Biblio

Found 7524 results

Filters: Keyword is Metrics  [Clear All Filters]
2020-07-03
Pan, Jonathan.  2019.  Physical Integrity Attack Detection of Surveillance Camera with Deep Learning based Video Frame Interpolation. 2019 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS). :79—85.

Surveillance cameras, which is a form of Cyber Physical System, are deployed extensively to provide visual surveillance monitoring of activities of interest or anomalies. However, these cameras are at risks of physical security attacks against their physical attributes or configuration like tampering of their recording coverage, camera positions or recording configurations like focus and zoom factors. Such adversarial alteration of physical configuration could also be invoked through cyber security attacks against the camera's software vulnerabilities to administratively change the camera's physical configuration settings. When such Cyber Physical attacks occur, they affect the integrity of the targeted cameras that would in turn render these cameras ineffective in fulfilling the intended security functions. There is a significant measure of research work in detection mechanisms of cyber-attacks against these Cyber Physical devices, however it is understudied area with such mechanisms against integrity attacks on physical configuration. This research proposes the use of the novel use of deep learning algorithms to detect such physical attacks originating from cyber or physical spaces. Additionally, we proposed the novel use of deep learning-based video frame interpolation for such detection that has comparatively better performance to other anomaly detectors in spatiotemporal environments.

2018-07-09
Anirudh Narasimman, Qiaozhi Wang, Fengjun Li, Dongwon Lee, Bo Luo.  2019.  Arcana: Enabling Private Posts on Public Microblog Platforms. 34rd International Information Security and Privacy Conference (IFIP SEC).

Many popular online social networks, such as Twitter, Tum-blr, and Sina Weibo, adopt too simple privacy models to satisfy users’diverse needs for privacy protection. In platforms with no (i.e., completely open) or binary (i.e., “public” and “friends-only”) access con-trol, users cannot control the dissemination boundary of the contentthey share. For instance, on Twitter, tweets in “public” accounts areaccessible to everyone including search engines, while tweets in “pro-tected” accounts are visible toallthe followers. In this work, we presentArcanato  enable  fine-grained access control for social network content sharing. In particular, we target the Twitter platform and intro-duce the “private tweet” function, which allows users to disseminateparticular tweets to designated group(s) of followers. Arcana employsCiphertext-Policy Attribute-based Encryption (CP-ABE) to implement social circle detection and private tweet encryption so that  access-controlled  tweets  are  only  readable  by  designated  recipients.  To  bestealthy, Arcana further embeds the protected content as digital water-marks in image tweets. We have implemented the Arcana prototype asa Chrome browser plug-in, and demonstrated its flexibility and effec-tiveness. Different from existing approaches that require trusted third-parties or additional server/broker/mediator, Arcana is light-weight andcompletely transparent to Twitter – all the communications, includingkey distribution and private tweet dissemination, are exchanged as Twit-ter messages. Therefore, with small API modifications, Arcana could beeasily ported to other online social networking platforms to support fine-grained access control.

2020-07-03
Lisova, Elena, El Hachem, Jamal, Causevic, Aida.  2019.  Investigating Attack Propagation in a SoS via a Service Decomposition. 2019 IEEE World Congress on Services (SERVICES). 2642-939X:9—14.

A term systems of systems (SoS) refers to a setup in which a number of independent systems collaborate to create a value that each of them is unable to achieve independently. Complexity of a SoS structure is higher compared to its constitute systems that brings challenges in analyzing its critical properties such as security. An SoS can be seen as a set of connected systems or services that needs to be adequately protected. Communication between such systems or services can be considered as a service itself, and it is the paramount for establishment of a SoS as it enables connections, dependencies, and a cooperation. Given that reliable and predictable communication contributes directly to a correct functioning of an SoS, communication as a service is one of the main assets to consider. Protecting it from malicious adversaries should be one of the highest priorities within SoS design and operation. This study aims to investigate the attack propagation problem in terms of service-guarantees through the decomposition into sub-services enriched with preconditions and postconditions at the service levels. Such analysis is required as a prerequisite for an efficient SoS risk assessment at the design stage of the SoS development life cycle to protect it from possibly high impact attacks capable of affecting safety of systems and humans using the system.

