W. Guibene, K. E. Nolan, M. Y. Kelly.
2015.
"Survey on Clean Slate Cellular-IoT Standard Proposals". 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. :1596-1599.
In this paper we investigate the proposals made by various industries for the Cellular Internet of Things (C-IoT). We start by introducing the context of C-IoT and demonstrate how this technology is closely linked to the Low Power-Wide Area (LPWA) technologies and networks. An in-depth look and system level evaluation is given for each clean slate technology and a comparison is made based on its specifications.
W. Guibene, K. E. Nolan, M. Y. Kelly.
2015.
"Survey on Clean Slate Cellular-IoT Standard Proposals". 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. :1596-1599.
In this paper we investigate the proposals made by various industries for the Cellular Internet of Things (C-IoT). We start by introducing the context of C-IoT and demonstrate how this technology is closely linked to the Low Power-Wide Area (LPWA) technologies and networks. An in-depth look and system level evaluation is given for each clean slate technology and a comparison is made based on its specifications.
W. Huang, J. Gu, X. Ma.
2015.
"Visual tracking based on compressive sensing and particle filter". 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE). :1435-1440.
A robust appearance model is usually required in visual tracking, which can handle pose variation, illumination variation, occlusion and many other interferences occurring in video. So far, a number of tracking algorithms make use of image samples in previous frames to update appearance models. There are many limitations of that approach: 1) At the beginning of tracking, there exists no sufficient amount of data for online update because these adaptive models are data-dependent and 2) in many challenging situations, robustly updating the appearance models is difficult, which often results in drift problems. In this paper, we proposed a tracking algorithm based on compressive sensing theory and particle filter framework. Features are extracted by random projection with data-independent basis. Particle filter is employed to make a more accurate estimation of the target location and make much of the updated classifier. The robustness and the effectiveness of our tracker have been demonstrated in several experiments.
W. Ketpan, S. Phonsri, R. Qian, M. Sellathurai.
2015.
"On the Target Detection in OFDM Passive Radar Using MUSIC and Compressive Sensing". 2015 Sensor Signal Processing for Defence (SSPD). :1-5.
The passive radar also known as Green Radar exploits the available commercial communication signals and is useful for target tracking and detection in general. Recent communications standards frequently employ Orthogonal Frequency Division Multiplexing (OFDM) waveforms and wideband for broadcasting. This paper focuses on the recent developments of the target detection algorithms in the OFDM passive radar framework where its channel estimates have been derived using the matched filter concept using the knowledge of the transmitted signals. The MUSIC algorithm, which has been modified to solve this two dimensional delay-Doppler detection problem, is first reviewed. As the target detection problem can be represented as sparse signals, this paper employs compressive sensing to compare with the detection capability of the 2-D MUSIC algorithm. It is found that the previously proposed single time sample compressive sensing cannot significantly reduce the leakage from the direct signal component. Furthermore, this paper proposes the compressive sensing method utilizing multiple time samples, namely l1-SVD, for the detection of multiple targets. In comparison between the MUSIC and compressive sensing, the results show that l1-SVD can decrease the direct signal leakage but its prerequisite of computational resources remains a major issue. This paper also presents the detection performance of these two algorithms for closely spaced targets.
Wade, Mamadou I., Chouikha, Mohamed, Gill, Tepper, Patterson, Wayne, Washington, Talitha M., Zeng, Jianchao.
2019.
Distributed Image Encryption Based On a Homomorphic Cryptographic Approach. 2019 IEEE 10th Annual Ubiquitous Computing, Electronics Mobile Communication Conference (UEMCON). :0686–0696.
The objective of this research is to develop a novel image encryption method that can be used to considerably increase the security of encrypted images. To solve this image security problem, we propose a distributed homomorphic image encryption scheme where the images of interest are those in the visible electromagnetic spectrum. In our encryption phase, a red green blue (RGB) image is first separated into its constituent channel images, and then the numerical intensity value of a pixel from each channel is written as a sum of smaller pixel intensity sub-values, leading to having several component images for each of the R, G, and B-channel images. A homomorphic encryption function is used to separately encrypted each of the pixel intensity sub-values in each component image using an encryption key, leading to a distributed image encryption approach. Each of the encrypted component images can be compressed before transmission and/or storage. In our decryption phase, each encrypted component image is decompressed if necessary, and then the homomorphic property of the encryption function is used to transform the product of individually encrypted pixel intensity sub-values in each encrypted component images, to the encryption of their sum, before applying the corresponding decryption function with a decryption key to recover the original pixel's intensity values for each channel image, and then recovering the original RGB image. Furthermore, a special case of an RGB image encryption and decryption where a pixel's intensity value from each channel is written as a sum of only two sub-values is implemented and simulated with a software. The resulting cipher-images are subject to a range of security tests and analyses. Results from these tests shown that our proposed homomorphic image encryption scheme is robust and can resist security attacks, as well as increases the security of the associated encrypted images. Our proposed homomorphic image encryption scheme has produced highly secure encrypted images.
Wadekar, Isha.
2021.
Artificial Conversational Agent using Robust Adversarial Reinforcement Learning. 2021 International Conference on Computer Communication and Informatics (ICCCI). :1–7.
Reinforcement learning (R.L.) is an effective and practical means for resolving problems where the broker possesses no information or knowledge about the environment. The agent acquires knowledge that is conditioned on two components: trial-and-error and rewards. An R.L. agent determines an effective approach by interacting directly with the setting and acquiring information regarding the circumstances. However, many modern R.L.-based strategies neglect to theorise considering there is an enormous rift within the simulation and the physical world due to which policy-learning tactics displease that stretches from simulation to physical world Even if design learning is achieved in the physical world, the knowledge inadequacy leads to failed generalization policies from suiting to test circumstances. The intention of robust adversarial reinforcement learning(RARL) is where an agent is instructed to perform in the presence of a destabilizing opponent(adversary agent) that connects impedance to the system. The combined trained adversary is reinforced so that the actual agent i.e. the protagonist is equipped rigorously.
Wadhawan, Yatin, Neuman, Clifford.
2016.
Defending Cyber-Physical Attacks on Oil Pipeline Systems: A Game-Theoretic Approach. Proceedings of the 1st International Workshop on AI for Privacy and Security. :7:1–7:8.
The security of critical infrastructures such as oil and gas cyber-physical systems is a significant concern in today's world where malicious activities are frequent like never before. On one side we have cyber criminals who compromise cyber infrastructure to control physical processes; we also have physical criminals who attack the physical infrastructure motivated to destroy the target or to steal oil from pipelines. Unfortunately, due to limited resources and physical dispersion, it is impossible for the system administrator to protect each target all the time. In this research paper, we tackle the problem of cyber and physical attacks on oil pipeline infrastructure by proposing a Stackelberg Security Game of three players: system administrator as a leader, cyber and physical attackers as followers. The novelty of this paper is that we have formulated a real world problem of oil stealing using a game theoretic approach. The game has two different types of targets attacked by two distinct types of adversaries with different motives and who can coordinate to maximize their rewards. The solution to this game assists the system administrator of the oil pipeline cyber-physical system to allocate the cyber security controls for the cyber targets and to assign patrol teams to the pipeline regions efficiently. This paper provides a theoretical framework for formulating and solving the above problem.
Wadhawan, Yatin, Neuman, Clifford.
2016.
Evaluating Resilience of Gas Pipeline Systems Under Cyber-Physical Attacks: A Function-Based Methodology. Proceedings of the 2Nd ACM Workshop on Cyber-Physical Systems Security and Privacy. :71–80.
In this research paper, we present a function-based methodology to evaluate the resilience of gas pipeline systems under two different cyber-physical attack scenarios. The first attack scenario is the pressure integrity attack on the natural gas high-pressure transmission pipeline. Through simulations, we have analyzed the cyber attacks that propagate from cyber to the gas pipeline physical domain, the time before which the SCADA system should respond to such attacks, and finally, an attack which prevents the response of the system. We have used the combined results of simulations of a wireless mesh network for remote terminal units and of a gas pipeline simulation to measure the shortest Time to Criticality (TTC) parameter; the time for an event to reach the failure state. The second attack scenario describes how a failure of a cyber node controlling power grid functionality propagates from cyber to power to gas pipeline systems. We formulate this problem using a graph-theoretic approach and quantify the resilience of the networks by percentage of connected nodes and the length of the shortest path between them. The results show that parameters such as TTC, power distribution capacity of the power grid nodes and percentage of the type of cyber nodes compromised, regulate the efficiency and resilience of the power and gas networks. The analysis of such attack scenarios helps the gas pipeline system administrators design attack remediation algorithms and improve the response of the system to an attack.
Wadsworth, Anthony, Thanoon, Mohammed I., McCurry, Charles, Sabatto, Saleh Zein.
2019.
Development of IIoT Monitoring and Control Security Scheme for Cyber Physical Systems. 2019 SoutheastCon. :1–5.
Industry 4.0 or the fourth industrial revolution encapsulates future industry development trends to achieve more intelligent manufacturing processes, including reliance on Cyber Physical Systems (CPS). The increase in online access and control given by the incorporation of CPSs introduces a new challenge securing the operations of the CPS in that they are not supported by standard security protocols. This paper describes a process used to effectively protect the operations of an IIoT system by implementing security protocols on the CPS within the IIoT. A series of predefined boundary conditions of the safety critical parameters for which a heating and cooling CPS can safely operate within were established. If the CPS is commended to operate outside of these boundaries, it will disconnect from all external communication network and default to some pre-defined safe-operation mode until the system has been evaluated locally by an administrator and released from the safe-mode. This method was tested and validated by establishing a sample IIoT and CPS testbed setup which monitor and control the temperature of a target environment. An attack was initiated to force the target environment outside of the determined safety-critical parameters. The system responded by disabling all network ports and defaulted to the safe-operation mode established previously.
Wagh, D., Pareek, N., Singh, U..
2017.
Elimination of internal attacksfor PUMA in MANET. 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA). 2:478–482.
Mobile ad hoc networks (MANETs) play a significant role for communication whenever infrastructure is not available. In MANET, the group communication-based applications use the multicast routing protocol, where there is a single sender node and a group of receiver nodes. The benefits of multicast routing protocols are the capability to reduce the communication costs and saving the network resources by reproduction of the message over a shared network. The security is the main concern for multicast routing protocol in MANET, as it includes large number of participants. The security issues become more rigorous in a multicast communication due to its high variedness and routing difficulty. In this paper, we consider the internal attack, namely Multicast Announcement Packet Fabrication Attack on PUMA (Protocol for Unified Multicasting through Announcements). We proposed the security approach to detect the attacks as multicast activity-based overhearing technique, i.e., traffic analysis-based detection method with a unique key value. The performance analysis, shows an improved network performance of proposed approach over PUMA.
Wagh, Gaurav S., Mishra, Sumita.
2020.
A Cyber-Resilient Privacy Framework for the Smart Grid with Dynamic Billing Capabilities. 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–6.
The desired features for the smart grid include dynamic billing capabilities along with consumer privacy protection. Existing aggregation-based privacy frameworks have limitations such as centralized designs prone to single points of failure and/or a high computational overload on the smart meters due to in-network aggregation or complex algorithmic operations. Additionally, these existing schemes do not consider how dynamic billing can be implemented while consumer privacy is preserved. In this paper, a cyber-resilient framework that enables dynamic billing while focusing on consumer privacy preservation is proposed. The distributed design provides a framework for spatio-temporal aggregation and keeps the process lightweight for the smart meters. The comparative analysis of our proposed work with existing work shows a significant improvement in terms of the spatial aggregation overhead, overhead on smart meters and scalability. The paper also discusses the resilience of our framework against privacy attacks.
Wagle, S.K., Bazilraj, A.A, Ray, K.P..
2021.
Energy Efficient Security Solution for Attacks on Wireless Sensor Networks. 2021 2nd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS). :313–318.
Wireless Sensor Networks (WSN) are gaining popularity as being the backbone of Cyber physical systems, IOT and various data acquisition from sensors deployed in remote, inaccessible terrains have remote deployment. However due to remote deployment, WSN is an adhoc network of large number of sensors either heli-dropped in inaccessible terrain like volcanoes, Forests, border areas are highly energy deficient and available in large numbers. This makes it the right soup to become vulnerable to various kinds of Security attacks. The lack of energy and resources makes it deprived of developing a robust security code for mitigation of various kinds of attacks. Many attempts have been made to suggest a robust security Protocol. But these consume so much energy, bandwidth, processing power, memory and other resources that the sole purpose of data gathering from inaccessible terrain from energy deprived sensors gets defeated. This paper makes an attempt to study the types of attacks on different layers of WSN and the examine the recent trends in development of various security protocols to mitigate the attacks. Further, we have proposed a simple, lightweight but powerful security protocol known as Simple Sensor Security Protocol (SSSP), which captures the uniqueness of WSN and its isolation from internet to develop an energy efficient security solution.
Wagner, Alan R..
2018.
An Autonomous Architecture That Protects the Right to Privacy. Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society. :330–334.
The advent and widespread adoption of wearable cameras and autonomous robots raises important issues related to privacy. The mobile cameras on these systems record and may re-transmit enormous amounts of video data that can then be used to identify, track, and characterize the behavior of the general populous. This paper presents a preliminary computational architecture designed to preserve specific types of privacy over a video stream by identifying categories of individuals, places, and things that require higher than normal privacy protection. This paper describes the architecture as a whole as well as preliminary results testing aspects of the system. Our intention is to implement and test the system on ground robots and small UAVs and demonstrate that the system can provide selective low-level masking or deletion of data requiring higher privacy protection.
Wagner, Eric, Matzutt, Roman, Pennekamp, Jan, Bader, Lennart, Bajelidze, Irakli, Wehrle, Klaus, Henze, Martin.
2022.
Scalable and Privacy-Focused Company-Centric Supply Chain Management. 2022 IEEE International Conference on Blockchain and Cryptocurrency (ICBC).
Blockchain technology promises to overcome trust and privacy concerns inherent to centralized information sharing. However, current decentralized supply chain management systems do either not meet privacy and scalability requirements or require a trustworthy consortium, which is challenging for increasingly dynamic supply chains with constantly changing participants. In this paper, we propose CCChain, a scalable and privacy-aware supply chain management system that stores all information locally to give companies complete sovereignty over who accesses their data. Still, tamper protection of all data through a permissionless blockchain enables on-demand tracking and tracing of products as well as reliable information sharing while affording the detection of data inconsistencies. Our evaluation confirms that CCChain offers superior scalability in comparison to alternatives while also enabling near real-time tracking and tracing for many, less complex products.
Wagner, Paul Georg, Birnstill, Pascal, Beyerer, Jürgen.
2018.
Distributed Usage Control Enforcement Through Trusted Platform Modules and SGX Enclaves. Proceedings of the 23Nd ACM on Symposium on Access Control Models and Technologies. :85–91.
In the light of mobile and ubiquitous computing, sharing sensitive information across different computer systems has become an increasingly prominent practice. This development entails a demand of access control measures that can protect data even after it has been transferred to a remote computer system. In order to address this problem, sophisticated usage control models have been developed. These models include a client side reference monitor (CRM) that continuously enforces protection policies on foreign data. However, it is still unclear how such a CRM can be properly protected in a hostile environment. The user of the data on the client system can influence the client's state and has physical access to the system. Hence technical measures are required to protect the CRM on a system, which is legitimately used by potential attackers. Existing solutions utilize Trusted Platform Modules (TPMs) to solve this problem by establishing an attestable trust anchor on the client. However, the resulting protocols have several drawbacks that make them infeasible for practical use. This work proposes a reference monitor implementation that establishes trust by using TPMs along with Intel SGX enclaves. First we show how SGX enclaves can realize a subset of the existing usage control requirements. Then we add a TPM to establish and protect a powerful enforcement component on the client. Ultimately this allows us to technically enforce usage control policies on an untrusted remote system.
