Bayesian signaling game based efficient security model for MANETs

Game Theory acts as a suitable tool offering promising solutions to security-related concerns in Mobile Ad Hoc Networks (i.e., MANETs). In MANETs, security forms a prominent concern as it includes nodes which are usually portable and require significant coordination between them. Further, the absence of physical organisation makes such networks susceptible to security breaches, hindering secure routing and execution among nodes. Game Theory approach has been manipulated in the current study to achieve an analytical view while addressing the security concerns in MANETs. This paper offers a Bayesian-Signaling game model capable of analysing the behaviour associated with regular as well as malicious nodes. In the proposed model, the utility of normal nodes has been increased while reducing the utility linked to malicious nodes. Moreover, the system employs a reputation system capable of stimulating best cooperation between the nodes. The regular nodes record incessantly to examine their corresponding nodes’ behaviours by using the belief system of Bayes-rules. On its comparison with existing schemes, it was revealed that the presented algorithm provides better identification of malicious nodes and attacks while delivering improved throughput and reduced false positive rate

Manifestation and mitigation of node misbehaviour in adhoc networks

Mobile adhoc network is signified as a boon for advance and future wireless communication system. Owing to its self-establishing network features and decentralization, the system can actually establish a wireless communication with vast range of connectivity with the other nodes. However, the system of MANET is also beheld with various technical impediments owing to its inherent dynamic topologies. Although there are abundant volume of research work, but very few have been able to effectively address the node misbehavior problems in MANET. The paper initially tries to draw a line between different types of nodes in MANETs based on their behavior characteristics, then reviews some of the significant contribution of the prior researches for addressing node misbehavior issues. A major emphasis is laid on is the researches which use game theory as a tool to study and address the misbehavior problems. The manuscript is developed considering some of the latest and standard evidences of past 5 years and finally discusses the open issues related to the problems

ECM-GT: design of efficient computational modelling based on game theoretical approach towards enhancing the security solutions in MANET

Game Theory is a useful tool for exploring the issues concerning Mobile Ad-Hoc Network (or MANET) security. In MANETs, coordination among the portable nodes is more significant, which encompasses their vulnerability challenges to several security assaults and the inability to run securely, when storing its resources and manage secure routing between the nodes. Hence, it is imperative to design an efficient routing protocol to secure all nodes from unknown behaviors. In the current research study, the game-theory approach is utilized for analytical purpose and addresses the security problems in MANETs. The game-theoretic approach is mainly adopted to find the malicious activities in the networks. In the proposed work, a Bayesian-Signaling game model is proposed which analyses the behavior of both regular/normal and malicious nodes. The game model proposed also provides the finest actions of autonomous tactics for every node. A Bayesian-Equilibrium (BE) offers the best solution for games to resolve the incomplete information by joining strategies and players payoff which form an equilibrium. By exploiting the BE mechanism, the system can detect the behavior of regular as well as malicious nodes. Therefore, Efficient ComputationalModelling based on Game Theory or ECM-GT methodology will reduce the utility of malicious nodes and increase the utility of regular nodes. Also, it stimulates the best co-operation among the nodes by exploiting the reputation system. On comparing our results with the existing systems, it was found that the proposed algorithm performed better in the detection of malicious nodes, throughput, false positive rate and detection of attacks

Security Issues of Mobile and Smart Wearable Devices

Mobile and smart devices (ranging from popular smartphones and tablets to wearable fitness trackers equipped with sensing, computing and networking capabilities) have proliferated lately and redefined the way users carry out their day-to-day activities. These devices bring immense benefits to society and boast improved quality of life for users. As mobile and smart technologies become increasingly ubiquitous, the security of these devices becomes more urgent, and users should take precautions to keep their personal information secure. Privacy has also been called into question as so many of mobile and smart devices collect, process huge quantities of data, and store them on the cloud as a matter of fact. Ensuring confidentiality, integrity, and authenticity of the information is a cybersecurity challenge with no easy solution. Unfortunately, current security controls have not kept pace with the risks posed by mobile and smart devices, and have proven patently insufficient so far. Thwarting attacks is also a thriving research area with a substantial amount of still unsolved problems. The pervasiveness of smart devices, the growing attack vectors, and the current lack of security call for an effective and efficient way of protecting mobile and smart devices. This thesis deals with the security problems of mobile and smart devices, providing specific methods for improving current security solutions. Our contributions are grouped into two related areas which present natural intersections and corresponds to the two central parts of this document: (1) Tackling Mobile Malware, and (2) Security Analysis on Wearable and Smart Devices. In the first part of this thesis, we study methods and techniques to assist security analysts to tackle mobile malware and automate the identification of malicious applications. We provide threefold contributions in tackling mobile malware: First, we introduce a Secure Message Delivery (SMD) protocol for Device-to-Device (D2D) networks, with primary objective of choosing the most secure path to deliver a message from a sender to a destination in a multi-hop D2D network. Second, we illustrate a survey to investigate concrete and relevant questions concerning Android code obfuscation and protection techniques, where the purpose is to review code obfuscation and code protection practices. We evaluate efficacy of existing code de-obfuscation tools to tackle obfuscated Android malware (which provide attackers with the ability to evade detection mechanisms). Finally, we propose a Machine Learning-based detection framework to hunt malicious Android apps by introducing a system to detect and classify newly-discovered malware through analyzing applications. The proposed system classifies different types of malware from each other and helps to better understanding how malware can infect devices, the threat level they pose and how to protect against them. Our designed system leverages more complete coverage of apps’ behavioral characteristics than the state-of-the-art, integrates the most performant classifier, and utilizes the robustness of extracted features. The second part of this dissertation conducts an in-depth security analysis of the most popular wearable fitness trackers on the market. Our contributions are grouped into four central parts in this domain: First, we analyze the primitives governing the communication between fitness tracker and cloud-based services. In addition, we investigate communication requirements in this setting such as: (i) Data Confidentiality, (ii) Data Integrity, and (iii) Data Authenticity. Second, we show real-world demos on how modern wearable devices are vulnerable to false data injection attacks. Also, we document successful injection of falsified data to cloud-based services that appears legitimate to the cloud to obtain personal benefits. Third, we circumvent End-to-End protocol encryption implemented in the most advanced and secure fitness trackers (e.g., Fitbit, as the market leader) through Hardware-based reverse engineering. Last but not least, we provide guidelines for avoiding similar vulnerabilities in future system designs