2020-01-29
Hoang Hai Nguyen, Kartik Palani, David Nicol.  2019.  Extensions of Network Reliability Analysis. 49th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2020). :88-99.

Network reliability studies properties of networks subjected to random failures of their components. It has been widely adopted to modeling and analyzing real-world problems across different domains, such as circuit design, genomics, databases, information propagation, network security, and many others. Two practical situations that usually arise from such problems are (i) the correlation between component failures and (ii) the uncertainty in failure probabilities. Previous work captured correlations by modeling component reliability using general Boolean expression of Bernoulli random variables. This paper extends such a model to address the second problem, where we investigate the use of Beta distributions to capture the variance of uncertainty. We call this new formalism the Beta uncertain graph. We study the reliability polynomials of Beta uncertain graphs as multivariate polynomials of Beta random variables and demonstrate the use of the model on two realistic examples. We also observe that the reliability distribution of a monotone Beta uncertain graph can be approximated by a Beta distribution, usually with high accuracy. Numerical results from Monte Carlo simulation of an approximation scheme and from two case studies strongly support this observation.

2020-01-21
Jain, Jay Kumar, Chauhan, Dipti.  2019.  Analytical Study on Mobile Ad Hoc Networks for IPV6. 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU). :1–6.
The ongoing progressions in wireless innovation have lead to the advancement of another remote framework called Mobile Ad hoc Networks. The Mobile Ad hoc Network is a self arranging system of wireless gadgets associated by wireless connections. The traditional protocol, for example, TCP/IP has restricted use in Mobile impromptu systems in light of the absence of portability and assets. This has lead to the improvement of many steering conventions, for example, proactive, receptive and half breed. One intriguing examination zone in MANET is steering. Steering in the MANETs is a testing assignment and has gotten a colossal measure of consideration from examines. An uncommon consideration is paid on to feature the combination of MANET with the critical highlights of IPv6, for example, coordinated security, start to finish correspondence. This has prompted advancement of various directing conventions for MANETs, and every creator of each developed convention contends that the technique proposed gives an improvement over various distinctive systems considered in the writing for a given system situation. In this way, it is very hard to figure out which conventions may perform best under various diverse system situations, for example, expanding hub thickness and traffic. In this paper, we give the ongoing expository investigation on MANETs for IPV6 systems.
2020-10-29
Mintu, Singh, Gursharan, Malhi, Simarjit Singh, Mahajan, Makul, Batra, Salil, Bath, Ranbir Singh.  2019.  Anatomization of Detection and Performance Measures Techniques for Flooding Attacks using Routing Protocols in MANETs. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :160—167.
Mobile ad-hoc network (MANETS) is generally appropriate in different territories like military tactical network, educational, home and entertainment and emergency operations etc. The MANETSs are simply the disintegration and designing kind of system in this portable hubs coming up and out the system whenever. Because of decentralized creation of the network, security, routing and Standard of service are the three noteworthy issues. MANETSs are helpless against security attack in light of the decentralized validation. The mobile hubs can enter or out the system and at some point malicious hubs enter the system, which are capable to trigger different dynamic and inactive attack. The flooding attack is the dynamic sort of attack in which malicious hubs transfers flooding packets on the medium. Because of this, medium gets over-burden and packets drop may happen inside the system. This decreases the throughput and increased packet loss. In this paper we illustrated different techniques and proposed various methods responsible for flooding attack. Our commitment in this paper is that we have investigated various flooding attacks in MANETs, their detection techniques with performance measure parameters.
2020-02-10
Korzhik, Valery, Duy Cuong, Nguyen, Morales-Luna, Guillermo.  2019.  Cipher Modification Against Steganalysis Based on NIST Tests. 2019 24th Conference of Open Innovations Association (FRUCT). :179–186.