Wagner, T. J., Ford, T. C..
2020.
Metrics to Meet Security Privacy Requirements with Agile Software Development Methods in a Regulated Environment. 2020 International Conference on Computing, Networking and Communications (ICNC). :17—23.
This work examines metrics that can be used to measure the ability of agile software development methods to meet security and privacy requirements of communications applications. Many implementations of communication protocols, including those in vehicular networks, occur within regulated environments where agile development methods are traditionally discouraged. We propose a framework and metrics to measure adherence to security, quality and software effectiveness regulations if developers desire the cost and schedule benefits of agile methods. After providing an overview of specific challenges that a regulated environment imposes on communications software development, we proceed to examine the 12 agile principles and how they relate to a regulatory environment. From this review we identify two metrics to measure performance of three key regulatory attributes of software for communications applications, and then recommend an approach of either tools, agile methods or DevOps that is best positioned to satisfy its regulated environment attributes. By considering the recommendations in this paper, managers of software-dominant communications programs in a regulated environment can gain insight into leveraging the benefits of agile methods.
Wagner, Torrey J., Ford, Thomas C..
2020.
Metrics to Meet Security amp; Privacy Requirements with Agile Software Development Methods in a Regulated Environment. 2020 International Conference on Computing, Networking and Communications (ICNC). :17—23.
This work examines metrics that can be used to measure the ability of agile software development methods to meet security and privacy requirements of communications applications. Many implementations of communication protocols, including those in vehicular networks, occur within regulated environments where agile development methods are traditionally discouraged. We propose a framework and metrics to measure adherence to security, quality and software effectiveness regulations if developers desire the cost and schedule benefits of agile methods. After providing an overview of specific challenges that a regulated environment imposes on communications software development, we proceed to examine the 12 agile principles and how they relate to a regulatory environment. From this review we identify two metrics to measure performance of three key regulatory attributes of software for communications applications, and then recommend an approach of either tools, agile methods or DevOps that is best positioned to satisfy its regulated environment attributes. By considering the recommendations in this paper, managers of software-dominant communications programs in a regulated environment can gain insight into leveraging the benefits of agile methods.
Waguie, Francxa Tagne, Al-Turjman, Fadi.
2022.
Artificial Intelligence for Edge Computing Security: A Survey. 2022 International Conference on Artificial Intelligence in Everything (AIE). :446—450.
Edge computing is a prospective notion for expanding the potential of cloud computing. It is vital to maintaining a decent atmosphere free of all forms of security and breaches in order to continue utilizing computer services. The security concerns surrounding the edge computing environment has been impeded as a result of the security issues that surround the area. Many researchers have looked into edge computing security issues, however, not all have thoroughly studied the needs. Security requirements are the goals that specify the capabilities and operations that a process that is carried out by a system in order to eliminate various security flaws. The purpose of this study is to give a complete overview of the many different artificial intelligence technologies that are now being utilized for edge computing security with the intention of aiding research in the future in locating research potential. This article analyzed the most recent research and shed light on the following topics: state-of-the-art techniques used to combat security threats, technological trends used by the method, metrics utilize to assess the techniques' ability, and opportunities of research for future researchers in the area of artificial intelligence for edge computing security.
Wah Myint, Phyo Wah, Hlaing, Swe Zin, Htoon, Ei Chaw.
2020.
EAC: Encryption Access Control Scheme for Policy Revocation in Cloud Data. 2020 International Conference on Advanced Information Technologies (ICAIT). :182—187.
Since a lot of information is outsourcing into cloud servers, data confidentiality becomes a higher risk to service providers. To assure data security, Ciphertext Policy Attributes-Based Encryption (CP-ABE) is observed for the cloud environment. Because ciphertexts and secret keys are relying on attributes, the revocation issue becomes a challenge for CP-ABE. This paper proposes an encryption access control (EAC) scheme to fulfill policy revocation which covers both attribute and user revocation. When one of the attributes in an access policy is changed by the data owner, the authorized users should be updated immediately because the revoked users who have gained previous access policy can observe the ciphertext. Especially for data owners, four types of updating policy levels are predefined. By classifying those levels, each secret token key is distinctly generated for each level. Consequently, a new secret key is produced by hashing the secret token key. This paper analyzes the execution times of key generation, encryption, and decryption times between non-revocation and policy revocation cases. Performance analysis for policy revocation is also presented in this paper.
Wahby, Riad S., Ji, Ye, Blumberg, Andrew J., shelat, abhi, Thaler, Justin, Walfish, Michael, Wies, Thomas.
2017.
Full Accounting for Verifiable Outsourcing. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2071–2086.
Systems for verifiable outsourcing incur costs for a prover, a verifier, and precomputation; outsourcing makes sense when the combination of these costs is cheaper than not outsourcing. Yet, when prior works impose quantitative thresholds to analyze whether outsourcing is justified, they generally ignore prover costs. Verifiable ASICs (VA)—in which the prover is a custom chip—is the other way around: its cost calculations ignore precomputation. This paper describes a new VA system, called Giraffe; charges Giraffe for all three costs; and identifies regimes where outsourcing is worthwhile. Giraffe's base is an interactive proof geared to data-parallel computation. Giraffe makes this protocol asymptotically optimal for the prover and improves the verifier's main bottleneck by almost 3x, both of which are of independent interest. Giraffe also develops a design template that produces hardware designs automatically for a wide range of parameters, introduces hardware primitives molded to the protocol's data flows, and incorporates program analyses that expand applicability. Giraffe wins even when outsourcing several tens of sub-computations, scales to 500x larger computations than prior work, and can profitably outsource parts of programs that are not worthwhile to outsource in full.
Waheed, A., Riaz, M., Wani, M. Y..
2017.
Anti-theft mobile phone security system with the help of BIOS. 2017 International Symposium on Wireless Systems and Networks (ISWSN). :1–6.
Mobile tracking is a key challenge that has been investigated from both practical and theoretical aspects. This paper proposes an anti-theft mobile phone security system using basic input/output system (BIOS). This mobile phone security system allows us to determine the position of mobile device. The proposed security system is based on hardware implementation technique in which mobile is designed in such a way that a mobile can be traced out even if battery and Subscriber Identity Module (SIM) are plug-out. Furthermore, we also consider the usage of BIOS and its importance in our daily life. Our proposed solution will help the designers in improving the device security.
Wahyudono, Bintang, Ogi, Dion.
2020.
Implementation of Two Factor Authentication based on RFID and Face Recognition using LBP Algorithm on Access Control System. 2020 International Conference on ICT for Smart Society (ICISS). CFP2013V-ART:1—6.
Studies on two-factor authentication based on RFID and face recognition have been carried out on a large scale. However, these studies didn't discuss the way to overcome the weaknesses of face recognition authentication in the access control systems. In this study, two authentication factors, RFID and face recognition, were implemented using the LBP (Local Binary Pattern) algorithm to overcome weaknesses of face recognition authentication in the access control system. Based on the results of performance testing, the access control system has 100% RFID authentication and 80% face recognition authentication. The average time for the RFID authentication process is 0.03 seconds, the face recognition process is 6.3885 seconds and the verification of the face recognition is 0.1970 seconds. The access control system can still work properly after three days without being switched off. The results of security testing showed that the capabilities spoofing detection has 100% overcome the photo attack.
Wai, Fok Kar, Thing, Vrizlynn L. L..
