Secure-GLOR: An adaptive secure routing protocol for dynamic wireless mesh networks

© 2017 IEEE. With the dawn of a new era, digital security has become one of the most essential part of any network. Be it a physical network, virtual network or social network, the demand for secure data transmission is ever increasing. Wireless mesh networks also stand the same test of security as the legacy networks. This paper presents a secure version of the Geo-Location Oriented Routing (GLOR) protocol for wireless mesh networks, incorporating a multilevel security framework. It implements authentication using the new features of the network model and enables encryption throughout the network to provide high levels of security

DEMISe: interpretable deep extraction and mutual information selection techniques for IoT intrusion detection

Recent studies have proposed that traditional security technology – involving pattern-matching algorithms that check predefined pattern sets of intrusion signatures – should be replaced with sophisticated adaptive approaches that combine machine learning and behavioural analytics. However, machine learning is performance driven, and the high computational cost is incompatible with the limited computing power, memory capacity and energy resources of portable IoT-enabled devices. The convoluted nature of deep-structured machine learning means that such models also lack transparency and interpretability. The knowledge obtained by interpretable learners is critical in security software design. We therefore propose two novel models featuring a common Deep Extraction and Mutual Information Selection (DEMISe) element which extracts features using a deep-structured stacked autoencoder, prior to feature selection based on the amount of mutual information (MI) shared between each feature and the class label. An entropy-based tree wrapper is used to optimise the feature subsets identified by the DEMISe element, yielding the DEMISe with Tree Evaluation and Regression Detection (DETEReD) model. This affords ‘white box’ insight, and achieves a time to build of 603 seconds, a 99.07% detection rate, and 98.04% model accuracy. When tested against AWID, the best-referenced intrusion detection dataset, the new models achieved a test error comparable to or better than state-of-the-art machine-learning models, with a lower computational cost and higher levels of transparency and interpretability

Formal verification and access control approach of an IoT protocol

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2017.Protocolos de Segurança estão na nossa rotina diária e exemplos distosão compras utilizando o cartão de crédito, eleição eletrônica, redes sem fio e etc. O primeiro objetivo deste trabalho é a verificação formal dos aspectos de segurança de um protocolo voltado para Wireless Sensor Networks (WSN). O Trustful Space-Time Protocol (TSTP) engloba a maioria das características necessárias para aplicações WSN como por exemplo controle de acesso, roteamento geográfico de pacotes, estimativa de localização, relógio precisamente sincronizado, canais de comunicação segura e um esquema de distribuição de chaves entre o gateway e os sensores. Após a análise formal do protocolo de distribuição de chaves do TSTP usando Proverif, nós encontramos duas falhas de segurança: uma relacionada ao componente de sincronização de tempo e outra relacionada ao método mac-then-encrypt empregado. Com as falhas encontradas nós propómos uma versão melhorada do protocolo de distribuição de chaves. O segundo objetivo é criar um esquema de controle de acesso sensível ao contexto para dispositivos Internet de Coisas(IoC) usando TSTP como canal de comunicação. O esquema da política foi projetado para um cenário Smart Campus e seu contexto. Aproveitamos os recursos do TSTP para adicionar dados de tempo e espaço como contexto para o nosso modelo. Após o desenho do modelo de política, descrevemos seu modelo simbólico e fizemos uma análise formal para ter certeza de que os valores das propriedades de contexto não foram adulterados.Abstract : Security protocols are included in our every day routine. A few examplesare credit card purchases, e-voting, wireless networks, etc. Thefirst goal of this dissertation is the formal verification of the securityaspects of a cross-layer, application-oriented communication protocolfor Wireless Sensor Networks (WSN). The Trustful Space-Time Protocol(TSTP) encompasses a majority of features recurrently needed byWSN applications like medium access control, geographic routing, locationestimation, precise time synchronization, secure communicationchannels and a key distribution scheme between sensors and the sink.After the security protocol analysis of TSTP?s key distribution protocolusing ProVerif we were able to find two security flaws: one related tothe time synchronization component and another being a bad approachrelated to a mac-then-encrypt method employed. With our findingswe propose an improved version of the key distribution protocol. Thesecond goal is to create a context-aware access control scheme for Internetof Things(IoT) devices using TSTP as a communication channel.The policy?s scheme was designed for a Smart Campus scenario andits context. We take advantage of TSTP?s features to add time andspace data as context for our model too. After the design of the policymodel, we described its symbolic model and we did a formal analysisto be sure that the context properties values were not tampered

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

The Treatment of Advanced Persistent Threats on Windows Based Systems

Advanced Persistent Threat (APT) is the name given to individuals or groups who write malicious software (malware) and who have the intent to perform actions detrimental to the victim or the victims' organisation. This thesis investigates ways in which it is possible to treat APTs before, during and after the malware has been laid down on the victim's computer. The scope of the thesis is restricted to desktop and laptop computers with hard disk drives. APTs have different motivations for their work and this thesis is agnostic towards their origin and intent. Anti-malware companies freely present the work of APTs in many ways but summarise mainly in the form of white papers. Individually, pieces of these works give an incomplete picture of an APT but in aggregate it is possible to construct a view of APT families and pan-APT commonalities by comparing and contrasting the work of many anti-malware companies; it as if there are alot of the pieces of a jigsaw puzzle but there is no box lid available with the complete picture. In addition, academic papers provide proof of concept attacks and observations, some of which may become used by malware writers. Gaps in, and extensions to, the public knowledge may be filled through inference, implication, interpolation and extrapolation and form the basis for this thesis. The thesis presents a view of where APTs lie on windows-based systems. It uses this view to create and build generic views of where APTs lie on Hard Disc Drives on Windows based systems using the Lockheed Martin Cyber Kill Chain. This is then used to treat APTs on Windows based IT systems using purpose-built software in such a way that the malware is negated by. The thesis does not claim to find all malware on but it demonstrates how to increase the cost of doing business for APTs, for example by overwriting unused disc space so APTs cannot place malware there. The software developed was able to find Indicators of Compromise on all eight Hard Disc Drives provided for analysis. Separately, from a corpus of 228 files known to be associated with malware it identified approximately two thirds as Indicators of Compromise

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets