary. In our work, the goal of the legitimate parties is to land on a given frequency without the adversary eavesdroppers doing so, therefore being able to communicate securely in that period, that may be used for secret-key exchange. We also consider the effect on secrecy of the availability of friendly jammers that can be used to obstruct eavesdroppers by causing them interference. Our results show that tuning the number of frequencies and adding friendly jammers are effective countermeasures against eavesdroppers.

While many theoretical and simulation works have highlighted the potential gains of cognitive radio, several technical issues still need to be evaluated from an experimental point of view. Deploying complex heterogeneous system scenarios is tedious, time consuming and hardly reproducible. To address this problem, we have developed a new experimental facility, called CorteXlab, that allows complex multi-node cognitive radio scenarios to be easily deployed and tested by anyone in the world. Our objective is not to design new software defined radio (SDR) nodes, but rather to provide a comprehensive access to a large set of high performance SDR nodes. The CorteXlab facility offers a 167 m2 electromagnetically (EM) shielded room and integrates a set of 24 universal software radio peripherals (USRPs) from National Instruments, 18 PicoSDR nodes from Nutaq and 42 IoT-Lab wireless sensor nodes from Hikob. CorteXlab is built upon the foundations of the SensLAB testbed and is based the free and open-source toolkit GNU Radio. Automation in scenario deployment, experiment start, stop and results collection is performed by an experiment controller, called Minus. CorteXlab is in its final stages of development and is already capable of running test scenarios. In this contribution, we show that CorteXlab is able to easily cope with the usual issues faced by other testbeds providing a reproducible experiment environment for CR experimentation.
 

Wireless sensor networks (WSNs) are prone to propagating malware because of special characteristics of sensor nodes. Considering the fact that sensor nodes periodically enter sleep mode to save energy, we develop traditional epidemic theory and construct a malware propagation model consisting of seven states. We formulate differential equations to represent the dynamics between states. We view the decision-making problem between system and malware as an optimal control problem; therefore, we formulate a malware-defense differential game in which the system can dynamically choose its strategies to minimize the overall cost whereas the malware intelligently varies its strategies over time to maximize this cost. We prove the existence of the saddle-point in the game. Further, we attain optimal dynamic strategies for the system and malware, which are bang-bang controls that can be conveniently operated and are suitable for sensor nodes. Experiments identify factors that influence the propagation of malware. We also determine that optimal dynamic strategies can reduce the overall cost to a certain extent and can suppress the malware propagation. These results support a theoretical foundation to limit malware in WSNs.

The reliability theory used in the design of complex systems including electric grids assumes random component failures and is thus unsuited to analyzing security risks due to attackers that intentionally damage several components of the system. In this paper, a security risk analysis methodology is proposed consisting of vulnerability analysis and impact analysis. Vulnerability analysis is a method developed by security engineers to identify the attacks that are relevant for the system under study, and in this paper, the analysis is applied on the communications network topology of the electric grid automation system. Impact analysis is then performed through co-simulation of automation and the electric grid to assess the potential damage from the attacks. This paper makes an extensive review of vulnerability and impact analysis methods and relevant system modeling techniques from the fields of security and industrial automation engineering, with a focus on smart grid automation, and then applies and combines approaches to obtain a security risk analysis methodology. The methodology is demonstrated with a case study of fault location, isolation and supply restoration smart grid automation.

The addition of synchrophasors such as phasor measurement units (PMUs) to the existing power grid will enhance real-time monitoring and analysis of the grid. The PMU collects bus voltage, line current, and frequency measurements and uses the communication network to send the measurements to the respective substation(s)/control center(s). Since this approach relies on network infrastructure, possible cyber security vulnerabilities have to be addressed to ensure that is stable, secure, and reliable. In this paper, security vulnerabilities associated with a synchrophasor network in a benchmark IEEE 68 bus (New England/New York) power system model are examined. Currently known feasible attacks are demonstrated. Recommended testing and verification methods are also presented.

In this paper we propose a methodology and a prototype tool to evaluate web application security mechanisms. The methodology is based on the idea that injecting realistic vulnerabilities in a web application and attacking them automatically can be used to support the assessment of existing security mechanisms and tools in custom setup scenarios. To provide true to life results, the proposed vulnerability and attack injection methodology relies on the study of a large number of vulnerabilities in real web applications. In addition to the generic methodology, the paper describes the implementation of the Vulnerability & Attack Injector Tool (VAIT) that allows the automation of the entire process. We used this tool to run a set of experiments that demonstrate the feasibility and the effectiveness of the proposed methodology. The experiments include the evaluation of coverage and false positives of an intrusion detection system for SQL Injection attacks and the assessment of the effectiveness of two top commercial web application vulnerability scanners. Results show that the injection of vulnerabilities and attacks is indeed an effective way to evaluate security mechanisms and to point out not only their weaknesses but also ways for their improvement.