Part of our team proposed a new steganalytic method based on NIST tests at MMM-ACNS 2017 [1], and it was encouraged to investigate some cipher modifications to prevent such types of steganalysis. In the current paper, we propose one cipher modification based on decompression by arithmetic source compression coding. The experiment shows that the current proposed method allows to protect stegosystems against steganalysis based on NIST tests, while security of the encrypted embedded messages is kept. Protection of contemporary image steganography based on edge detection and modified LSB against NIST tests steganalysis is also presented.

2020-01-20
Jasim, Anwar Chitheer, Hassoon, Imad Ali, Tapus, Nicolae.  2019.  Cloud: privacy For Locations Based-services' through Access Control with dynamic multi-level policy. 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT). :1911–1916.

LBSs are Location-Based Services that provide certain service based on the current or past user's location. During the past decade, LBSs have become more popular as a result of the widespread use of mobile devices with position functions. Location information is a secondary information that can provide personal insight about one's life. This issue associated with sharing of data in cloud-based locations. For example, a hospital is a public space and the actual location of the hospital does not carry any sensitive information. However, it may become sensitive if the specialty of the hospital is analyzed. In this paper we proposed design presents a combination of methods for providing data privacy protection for location-based services (LBSs) with the use of cloud service. The work built in zero trust and we start to manage the access to the system through different levels. The proposal is based on a model that stores user location data in supplementary servers and not in non-trustable third-party applications. The approach of the present research is to analyze the privacy protection possibilities through data partitioning. The data collected from the different recourses are distributed into different servers according to the partitioning model based on multi-level policy. Access is granted to third party applications only to designated servers and the privacy of the user profile is also ensured in each server, as they are not trustable.

2020-02-18
Quan, Guocong, Tan, Jian, Eryilmaz, Atilla.  2019.  Counterintuitive Characteristics of Optimal Distributed LRU Caching Over Unreliable Channels. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. :694–702.
Least-recently-used (LRU) caching and its variants have conventionally been used as a fundamental and critical method to ensure fast and efficient data access in computer and communication systems. Emerging data-intensive applications over unreliable channels, e.g., mobile edge computing and wireless content delivery networks, have imposed new challenges in optimizing LRU caching systems in environments prone to failures. Most existing studies focus on reliable channels, e.g., on wired Web servers and within data centers, which have already yielded good insights with successful algorithms on how to reduce cache miss ratios. Surprisingly, we show that these widely held insights do not necessarily hold true for unreliable channels. We consider a single-hop multi-cache distributed system with data items being dispatched by random hashing. The objective is to achieve efficient cache organization and data placement. The former allocates the total memory space to each of the involved caches. The latter decides data routing strategies and data replication schemes. Analytically we characterize the unreliable LRU caches by explicitly deriving their asymptotic miss probabilities. Based on these results, we optimize the system design. Remarkably, these results sometimes are counterintuitive, differing from the ones obtained for reliable caches. We discover an interesting phenomenon: asymmetric cache organization is optimal even for symmetric channels. Specifically, even when channel unreliability probabilities are equal, allocating the cache spaces unequally can achieve a better performance. We also propose an explicit unequal allocation policy that outperforms the equal allocation. In addition, we prove that splitting the total cache space into separate LRU caches can achieve a lower asymptotic miss probability than resource pooling that organizes the total space in a single LRU cache. These results provide new and even counterintuitive insights that motivate novel designs for caching systems over unreliable channels. They can potentially be exploited to further improve the system performance in real practice.
2020-06-29
Ateş, Çağatay, Özdel, Süleyman, Yıldırım, Metehan, Anarım, Emin.  2019.  DDoS Attack Detection Using Greedy Algorithm and Frequency Modulation. 2019 27th Signal Processing and Communications Applications Conference (SIU). :1–4.
Distributed Denial of Service (DDoS) attack is one of the major threats to the network services. In this paper, we propose a DDoS attack detection algorithm based on the probability distributions of source IP addresses and destination IP addresses. According to the behavior of source and destination IP addresses during DDoS attack, the distance between these features is calculated and used.It is calculated with using the Greedy algorithm which eliminates some requirements associated with Kullback-Leibler divergence such as having the same rank of the probability distributions. Then frequency modulation is proposed in the detection phase to reduce false alarm rates and to avoid using static threshold. This algorithm is tested on the real data collected from Boğaziçi University network.
2020-02-18
Fattahi, Saeideh, Yazdani, Reza, Vahidipour, Seyyed Mehdi.  2019.  Discovery of Society Structure in A Social Network Using Distributed Cache Memory. 2019 5th International Conference on Web Research (ICWR). :264–269.

