Biblio

Computer networks and surging advancements of innovative information technology construct a critical infrastructure for network transactions of business entities. Information exchange and data access though such infrastructure is scrutinized by adversaries for vulnerabilities that lead to cyber-attacks. This paper presents an agent-based system modelling to conceptualize and extract explicit and latent structure of the complex enterprise systems as well as human interactions within the system to determine common vulnerabilities of the entity. The model captures emergent behavior resulting from interactions of multiple network agents including the number of workstations, regular, administrator and third-party users, external and internal attacks, defense mechanisms for the network setting, and many other parameters. A risk-based approach to modelling cybersecurity of a business entity is utilized to derive the rate of attacks. A neural network model will generalize the type of attack based on network traffic features allowing dynamic state changes. Rules of engagement to generate self-organizing behavior will be leveraged to appoint a defense mechanism suitable for the attack-state of the model. The effectiveness of the model will be depicted by time-state chart that shows the number of affected assets for the different types of attacks triggered by the entity risk and the time it takes to revert into normal state. The model will also associate a relevant cost per incident occurrence that derives the need for enhancement of security solutions.

Cyber incidents are occurring every day using various attack strategies. Deploying security solutions with strong configurations will reduce the attack surface and improve the forensic readiness, but will increase the security overhead and cost. In contrast, using moderate or low security configurations will reduce that overhead, but will inevitably decrease the investigation readiness. To avoid the use of cost-prohibitive approaches in developing forensic-ready systems, we present in this paper a game theoretic approach for deploying an investigation-ready infrastructure. The proposed game is a non-cooperative two-player game between an adaptive cyber defender that uses a cognitive security solution to increase the investigation readiness and reduce the attackers' untraceability, and a cyber attacker that wants to execute non-provable attacks with a low cost. The cognitive security solution takes its strategic decision, mainly based on its ability to make forensic experts able to differentiate between provable identifiable, provable non-identifiable, and non-provable attack scenarios, starting from the expected evidences to be generated. We study the behavior of the two strategic players, looking for a mixed Nash equilibrium during competition and computing the probabilities of attacking and defending. A simulation is conducted to prove the efficiency of the proposed model in terms of the mean percentage of gained security cost, the number of stepping stones that an attacker creates and the rate of defender false decisions compared to two different approaches.

In order to the development of IoT, IETF developed a standard named 6LoWPAN for increase the usage of IPv6 to the tiny and smart objects with low power. Generally, the 6LoWPAN radio link needs end to end (e2e) security for its IPv6 communication process. 6LoWPAN requires light weight variant of security solutions in IPSec. A new security approach of 6LoWPAN at adaptation layer to provide e2e security with light weight IPSec. The existing security protocol IPsec is not suitable for its 6LoWPAN IoT environment because it has heavy restrictions on memory, power, duty cycle, additional overhead transmission. The IPSec had packet overhead problem due to share the secret key between two communicating peers by IKE (Internet Key Exchange) protocol. Hence the existing security protocol IPSec solutions are not suitable for lightweight-based security need in 6LoWPAN IoT. This paper describes 6LowPSec protocol with AES-CCM (Cipher block chaining Message authentication code with Counter mode) cryptographic algorithm with key size of 128 bits with minimum power consumption and duty cycle.

Cyber attacks against automobiles have increased over the last decade due to the expansion in attack surfaces. This is the result of modern automobiles having connections such as Bluetooth, WiFi, and other broadband services. While there has been numerous proposed solutions in the literature, none have been widely adopted as maintaining real-time message deliverability in the Controller Area Networks (CAN) outweighs proposed security solutions. Through iterative research, we have developed a solution which mitigates an attacker's impact on the CAN bus by using CAN's inherent features of arbitration, error detection and signaling, and fault confinement mechanism. The solution relies on an access controller and message priority thresholds added to the CAN data-link layer. The results provide no time delay for non-malicious traffic and mitigates bus impact of a subverted node attempting to fabricate messages at an unauthorized priority level.

Hardware vulnerabilities are often due to design mistakes because the designer does not sufficiently consider potential security vulnerabilities at the design stage. As a result, various security solutions have been developed to protect ICs, among which the language-based hardware security verification serves as a promising solution. The verification process will be performed while compiling the HDL of the design. However, similar to other formal verification methods, the language-based approach also suffers from scalability issue. Furthermore, existing solutions either lead to hardware overhead or are not designed for vulnerable or malicious logic detection. To alleviate these challenges, we propose a new language based framework, QIF-Verilog, to evaluate the trustworthiness of a hardware system at register transfer level (RTL). This framework introduces a quantified information flow (QIF) model and extends Verilog type systems to provide more expressiveness in presenting security rules; QIF is capable of checking the security rules given by the hardware designer. Secrets are labeled by the new type and then parsed to data flow, to which a QIF model will be applied. To demonstrate our approach, we design a compiler for QIF-Verilog and perform vulnerability analysis on benchmarks from Trust-Hub and OpenCore. We show that Trojans or design faults that leak information from circuit outputs can be detected automatically, and that our method evaluates the security of the design correctly.

Security challenges present in Machine-to-Machine Communication (M2M-C) and big data paradigm are fundamentally different from conventional network security challenges. In M2M-C paradigms, “Trust” is a vital constituent of security solutions that address security threats and for such solutions,it is important to quantify and evaluate the amount of trust in the information and its source. In this work, we focus on Machine Learning (ML) Based Trust (MLBT) evaluation model for detecting malicious activities in a vehicular Based M2M-C (VBM2M-C) network. In particular, we present an Entropy Based Feature Engineering (EBFE) coupled Extreme Gradient Boosting (XGBoost) model which is optimized with Binary Particle Swarm optimization technique. Based on three performance metrics, i.e., Accuracy Rate (AR), True Positive Rate (TPR), False Positive Rate (FPR), the effectiveness of the proposed method is evaluated in comparison to the state-of-the-art ensemble models, such as XGBoost and Random Forest. The simulation results demonstrates the superiority of the proposed model with approximately 10% improvement in accuracy, TPR and FPR, with reference to the attacker density of 30% compared with the start-of-the-art algorithms.