Most web applications have critical bugs (faults) affecting their security, which makes them vulnerable to attacks by hackers and organized crime. To prevent these security problems from occurring it is of utmost importance to understand the typical software faults. This paper contributes to this body of knowledge by presenting a field study on two of the most widely spread and critical web application vulnerabilities: SQL Injection and XSS. It analyzes the source code of security patches of widely used web applications written in weak and strong typed languages. Results show that only a small subset of software fault types, affecting a restricted collection of statements, is related to security. To understand how these vulnerabilities are really exploited by hackers, this paper also presents an analysis of the source code of the scripts used to attack them. The outcomes of this study can be used to train software developers and code inspectors in the detection of such faults and are also the foundation for the research of realistic vulnerability and attack injectors that can be used to assess security mechanisms, such as intrusion detection systems, vulnerability scanners, and static code analyzers.

A Wireless sensor network is a special type of Ad Hoc network, composed of a large number of sensor nodes spread over a wide geographical area. Each sensor node has the wireless communication capability and sufficient intelligence for making signal processing and dissemination of data from the collecting center .In this paper deals about redundancy management for improving network efficiency and query reliability in heterogeneous wireless sensor networks. The proposed scheme deals about finding a reliable path by using redundancy management algorithm and detection of unreliable nodes by discarding the path. The redundancy management algorithm finds the reliable path based on redundancy level, average distance between a source node and destination node and analyzes the redundancy level as the path and source redundancy. For finding the path from source CH to processing center we propose intrusion tolerance in the presence of unreliable nodes. Finally we applied our analyzed result to redundancy management algorithm to find the reliable path in which the network efficiency and Query success probability will be improved.

Cloud computing emerges as a new computing paradigm that aims to provide reliable, customized and quality of service guaranteed computation environments for cloud users. Applications and databases are moved to the large centralized data centers, called cloud. Due to resource virtualization, global replication and migration, the physical absence of data and machine in the cloud, the stored data in the cloud and the computation results may not be well managed and fully trusted by the cloud users. Most of the previous work on the cloud security focuses on the storage security rather than taking the computation security into consideration together. In this paper, we propose a privacy cheating discouragement and secure computation auditing protocol, or SecCloud, which is a first protocol bridging secure storage and secure computation auditing in cloud and achieving privacy cheating discouragement by designated verifier signature, batch verification and probabilistic sampling techniques. The detailed analysis is given to obtain an optimal sampling size to minimize the cost. Another major contribution of this paper is that we build a practical secure-aware cloud computing experimental environment, or SecHDFS, as a test bed to implement SecCloud. Further experimental results have demonstrated the effectiveness and efficiency of the proposed SecCloud.

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.

Hardware Trojan Threats (HTTs) are stealthy components embedded inside integrated circuits (ICs) with an intention to attack and cripple the IC similar to viruses infecting the human body. Previous efforts have focused essentially on systems being compromised using HTTs and the effectiveness of physical parameters including power consumption, timing variation and utilization for detecting HTTs. We propose a novel metric for hardware Trojan detection coined as HTT detectability metric (HDM) that uses a weighted combination of normalized physical parameters. HTTs are identified by comparing the HDM with an optimal detection threshold; if the monitored HDM exceeds the estimated optimal detection threshold, the IC will be tagged as malicious. As opposed to existing efforts, this work investigates a system model from a designer perspective in increasing the security of the device and an adversary model from an attacker perspective exposing and exploiting the vulnerabilities in the device. Using existing Trojan implementations and Trojan taxonomy as a baseline, seven HTTs were designed and implemented on a FPGA testbed; these Trojans perform a variety of threats ranging from sensitive information leak, denial of service to beat the Root of Trust (RoT). Security analysis on the implemented Trojans showed that existing detection techniques based on physical characteristics such as power consumption, timing variation or utilization alone does not necessarily capture the existence of HTTs and only a maximum of 57% of designed HTTs were detected. On the other hand, 86% of the implemented Trojans were detected with HDM. We further carry out analytical studies to determine the optimal detection threshold that minimizes the summation of false alarm and missed detection probabilities.

Phishing continues to remain a lucrative market for cyber criminals, mostly because of the vulnerable human element. Through emails and spoofed-websites, phishers exploit almost any opportunity using major events, considerable financial awards, fake warnings and the trusted reputation of established organizations, as a basis to gain their victims' trust. For many years, humans have often been referred to as the `weakest link' towards protecting information. To gain their victims' trust, phishers continue to use sophisticated looking emails and spoofed websites to trick them, and rely on their victims' lack of knowledge, lax security behavior and organizations' inadequate security measures towards protecting itself and their clients. As such, phishing security controls and vulnerabilities can arguably be classified into three main elements namely human factors (H), organizational aspects (O) and technological controls (T). All three of these elements have the common feature of human involvement and as such, security gaps are inevitable. Each element also functions as both security control and security vulnerability. A holistic framework towards combatting phishing is required whereby the human feature in all three of these elements is enhanced by means of a security education, training and awareness programme. This paper discusses the educational factors required to form part of a holistic framework, addressing the HOT elements as well as the relationships between these elements towards combatting phishing. The development of this framework uses the principles of design science to ensure that it is developed with rigor. Furthermore, this paper reports on the verification of the framework.