Community structure detection in social networks has become a big challenge. Various methods in the literature have been presented to solve this challenge. Recently, several methods have also been proposed to solve this challenge based on a mapping-reduction model, in which data and algorithms are divided between different process nodes so that the complexity of time and memory of community detection in large social networks is reduced. In this paper, a mapping-reduction model is first proposed to detect the structure of communities. Then the proposed framework is rewritten according to a new mechanism called distributed cache memory; distributed cache memory can store different values associated with different keys and, if necessary, put them at different computational nodes. Finally, the proposed rewritten framework has been implemented using SPARK tools and its implementation results have been reported on several major social networks. The performed experiments show the effectiveness of the proposed framework by varying the values of various parameters.

2020-04-03
Perveen, Abida, Patwary, Mohammad, Aneiba, Adel.  2019.  Dynamically Reconfigurable Slice Allocation and Admission Control within 5G Wireless Networks. 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring). :1—7.
Serving heterogeneous traffic demand requires efficient resource utilization to deliver the promises of 5G wireless network towards enhanced mobile broadband, massive machine type communication and ultra-reliable low-latency communication. In this paper, an integrated user application-specific demand characteristics as well as network characteristics evaluation based online slice allocation model for 5G wireless network is proposed. Such characteristics include, available bandwidth, power, quality of service demand, service priority, security sensitivity, network load, predictive load etc. A degree of intra-slice resource sharing elasticity has been considered based on their availability. The availability has been assessed based on the current availability as well as forecasted availability. On the basis of application characteristics, an admission control strategy has been proposed. An interactive AMF (Access and Mobility Function)- RAN (Radio Access Network) information exchange has been assumed. A cost function has been derived to quantify resource allocation decision metric that is valid for both static and dynamic nature of user and network characteristics. A dynamic intra-slice decision boundary estimation model has been proposed. A set of analytical comparative results have been attained in comparison to the results available in the literature. The results suggest the proposed resource allocation framework performance is superior to the existing results in the context of network utility, mean delay and network grade of service, while providing similar throughput. The superiority reported is due to soft nature of the decision metric while reconfiguring slice resource block-size and boundaries.
2021-01-18
Barbareschi, M., Barone, S., Mazzeo, A., Mazzocca, N..  2019.  Efficient Reed-Muller Implementation for Fuzzy Extractor Schemes. 2019 14th International Conference on Design Technology of Integrated Systems In Nanoscale Era (DTIS). :1–2.
Nowadays, physical tampering and counterfeiting of electronic devices are still an important security problem and have a great impact on large-scale and distributed applications, such as Internet-of-Things. Physical Unclonable Functions (PUFs) have the potential to be a fundamental means to guarantee intrinsic hardware security, since they promise immunity against most of known attack models. However, inner nature of PUF circuits hinders a wider adoption since responses turn out to be noisy and not stable during time. To overcome this issue, most of PUF implementations require a fuzzy extraction scheme, able to recover responses stability by exploiting error correction codes (ECCs). In this paper, we propose a Reed-Muller (RM) ECC design, meant to be embedded into a fuzzy extractor, that can be efficiently configured in terms of area/delay constraints in order to get reliable responses from PUFs. We provide implementation details and experimental evidences of area/delay efficiency through syntheses on medium-range FPGA device.
2020-10-29
Kaur, Jasleen, Singh, Tejpreet, Lakhwani, Kamlesh.  2019.  An Enhanced Approach for Attack Detection in VANETs Using Adaptive Neuro-Fuzzy System. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :191—197.
Vehicular Ad-hoc Networks (VANETs) are generally acknowledged as an extraordinary sort of Mobile Ad hoc Network (MANET). VANETs have seen enormous development in a decade ago, giving a tremendous scope of employments in both military and in addition non-military personnel exercises. The temporary network in the vehicles can likewise build the driver's capability on the road. In this paper, an effective information dispersal approach is proposed which enhances the vehicle-to-vehicle availability as well as enhances the QoS between the source and the goal. The viability of the proposed approach is shown with regards to the noteworthy gets accomplished in the parameters in particular, end to end delay, packet drop ratio, average download delay and throughput in comparison with the existing approaches.
2020-06-26
Gupta, Shubhi, Vashisht, Swati, Singh, Divya, kushwaha, Pradeep.  2019.  Enhancing Big Data Security using Elliptic Curve Cryptography. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :348—351.