2021.
Clustering Based Opcode Graph Generation for Malware Variant Detection. 2021 18th International Conference on Privacy, Security and Trust (PST). :1–11.
Malwares are the key means leveraged by threat actors in the cyber space for their attacks. There is a large array of commercial solutions in the market and significant scientific research to tackle the challenge of the detection and defense against malwares. At the same time, attackers also advance their capabilities in creating polymorphic and metamorphic malwares to make it increasingly challenging for existing solutions. To tackle this issue, we propose a methodology to perform malware detection and family attribution. The proposed methodology first performs the extraction of opcodes from malwares in each family and constructs their respective opcode graphs. We explore the use of clustering algorithms on the opcode graphs to detect clusters of malwares within the same malware family. Such clusters can be seen as belonging to different sub-family groups. Opcode graph signatures are built from each detected cluster. Hence, for each malware family, a group of signatures is generated to represent the family. These signatures are used to classify an unknown sample as benign or belonging to one the malware families. We evaluate our methodology by performing experiments on a dataset consisting of both benign files and malware samples belonging to a number of different malware families and comparing the results to existing approach.
Waitelonis, Jörg, Jürges, Henrik, Sack, Harald.
2016.
Don'T Compare Apples to Oranges: Extending GERBIL for a Fine Grained NEL Evaluation. Proceedings of the 12th International Conference on Semantic Systems. :65–72.
In recent years, named entity linking (NEL) tools were primarily developed as general approaches, whereas today numerous tools are focusing on specific domains such as e.g. the mapping of persons and organizations only, or the annotation of locations or events in microposts. However, the available benchmark datasets used for the evaluation of NEL tools do not reflect this focalizing trend. We have analyzed the evaluation process applied in the NEL benchmarking framework GERBIL [16] and its benchmark datasets. Based on these insights we extend the GERBIL framework to enable a more fine grained evaluation and in deep analysis of the used benchmark datasets according to different emphases. In this paper, we present the implementation of an adaptive filter for arbitrary entities as well as a system to automatically measure benchmark dataset properties, such as the extent of content-related ambiguity and diversity. The implementation as well as a result visualization are integrated in the publicly available GERBIL framework.
Wajahat, Ahsan, Imran, Azhar, Latif, Jahanzaib, Nazir, Ahsan, Bilal, Anas.
2019.
A Novel Approach of Unprivileged Keylogger Detection. 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). :1—6.
Nowadays, computers are used everywhere to carry out daily routine tasks. The input devices i.e. keyboard or mouse are used to feed input to computers. The surveillance of input devices is much important as monitoring the users logging activity. A keylogger also referred as a keystroke logger, is a software or hardware device which monitors every keystroke typed by a user. Keylogger runs in the background that user cannot identify its presence. It can be used as monitoring software for parents to keep an eye on children activity on computers and for the owner to monitor their employees. A keylogger (which can be either spyware or software) is a kind of surveillance software that has the ability to store every keystroke in a log file. It is very dangerous for those systems which use their system for daily transaction purpose i.e. Online Banking Systems. A keylogger is a tool, made to save all the keystroke generated through the machine which sanctions hackers to steal sensitive information without user's intention. Privileged also relies on the access for both implementation and placement by Kernel keylogger, the entire message transmitted from the keyboard drivers, while the programmer simply relies on kernel level facilities that interrupt. This certainly needs a large power and expertise for real and error-free execution. However, it has been observed that 90% of the current keyloggers are running in userspace so they do not need any permission for execution. Our aim is focused on detecting userspace keylogger. Our intention is to forbid userspace keylogger from stealing confidential data and information. For this purpose, we use a strategy which is clearly based on detection manner techniques for userspace keyloggers, an essential category of malware packages. We intend to achieve this goal by matching I/O of all processes with some simulated activity of the user, and we assert detection in case the two are highly correlated. The rationale behind this is that the more powerful stream of keystrokes, the more I/O operations are required by the keylogger to log the keystrokes into the file.