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IBM C2090-623 : IBM Cognos Analytics Administrator V11 Exam

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Test Number : C2090-623
Test Name : IBM Cognos Analytics Administrator V11
Vendor Name : IBM
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C2090-623 test Format | C2090-623 Course Contents | C2090-623 Course Outline | C2090-623 test Syllabus | C2090-623 test Objectives

Exam Title : IBM Certified Administrator - IBM Cognos Analytics Administrator V11
Exam ID : C2090-623
Exam Duration : 90 mins
Questions in test : 60
Passing Score : 38 / 60
Official Training : IBM Cognos Analytics - Enterprise Administration (v11.0)
IBM Cognos Analytics: Architecture and Logging (v11.0)
Exam Center : Pearson VUE
Real Questions : IBM Cognos Analytics Administrator Real Questions
VCE Practice Test : IBM C2090-623 Certification VCE Practice Test

Administrative Tasks
- Describe the steps and options in content administration
- Describe the steps of creating a datasource
- Describe configuring the memory settings
- Demonstrate balancing the server components
- Describe using LifeCycle Manager (LCM)
- Describe system backup and restoration
- Describe using administrative portal options
- Identify using Library management 25%
- Describe how to implement and manage audit logging
- Demonstrate troubleshooting techniques
- Describe how to implement and work with tracing
- Identify how to use additional performance tools
- Describe how to monitor system components 20%
Report Execution
- Identify techniques to organize report content in the portal
- Describe the request flow of report execution
- Describe how to manage and schedule reports
- Describe how to manage report execution 15%
Security Tasks
- Describe how to secure an environment
- Describe how authentication is implemented
- Identify how authorization is achieved and implemented
- Describe how to secure content 20%
Server Environment
- Identify the architecture and components
- Describe installation options and configurations
- Demonstrate tasks to implement configuration and performance tuning
- Describe tasks used to manage components
- Demonstrate troubleshooting techniques in the server environment
- Describe maintaining configuration settings 20%

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IBM learning

IBM, AI And The fight For Cybersecurity | C2090-623 cheat sheet and Latest Topics

AI and people work together on Cybersecurity


As artificial Intelligence (AI) turns into a much bigger a part of the IT landscape, cybersecurity is fitting an AI battlefield. The existing and most aggressive assaults in cybersecurity at the moment are leveraging AI to ward off ordinary protection defenses and to counter adversarial responses. The cat and mouse online game between attacker and defender is moving to a unique stage the place AI is augmenting the human aspect. The future of cybersecurity will likely be AI versus AI.

Attackers can use AI in cybersecurity attacks to evade detection (evasive), cover in lots of areas without detection (pervasive) and automatically adapt to counter measures (adaptive).IBM research is the usage of its competencies to help construct the tools to preserve in opposition t assaults of every kind and protect facts privateness.

As firms scan with AI features, computing device gaining knowledge of models that energy AI have develop into so crucial that the fashions themselves are the target of intrusion attacks. These computing device getting to know models are sometimes constructed the use of hours and days of compute time and can contain proprietary assistance, making them useful and a goal for theft. models could be stolen for his or her financial cost or highbrow property they include, or as a way to design countermeasures to the mannequin. The countermeasures may well be used to fool the AI-based mostly techniques into fallacious habits by way of “poisoning” the practicing mannequin or the deployed neural net. This can also be dangerous if that AI mannequin is basic to working an self sufficient vehicle and hacking it puts the defense of the occupants in danger. The proficient AI model may also also be corrupted/exploited in alternative routes to design how one can mis-categorize objects of activity.

The Evolving Threats to Cybersecurity.


The paintings of the attack

Attackers can use AI in cyberattacks to conceal the assault. One aim of IBM analysis’s work in safety AI is to imagine feasible assaults and create shielding innovations earlier than the genuine black hats (criminals) launch an assault. One application IBM created changed into the Adversarial powerful Toolbox (paintings), an open sourced device for use by means of the AI and utility neighborhood for this type of analysis.

IBM research has been investigating how you can create and propagate sophisticated and stealthy malware in order to most effective show/extract itself when it finds itself in the desired region making it undetectable except it is too late.

The DeepLocker attack components


With IBM researchers interest AI and safety, they were decided to create such an attack as part of its countermeasure research. The malware became referred to as DeepLocker. The malware includes the encrypted payload, but not the important thing to decrypt the malware. The key's derived and malware activated when the malware determines it has reached its certain target. To all other defenses and all different potential targets, it'll appear benign and hence will elude detection. With using AI, it might be effortless to mass enhance such malware personalized for each selected target. deciding on the goal might use neural nets to determine the relevant vacation spot through the use of picture recognize photographs or respect voices or noises.

Locksmithing hides the malware unless it will also be activated


a further area of IBM research investigation is providing equipment for differential privacy. Differential protection adds some random bias to a database that anonymizes the facts however doesn’t disrupt the outcomes.

IBM research BlogIBM Differential privateness Library: the single line of code that can protect your facts | IBM analysis weblog

AI Enhances Adversarial assaults

while older adversarial attack patterns had been algorithmic and simpler to realize, new attacks add AI points reminiscent of herbal language processing and a greater natural human laptop interplay to make malware more evasive, pervasive and scalable. The malware will use AI to retain changing kind as a way to be extra evasive and fool average detection options and rules. automatic techniques can make the malware more scalable and mixed with AI can circulate laterally through an business and assault aims with out human intervention.

the use of AI in cybersecurity assaults will doubtless turn into extra pervasive. better unsolicited mail will also be crafted that avoids detection or personalised to a selected target as a kind of spear phishing attack through the use of natural language processing to craft greater human like messages. furthermore, malware may also be wise ample to consider when it is in a honeypot or sandbox and may avoid malicious execution to look greater benign and not tip off security defenses.

Adversarial AI assaults the human element with using AI augmented chatbots to conceal the assault with human-like emulation. this may boost to the factor the place AI powered voice synthesis can idiot individuals into believing that they’re coping with a true human within their corporation.

the use of AI in cyber-assaults is part of the continuum of the functions of AI in cases which are designed to fool people. as an instance, Deepfakes video clips and pictures are positive for social engineering and may erode their believe in a considerable number of medias. textual content is one more leading-side chance for AI with courses equivalent to OpenAI GPT-2 that may generate false text messages that seem extra humanlike and make it tougher to discover.

AI helps humans shield against adversarial attacks

To shield towards adversarial attacks there's the GLTR (http://gltr.io/) device to detect automatically generated text through the use of the very equal machine discovering recommendations to create fake text to determine even if the textual content turned into created by ML. this is an example of using AI to shelter against AI. however is this a struggle that they can win? Detection is getting tougher as AI’s become greater subtle and fashions turn into greater complicated. it's going to get more durable to search for markers that may distinguish between human and AI and can require certain watermarking, digital signatures, or different fingerprinting patterns to determine precise content.

Multilevel AI attacks and Defenses


using AI in cyberattacks makes it an awful lot more durable to defeat as a result of whereas algorithmic code will also be greater effectively matched to an attack pattern, assaults applying laptop gaining knowledge of are an awful lot tougher to admire as a result of its less predictable. it truly is why you need computing device getting to know defenses to counter computing device studying assaults.

The way forward for cybersecurity will need to make the most of AI to counter the unhealthy man’s AI. the use of AI in cybersecurity is so critical that the DARPA created and ran the Cyber Grand problem program in 2016 to incorporated AI assaults in opposition t shielding AI’s in a battle to peer which AI wins. The winner of the Cyber Grand problem used the chance to build a safety enterprise in line with the know-how used in the challenge.

IBM analysis and different security researchers are engaged on techniques with the aid of imagining the attack and creating defenses and counterattacks. it is a critical enviornment of security investment as defenses deserve to retain pace with the attacks. This video game of AI vs. AI in cybersecurity has simplest simply begun.

The writer and individuals of the Tirias research body of workers do not hang equity positions in any of the groups outlined. Tirias research tracks and consults for corporations all through the electronics ecosystem from semiconductors to systems and sensors to the cloud. individuals of the Tirias analysis crew have consulted for IBM, and other companies right through the AI and protection ecosystems.

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