Sybil attack poses a serious threat to geographic routing. In this attack, a malicious node attempts to broadcast incorrect location information, identity and secret key information. A Sybil node can tamper its neighboring nodes for the purpose of converting them as malicious. As the amount of Sybil nodes increase in the network, the network traffic will seriously affect and the data packets will never reach to their destinations. To address this problem, researchers have proposed several schemes to detect Sybil attacks. However, most of these schemes assume costly setup such as the use of relay nodes or use of expensive devices and expensive encryption methods to verify the location information. In this paper, the authors present a method to detect Sybil attacks using Sequential Hypothesis Testing. The proposed method has been examined using a Greedy Perimeter Stateless Routing (GPSR) protocol with analysis and simulation. The simulation results demonstrate that the proposed method is robust against detecting Sybil attacks.

Sybil attack poses a serious threat to geographic routing. In this attack, a malicious node attempts to broadcast incorrect location information, identity and secret key information. A Sybil node can tamper its neighboring nodes for the purpose of converting them as malicious. As the amount of Sybil nodes increase in the network, the network traffic will seriously affect and the data packets will never reach to their destinations. To address this problem, researchers have proposed several schemes to detect Sybil attacks. However, most of these schemes assume costly setup such as the use of relay nodes or use of expensive devices and expensive encryption methods to verify the location information. In this paper, the authors present a method to detect Sybil attacks using Sequential Hypothesis Testing. The proposed method has been examined using a Greedy Perimeter Stateless Routing (GPSR) protocol with analysis and simulation. The simulation results demonstrate that the proposed method is robust against detecting Sybil attacks.

This paper deals with the robust H∞ cyber-attacks estimation problem for control systems under stochastic cyber-attacks and disturbances. The focus is on designing a H∞ filter which maximize the attack sensitivity and minimize the effect of disturbances. The design requires not only the disturbance attenuation, but also the residual to remain the attack sensitivity as much as possible while the effect of disturbance is minimized. A stochastic model of control system with stochastic cyber-attacks which satisfy the Markovian stochastic process is constructed. And we also present the stochastic attack models that a control system is possibly exposed to. Furthermore, applying H∞ filtering technique-based on linear matrix inequalities (LMIs), the paper obtains sufficient conditions that ensure the filtering error dynamic is asymptotically stable and satisfies a prescribed ratio between cyber-attack sensitivity and disturbance sensitivity. Finally, the results are applied to the control of a Quadruple-tank process (QTP) under a stochastic cyber-attack and a stochastic disturbance. The simulation results underline that the designed filters is effective and feasible in practical application.

The success of machine learning, particularly in supervised settings, has led to numerous attempts to apply it in adversarial settings such as spam and malware detection. The core challenge in this class of applications is that adversaries are not static data generators, but make a deliberate effort to evade the classifiers deployed to detect them. We investigate both the problem of modeling the objectives of such adversaries, as well as the algorithmic problem of accounting for rational, objective-driven adversaries. In particular, we demonstrate severe shortcomings of feature reduction in adversarial settings using several natural adversarial objective functions, an observation that is particularly pronounced when the adversary is able to substitute across similar features (for example, replace words with synonyms or replace letters in words). We offer a simple heuristic method for making learning more robust to feature cross-substitution attacks. We then present a more general approach based on mixed-integer linear programming with constraint generation, which implicitly trades off overfitting and feature selection in an adversarial setting using a sparse regularizer along with an evasion model. Our approach is the first method for combining an adversarial classification algorithm with a very general class of models of adversarial classifier evasion. We show that our algorithmic approach significantly outperforms state-of-the-art alternatives.

Stackelberg security game models and associated computational tools have seen deployment in a number of high- consequence security settings, such as LAX canine patrols and Federal Air Marshal Service. This deployment across essentially independent agencies raises a natural question: what global impact does the resulting strategic interaction among the defenders, each using a similar model, have? We address this question in two ways. First, we demonstrate that the most common solution concept of Strong Stackelberg equilibrium (SSE) can result in significant under-investment in security entirely because SSE presupposes a single defender. Second, we propose a framework based on a different solution concept which incorporates a model of interdependencies among targets, and show that in this framework defenders tend to over-defend, even under significant positive externalities of increased defense.

We introduce noncooperatively optimized tolerance (NOT), a game theoretic generalization of highly optimized tolerance (HOT), which we illustrate in the forest fire framework. As the number of players increases, NOT retains features of HOT, such as robustness and self-dissimilar landscapes, but also develops features of self-organized criticality. The system retains considerable robustness even as it becomes fractured, due in part to emergent cooperation between players, and at the same time exhibits increasing resilience against changes in the environment, giving rise to intermediate regimes where the system is robust to a particular distribution of adverse events, yet not very fragile to changes.