Withgrowing times and technology, and the data related to it is increasing on daily basis and so is the daunting task to manage it. The present solution to this problem i.e our present databases, are not the long-term solutions. These data volumes need to be stored safely and retrieved safely to use. This paper presents an overview of security issues for big data. Big Data encompasses data configuration, distribution and analysis of the data that overcome the drawbacks of traditional data processing technology. Big data manages, stores and acquires data in a speedy and cost-effective manner with the help of tools, technologies and frameworks.

2020-02-10
Hasan, Jasim, Zeki, Ahmed M., Alharam, Aysha, Al-Mashhur, Nuha.  2019.  Evaluation of SQL Injection Prevention Methods. 2019 8th International Conference on Modeling Simulation and Applied Optimization (ICMSAO). :1–6.
In the last few years, the usage and dependency on web applications and websites has significantly increased across a number of different areas such as online banking, shopping, financial transactions etc. amongst the several other areas. This has even directly multiplied the threat of SQL injection issue. A number of past studies have suggested that SQL injection should be handled as effectively as possible in order to avoid long term threats and dangers. This paper in specific attempts to discuss and evaluate some of the main SQL injection prevention methods.
2020-07-30
Bays, Jason, Karabiyik, Umit.  2019.  Forensic Analysis of Third Party Location Applications in Android and iOS. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). :1—6.
Location sharing applications are becoming increasingly common. These applications allow users to share their own locations and view contacts’ current locations on a map. Location applications are commonly used by friends and family members to view Global Positioning System (GPS) location of an individual, but valuable forensic evidence may exist in this data when stored locally on smartphones. This paper aims to discover forensic artifacts from two popular third-party location sharing applications on iOS and Android devices. Industry standard mobile forensic suites are utilized to discover if any locally stored data could be used to assist investigations reliant on knowing the past location of a suspect. Security issues raised regarding the artifacts found during our analysis is also discussed.
2020-11-16
Zhang, C., Xu, C., Xu, J., Tang, Y., Choi, B..  2019.  GEMˆ2-Tree: A Gas-Efficient Structure for Authenticated Range Queries in Blockchain. 2019 IEEE 35th International Conference on Data Engineering (ICDE). :842–853.
Blockchain technology has attracted much attention due to the great success of the cryptocurrencies. Owing to its immutability property and consensus protocol, blockchain offers a new solution for trusted storage and computation services. To scale up the services, prior research has suggested a hybrid storage architecture, where only small meta-data are stored onchain and the raw data are outsourced to off-chain storage. To protect data integrity, a cryptographic proof can be constructed online for queries over the data stored in the system. However, the previous schemes only support simple key-value queries. In this paper, we take the first step toward studying authenticated range queries in the hybrid-storage blockchain. The key challenge lies in how to design an authenticated data structure (ADS) that can be efficiently maintained by the blockchain, in which a unique gas cost model is employed. By analyzing the performance of the existing techniques, we propose a novel ADS, called GEM2-tree, which is not only gas-efficient but also effective in supporting authenticated queries. To further reduce the ADS maintenance cost without sacrificing much the query performance, we also propose an optimized structure, GEM2*-tree, by designing a two-level index structure. Theoretical analysis and empirical evaluation validate the performance of the proposed ADSs.
2020-08-28
Pradhan, Chittaranjan, Banerjee, Debanjan, Nandy, Nabarun, Biswas, Udita.  2019.  Generating Digital Signature using Facial Landmlark Detection. 2019 International Conference on Communication and Signal Processing (ICCSP). :0180—0184.
Information security has developed rapidly over the recent years with a key being the emergence of social media. To standardize this discipline, security of an individual becomes an urgent concern. In 2019, it is estimated that there will be over 2.5 billion social media users around the globe. Unfortunately, anonymous identity has become a major concern for the security advisors. Due to the technological advancements, the phishers are able to access the confidential information. To resolve these issues numerous solutions have been proposed, such as biometric identification, facial and audio recognition etc prior access to any highly secure forum on the web. Generating digital signatures is the recent trend being incorporated in the field of digital security. We have designed an algorithm that after generating 68 point facial landmark, converts the image to a highly compressed and secure digital signature. The proposed algorithm generates a unique signature for an individual which when stored in the user account information database will limit the creation of fake or multiple accounts. At the same time the algorithm reduces the database storage overhead as it stores the facial identity of an individual in the form of a compressed textual signature rather than the traditional method where the image file was being stored, occupying lesser amount of space and making it more efficient in terms of searching, fetching and manipulation. A unique new analysis of the features produced at intermediate layers has been applied. Here, we opt to use the normal and two opposites' angular measures of the triangle as the invariance. It simply acts as the real-time optimized encryption procedure to achieve the reliable security goals explained in detail in the later sections.
2020-03-30
Narendra, Nanjangud C., Shukla, Anshu, Nayak, Sambit, Jagadish, Asha, Kalkur, Rachana.  2019.  Genoma: Distributed Provenance as a Service for IoT-based Systems. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). :755–760.
One of the key aspects of IoT-based systems, which we believe has not been getting the attention it deserves, is provenance. Provenance refers to those actions that record the usage of data in the system, along with the rationale for said usage. Historically, most provenance methods in distributed systems have been tightly coupled with those of the underlying data processing frameworks in such systems. However, in this paper, we argue that IoT provenance requires a different treatment, given the heterogeneity and dynamism of IoT-based systems. In particular, provenance in IoT-based systems should be decoupled as far as possible from the underlying data processing substrates in IoT-based systems.To that end, in this paper, we present Genoma, our ongoing work on a system for provenance-as-a-service in IoT-based systems. By "provenance-as-a-service" we mean the following: distributed provenance across IoT devices, edge and cloud; and agnostic of the underlying data processing substrate. Genoma comprises a set of services that act together to provide useful provenance information to users across the system. We also show how we are realizing Genoma via an implementation prototype built on Apache Atlas and Tinkergraph, through which we are investigating several key research issues in distributed IoT provenance.
2020-06-01
Vishwakarma, Ruchi, Jain, Ankit Kumar.  2019.  A Honeypot with Machine Learning based Detection Framework for defending IoT based Botnet DDoS Attacks. 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). :1019–1024.

With the tremendous growth of IoT botnet DDoS attacks in recent years, IoT security has now become one of the most concerned topics in the field of network security. A lot of security approaches have been proposed in the area, but they still lack in terms of dealing with newer emerging variants of IoT malware, known as Zero-Day Attacks. In this paper, we present a honeypot-based approach which uses machine learning techniques for malware detection. The IoT honeypot generated data is used as a dataset for the effective and dynamic training of a machine learning model. The approach can be taken as a productive outset towards combatting Zero-Day DDoS Attacks which now has emerged as an open challenge in defending IoT against DDoS Attacks.