Deep Packet Inspection (DPI) is instrumental in investigating the presence of malicious activity in network traffic and most existing DPI tools work on unencrypted payloads. As the internet is moving towards fully encrypted data-transfer, there is a critical requirement for privacy-aware techniques to efficiently decrypt network payloads. Until recently, passive proxying using certain aspects of TLS 1.2 were used to perform decryption and further DPI analysis. With the introduction of TLS 1.3 standard that only supports protocols with Perfect Forward Secrecy (PFS), many such techniques will become ineffective. Several security solutions will be forced to adopt active proxying that will become a big-data problem considering the velocity and veracity of network traffic involved. We have developed an ABAC (Attribute Based Access Control) framework that efficiently supports existing DPI tools while respecting user's privacy requirements and organizational policies. It gives the user the ability to accept or decline access decision based on his privileges. Our solution evaluates various observed and derived attributes of network connections against user access privileges using policies described with semantic technologies. In this paper, we describe our framework and demonstrate the efficacy of our technique with the help of use-case scenarios to identify network connections that are candidates for Deep Packet Inspection. Since our technique makes selective identification of connections based on policies, both processing and memory load at the gateway will be reduced significantly.

With the rapid technological growth in the present context, Internet of Things (IoT) has attracted the worldwide attention and has become pivotal technology in the smart computing environment of 21st century. IoT provides a virtual view of real-life things in resource-constrained environment where security and privacy are of prime concern. Lightweight cryptography provides security solutions in resource-constrained environment of IoT. Several software and hardware implementation of lightweight ciphers have been presented by different researchers in this area. This paper presents a comparative analysis of several lightweight cryptographic solutions along with their pros and cons, and their future scope. The comparative analysis may further help in proposing a 32-bit ultra-lightweight block cipher security model for IoT enabled applications in the smart environment.

Information Centric Networking (ICN) changed the communication model from host-based to content-based to cope with the high volume of traffic due to the rapidly increasing number of users, data objects, devices, and applications. ICN communication model requires new security solutions that will be integrated with ICN architectures. In this paper, we present a security framework to manage ICN traffic by detecting, preventing, and responding to ICN attacks. The framework consists of three components: availability, access control, and privacy. The availability component ensures that contents are available for legitimate users. The access control component allows only legitimate users to get restrictedaccess contents. The privacy component prevents attackers from knowing content popularities or user requests. We also show our specific solutions as examples of the framework components.

Software Defined Networks (SDNs) is a new networking paradigm that has gained a lot of attention in recent years especially in implementing data center networks and in providing efficient security solutions. The popularity of SDN and its attractive security features suggest that it can be used in the context of smart grid systems to address many of the vulnerabilities and security problems facing such critical infrastructure systems. This paper studies the impact of different cyber attacks that can target smart grid communication network which is implemented as a software defined network on the operation of the smart grid system in general. In particular, we perform different attack scenarios including DDoS attacks, location highjacking and link overloading against SDN networks of different controller types that include POX, Floodlight and RYU. Our experiments were carried out using the mininet simulator. The experiments show that SDN-enabled smartgrid systems are vulnerable to different types of attacks.

Software defined networking promises network operators to dramatically simplify network management. It provides flexibility and innovation through network programmability. With SDN, network management moves from codifying functionality in terms of low-level device configuration to building software that facilitates network management and debugging[1]. SDN provides new techniques to solve long-standing problems in networking like routing by separating the complexity of state distribution from network specification. Despite all the hype surrounding SDNs, exploiting its full potential is demanding. Security is still the major issue and a striking challenge that reduces the growth of SDNs. Moreover the introduction of various architectural components and up cycling of novel entities of SDN poses new security issues and threats. SDN is considered as major target for digital threats and cyber-attacks[2] and have more devastating effects than simple networks. Initial SDN design doesn't considered security as its part; therefore, it must be raised on the agenda. This article discusses the security solutions proposed to secure SDNs. We categorize the security solutions in the article by presenting a thematic taxonomy based on SDN architectural layers/interfaces[3], security measures and goals, simulation framework. Moreover, the literature also points out the possible attacks[2] targeting different layers/interfaces of SDNs. For securing SDNs, the potential requirements and their key enablers are also identified and presented. Also, the articles sketch the design of secure and dependable SDNs. At last, we discuss open issues and challenges of SDN security that may be rated appropriate to be handled by professionals and researchers in the future.

Web Services can be invoked from anywhere through internet without having enough knowledge about the implementation details. In some cases, single service cannot accomplish user needs. One or more services must be composed which together satisfy the user needs. Therefore, security is the most important concern not only at single service level but also at composition level. Several attacks are possible on SOAP messages communicated among Web Services because of their standardized interfaces. Examples of Web Service attacks are oversize payload, SOAPAction spoofing, XML injection, WS-Addressing spoofing, etc. Most of the existing works provide solution to ensure basic security features of Web Services such as confidentiality, integrity, authentication, authorization, and non-repudiation. Very few of the existing works provide solutions such as schema validation and schema hardening for attacks on Web Services. But these solutions do not address and provide attack specific solutions for SOAP messages communicated between Web Service. Hence, it is proposed to provide solutions for two of the prevailing Web Service attacks. Since new types of Web Service attacks are evolving over time, the proposed security solutions are implemented as APIs that are pluggable in any server where the Web Service is deployed.