2020-01-27
Eya, Nnabuike, Alhassan, Haru, AlAbdullah, Ali, Hameed, Khalid, Bin-Melha, Mohammed, Abd-Alhameed, Raed A..  2019.  Improved Group Key Management with Host Mobility Protocol in Wireless Mobile Environment. Proceedings of the International Conference on Information and Communication Technology. :56–64.

Group communication as an efficient communication mechanism, in recent years has become popular. This is due to the increase in group applications and services. Group communication ensures efficient delivery of packets from one source to multiple recipients or many sources to multiple recipients. Group key management in a wireless environment has been an interesting challenge with group communication because of insecure communication channel. The security and integrity of group communication in a wireless environment is a challenge. One of the challenges with group communication is the mobility of group members. Member mobility is a challenge when designing a group key management scheme. There have been several attempts that have been made to design a secure group key management for wireless environment. Not so many successful attempts have towards wireless mobile environments to explicitly address the various challenges with dynamic mobility issue between multiple networks. This research proposes a GKM scheme that tackles mobility in group communication. The protocol is analyzed to assess security and performance requirements. The size of the group variation, the mobility rate variation are carefully observed to determine the impact on the average of rekeying messages generated at every event and also 1-affects-n phenomenon. The results achieved, shows that the proposed protocol outperforms other popular solutions with less number of rekeying messages per event and also less number of affected members per event. Backward and Forward security are preserved for moving members.

2020-01-21
Le, Duc C., Nur Zincir-Heywood, A..  2019.  Machine Learning Based Insider Threat Modelling and Detection. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :1–6.

Recently, malicious insider attacks represent one of the most damaging threats to companies and government agencies. This paper proposes a new framework in constructing a user-centered machine learning based insider threat detection system on multiple data granularity levels. System evaluations and analysis are performed not only on individual data instances but also on normal and malicious insiders, where insider scenario specific results and delay in detection are reported and discussed. Our results show that the machine learning based detection system can learn from limited ground truth and detect new malicious insiders with a high accuracy.

2020-01-13
Mohamed, Nader, Al-Jaroodi, Jameela.  2019.  A Middleware Framework to Address Security Issues in Integrated Multisystem Applications. 2019 IEEE International Systems Conference (SysCon). :1–6.
Integrating multiple programmable components and subsystems developed by different manufacturers into a final system (a system of systems) can create some security concerns. While there are many efforts for developing interoperability approaches to enable smooth, reliable and safe integration among different types of components to build final systems for different applications, less attention is usually given for the security aspects of this integration. This may leave the final systems exposed and vulnerable to potential security attacks. The issues elevate further when such systems are also connected to other networks such as the Internet or systems like fog and cloud computing. This issue can be found in important industrial applications like smart medical, smart manufacturing and smart city systems. As a result, along with performance, safety and reliability; multisystem integration must also be highly secure. This paper discusses the security issues instigated by such integration. In addition, it proposes a middleware framework to address the security issues for integrated multisystem applications.
2020-02-17
Biswal, Satya Ranjan, Swain, Santosh Kumar.  2019.  Model for Study of Malware Propagation Dynamics in Wireless Sensor Network. 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). :647–653.
Wireless Sensor Network (WSN) faces critical security challenges due to malware(worm, virus, malicious code etc.) attack. When a single node gets compromised by malware then start to spread in entire sensor network through neighboring sensor nodes. To understand the dynamics of malware propagation in WSN proposed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model. This model used the concept of epidemiology. The model focused on early detection of malicious signals presence in the network and accordingly application of security mechanism for its removal. The early detection method helps in controlling of malware spread and reduce battery consumption of sensor nodes. In this paper study the dynamics of malware propagation and stability analysis of the system. In epidemiology basic reproduction number is a crucial parameter which is used for the determination of malware status in the system. The expression of basic reproduction number has been obtained. Analyze the propagation dynamics and compared with previous model. The proposed model provides improved security mechanism in comparison to previous one. The extensive simulation results conform the analytical investigation and accuracy of proposed model.